Team:St Andrews/Human-practices

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   <h1>Scientific impact of iGEM</h1>
   <h1>Scientific impact of iGEM</h1>
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   <p class="lead">"The most influential Synthetic Biology competition" vs. "let the kids play"</p>
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   <p class="lead">"Most influential synthetic biology competition" vs. "Just some kids playing"?</p>
   <div class="subnav">
   <div class="subnav">
     <ul class="nav nav-pills">
     <ul class="nav nav-pills">
       <li><a href="#introduction">Introduction</a></li>
       <li><a href="#introduction">Introduction</a></li>
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       <li><a href="#june">June</a></li>
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       <li><a href="#data-collection">Data collection</a></li>
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      <li><a href="#metrics">Metrics</a></li>
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      <li><a href="#data-analysis">Data analysis</a></li>
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      <li><a href="#citations">Citations</a></li>
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      <li><a href="#conclusion">Conclusion</a></li>
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      <li><a href="#references">References</a></li>
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<!-- Introduction
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<section id="introduction">
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<br>
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<section id="introduction" class="span9">
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<div class="page-header">
<h1>Introduction</h1>
<h1>Introduction</h1>
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</div>
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<img src="https://static.igem.org/mediawiki/2012/a/ac/ImpactLogo_100.png" align="left"></img>
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<p>We wanted to determine how relevant the iGEM competition is for the greater SynBio community. So we investigated the scientific attention garnered by both the iGEM and the Registry of Standard Parts. A data-driven approach was chosen: We extracted data from search results using various queries (such as <code>("iGEM" OR "International Genetically Engineered Machine") AND ("synthetic biology" OR "genetic engineering")</code>) from various publication search engines. We searched <a href="http://apps.webofknowledge.com/">Web of Knowledge</a>, <a href="http://www.scopus.com/home.url">Scopus</a>, <a href="http://www.ncbi.nlm.nih.gov/pubmed/">PubMed</a> and <a href="http://scholar.google.co.uk/">Google Scholar</a>. Google Scholar was chosen to perform more detailed data analysis, as we found the alternatives to have various shortcomings.</p>
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<p>We found that our data results are conclusive with our initial hypothesis: iGEM is an important contributor to the SynBio community. These findings have some implications for the iGEM competition, which we discuss.</p>
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<p>In order to quantify these results further, we analyzed how exactly iGEM and the Registry has been cited. Examining around 50 papers in closer detail, we recommend all papers published by iGEM teams or related to iGEM or the Registry to use a standard citation.</p>
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</section>
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<!-- Data collection
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<section id="data-collection">
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<div class="row">
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<div class="span12">
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<div class="page-header">
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<h1>Data collection <small>Data and where to find it</small></h1>
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</div>
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<h2 id="query-summary">Query summary</h2>
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<p>Here's a quick breakdown of what we queried for on Google Scholar and what sort of data was returned. (The <em>ID</em> matches the name of the data set in our <a href="https://docs.google.com/folder/d/0B6xW2A1PIytESjJ4SUlteG9rUEU/edit?pli=1">data tables</a>). The <i>h-</i> and <i>g-indexes</i> are explained just below!</p>
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<table class="table table-striped">
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<tr>
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<th>Dataset ID</th>
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<th>Plain English query</th>
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<th>Query</th>
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<th>Nº Papers</th>
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<th>Nº Citations</th>
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<th>h-index</th>
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<th>g-index</th>
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<th>Query date</th>
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</tr>
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<tr>
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<td><a href="https://docs.google.com/folder/d/0B6xW2A1PIytESjJ4SUlteG9rUEU/edit?pli=1&docId=0AqxW2A1PIytEdDBNV2ExQnluOXJ6SzlqeEZSQ2twc1E">1</a></td>
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<td>Papers mentioning iGEM in context of synbio</td>
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<td><code>(“synthetic biology” OR "genetic engineering") AND (“iGEM” OR “International Genetically Engineered Machine")</code></td>
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<td>770</td>
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<td>3253</td>
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<td>26</td>
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<td>45</td>
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<td>17/7/2012</td>
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</tr>
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<tr>
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<td><a href="https://docs.google.com/folder/d/0B6xW2A1PIytESjJ4SUlteG9rUEU/edit?pli=1&docId=0AqxW2A1PIytEdDVBSnY4ekt0ZUdJRXZqaFREVmJrUkE">2</a></td>
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<td>All synthetic biology</td>
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<td><code>synthetic biology</code></td>
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<td>1000</td>
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<td>68482</td>
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<td>127</td>
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<td>214</td>
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<td>17/7/2012</td>
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</tr>
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<tr>
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<td><a href="https://docs.google.com/folder/d/0B6xW2A1PIytESjJ4SUlteG9rUEU/edit?pli=1&docId=0AqxW2A1PIytEdFFSV2hEMURWb1pCUmpHY3EyWndHeEE">3</a></td>
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<td>Papers mentioning Registry of Parts</td>
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<td><code>"Registry of Standard Biological Parts" OR "partsregistry.org" OR "parts.mit.edu"</code></td>
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<td>751</td>
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<td>6442</td>
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<td>39</td>
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<td>69</td>
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<td>17/7/2012</td>
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</tr>
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<tr>
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<td><a href="https://docs.google.com/folder/d/0B6xW2A1PIytESjJ4SUlteG9rUEU/edit?pli=1&docId=0AqxW2A1PIytEdFBWY3B5X0tSQl9NTUFCTDhDVGU1dWc">4</a></td>
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<td>Papers citing a particular Part</td>
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<td><code>partsregistry.org/Part:</code></td>
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<td>54</td>
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<td>263</td>
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<td>5</td>
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<td>16</td>
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<td>17/7/2012</td>
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</tr>
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<tr>
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<td><a href="https://docs.google.com/folder/d/0B6xW2A1PIytESjJ4SUlteG9rUEU/edit?pli=1&docId=0AqxW2A1PIytEdFY5ay1oX0lJNEl5Ql84Y0diaUpaLXc">5</a></td>
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<td>Papers mentioning iGEM</td>
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<td><code>iGEM OR "International Genetically Engineered Machine"</code></td>
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<td>1000</td>
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<td>9095</td>
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<td>36</td>
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<td>64</td>
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<td>17/7/2012</td>
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</tr>
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<tr>
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<td><a href="https://docs.google.com/folder/d/0B6xW2A1PIytESjJ4SUlteG9rUEU/edit?pli=1&docId=0AqxW2A1PIytEdGVLRGtzLVF4NXFjOFlOR3dsRENuekE">6</a></td>
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<td>Papers mentioning iGEM and Registry</td>
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<td><code>("iGEM" OR "International Genetically Engineered Machine") AND("Registry of Standard Biological Parts" OR "partsregistry.org" OR "parts.mit.edu")</code></td>
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<td>330</td>
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<td>2208</td>
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<td>23</td>
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<td>42</td>
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<td>17/7/2012</td>
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</tr>
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</table>
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<p><span class="label label-info">Note</span> Searches were capped at a maximum of 1000 results. Hence getting 1000 results for a query implies that <em>more exist</em>! Those first 1000 are only the ones the search engine judged most relevant.
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</p>
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</div>
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<div class="span8 extra-spacing">
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<h2>Why we used Google Scholar</h2>
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<p>All in all, we found Google Scholar to most closely meet our analytic needs.</p>
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        <p>As WoK, Scopus and PubMed are strictly curated databases and limited in scope, they missed many obviously relevant publications. We also found their search options unsuitable: Many of them did not support either full text search (they looked at titles, keywords and abstracts only) or boolean operators. But for the following reasons, we needed a search to include both:
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<ul>
 +
<li>iGEM cannot be expected to always be the main subject of a paper, hence full text search.</li>
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<li>There are many relevant terms floating about iGEM, hence boolean operators like "OR" to allow treating papers that contain "International Genetically Engineered Machine" or the acronym "iGEM" equally.</li>
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</ul>
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        <p></p>
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<p>Just how much wider is Google's search scope? Here is an example: PubMed gave so few results (<strong>16</strong> for <code>iGEM genetic*</code>) that we quickly discarded it. Manually merging the Web of Knowledge and Scopus results for the query <code>iGEM AND genetic*</code> (discarding obviously irrelevant results) gave <strong>43</strong> results. Then we queried Google Scholar. It gave us <strong>770</strong> for <code>(“synthetic biology” OR "genetic engineering") AND (“iGEM” OR “International Genetically Engineered Machine")</code>. </p>
 +
<p>Of course, Google Scholar too is but a bronze bullet: It brings its own drawbacks. It is engineered to pick up things that only <em>seem like</em> scholarly articles. Like Google's search results in general, the results are not curated by a human. This has been criticised in the literature (<a href="http://www.emeraldinsight.com/journals.htm?articleid=1550726&show=abstract">Péter J., 2006.</a>). We found the occasional <a href="https://2012.igem.org/File:TokyoTechNotReallyNature.png">hilarious total miss</a>. Google Scholar is also known to somewhat overestimate citation counts (<a href="http://oneentry.wordpress.com/2006/08/11/research-on-citation-search-in-web-of-science-scopus-and-google-scholar/">Iselid, L., 2006.</a>). However, we concluded from empirical manual examination of a random sample that the majority of the results are plausible and (most importantly) <em>far</em> greater in scope than searches in curated databases. Taking these aspects into consideration, we found Google Scholar best fulfilled our requirements.</p>
 +
<p><span class="label label-warning">Caveat!</span> We only wanted to identify trends. Large and coarse pieces of data with some error were sufficient for this. These values should not be taken as exact!</p>
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</div>
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<div class="span4">
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<h2>Browse the data</h2>
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<p><form action="https://docs.google.com/folder/d/0B6xW2A1PIytESjJ4SUlteG9rUEU/edit">
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<button type="submit" class="btn btn-large btn-info" href="https://docs.google.com/folder/d/0B6xW2A1PIytESjJ4SUlteG9rUEU/edit"><img src="https://static.igem.org/mediawiki/2012/6/61/Glyphicons_090_table.png"></img> Our tables</button></form></p>
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<p>...are online in a nifty and very usable Google Docs folder.</p>
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<p>An introduction is included in case you get lost or want more information.</p>
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 +
<h2 class="extra-spacing">On extraction tools</h2>
 +
<p>We made extensive use of Harzing Publish or Perish (<a href="http://www.harzing.com/pop.htm">Harzing, A.W., 2007.</a>) to scrape Google Scholar results. The tool has many limitations. However, in our experience it is the best available resource for managing the many locations in which scientific publications are deposited.</p>
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<p>We did try other things: Manual methods were too slow for hundreds of papers. Various Firefox browser plugins failed due to the search APIs having changed, were extremely awkward to use or produced clearly erroneous results. The Mac OS program <em>Papers</em> was easy to use and found large numbers of papers (as like Google Scholar it could access many sources), but had unacceptably high rates of error, problems with duplicates and could not export the results into a form we could easily process. Hence <em>Publish or Perish</em>.</p>
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</div>
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</div>
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</section> <!-- End "data-collection" -->
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<!-- Metrics
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<section id="metrics">
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<div class="page-header">
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<h1>Metrics <small>Quantifying scientific impact</small></h1>
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</div>
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<p>Once we had scraped our data from Google Scholar, we needed a method to quantify the relevance of a given scientific article. There are many ways you can quantify success of a paper. Here are a few we investigated:</p>
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<div class="row-fluid">
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<div class="span6">
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<div class="well">
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<h3>Plain citation count</h3>
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<p>High citation count can generally be taken as an indicator of a high-quality or high-impact paper. This is the most traditional method of ranking the influence of papers.</p>
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<p>The main disadvantage of the "citation count"-method is its lack of consistent standards. Even papers within a distinct scientific fields will have differing reference approaches and citation counts. It is also significant that old papers have an edge over newer papers, as they've had more time to be cited. </p>
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</div>
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<div class="well">
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<h3>h-index</h3>
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<p>The h-index is an integer unique to a set of papers. It is used to measure the output and influence of a set of scientists. A greater h-index implies more productive and more influential authors. It was invented by physicist <a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1283832/?tool=pmcentrez">J.E. Hirsch (2005)</a> and has since been automatically calculated by many citation databases. Here is its definition: "A set of papers has h-index <em>h</em> if <em>h</em> papers out of that set have been cited at least <em>h</em> times." An image (<a href="http://en.wikipedia.org/wiki/H-index">"Ael 2" and "Vulpecula", 2012.</a>) clarifies:
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<br /><img src="https://static.igem.org/mediawiki/2012/c/c1/HIndex.png"/></p>
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</div>
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</div>
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<div class="span6">
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<div class="well">
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<h3>g-index</h3>
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<p>The g-index is a citation index meant to quantify the influence of papers. It was proposed by <a href="http://www.springerlink.com/content/4119257t25h0852w/?MUD=MP">Leo Egghe (2006)</a> as a variation to the h-index. It puts more emphasis on the most cited papers and Egghe argues that it ranks highly cited authors more fairly. He gives the following definition: "A set of papers has a g-index <em>g</em> if <em>g</em> is the highest rank such that the top <em>g</em> papers have, together, at least <em>g²</em> citations." Here's a clarifying image by our Polish friend <a href="http://en.wikipedia.org/wiki/File:Gindex1.jpg">("Ael 2", 2012.)</a> again:
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<br /><img src="https://static.igem.org/mediawiki/2012/d/df/GIndex.png" /></p>
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</div>
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<div class="well">
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<h3>Algorithmic methods</h3>
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<p>It's worth noting that there are many other ways of quantifying productivity and impact of a set of papers or scientists. For example, <a href="http://iopscience.iop.org/1367-2630/14/3/033033/">Y.B. Zhou et al (2012)</a> propose a more complete method for "distinguishing prestige from popularity". In their algorithm, the weight of a citation to the influence of a paper is also dependent on the (already calculated) influences of the citing papers and their authors. This requires running a recursive algorithm on sufficiently complete bipartite network of papers and their authors.</p>
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</div><!--close well-->
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<div class="row-fluid">
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<div class="span12">
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<p>Though the alternatives look enticing, we ended up looking mainly at citation count.</p>
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<p>The algorithmic methods were beyond our reach of data availability: We would have had to find the names of every involved person in every iGEM team and all papers they've written, filtering out large amounts of false matches. This was impracticable.</p>
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<p>The h and g-indexes don't actually show more than the raw citation counts when it comes to tendencies over time. Also, we had relatively few search queries to compare against each other, given that two were discarded for having various flaws (discussed just below). This meant that the h and g-index, while valuable methods, were not suitable for our particular data analysis.</p>
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</div>
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<p>Team St Andrews forms, uniting nine students, seven world class researchers and four PhD advisors from disciplines as diverse as Computer Science and Physics, to Biology, Medicine and Chemistry.  </p>
 
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<h2>January - March 2012</h2>
 
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<p>Applications for sponsorship are made to specifically chosen businesses and organisations with an interest in advancing the Life Sciences.  Very quickly, "BioSilta", "GenScript", "Clontech", "Geneious", "Integrated DNA Technologies" and "Thermo Fisher" pledge their support and Team St Andrews grows...</p>
 
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<h2>10 March 2012</h2>
 
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<p>National Science and Engineering Week explodes in Fife with a regional "Science Discovery Day".  Team St Andrews works to convey fundamental concepts in Genetic Engineering and Synthetic Biology to members of the public in new and exciting ways.  The interactive "Codon Game", the 3 Dimensional visualisations of DNA and DNA polymerase 3 and display "E. Coli: under the Microscope" are all well received.  Children and adults alike are fascinated when DNA is extracted from bananas, using everyday kitchen utensils, before their eyes.</p>
 
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<h2>April 2012</h2>
 
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<p>Brainstorming sessions are held as the team researches project ideas.  Some promising titles include:</p>
 
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<ul>
 
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<li><p>"E. Coli and Omega 3: A Project to Feed the Minds of Our Generation"</p></li>
 
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<li><p>"Enzymatic Methane Conversion in Cows: a Sweet Smelling Approach to Reducing Climate Change"</p></li>
 
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<li><p>"Resurfacing Science, Resurfacing our Roads: Cell Factories and Metal Binding Proteins Recover Pavement Platinum"</p></li>
 
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<li><p>"Project Bio-logic-al: Optimizing Soil Composition by Method of Biological Computation"</p></li>
 
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</ul>
 
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<h2>27 April 2012</h2>
 
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<p>Team member Josi presents "Spider Mutants and Bioterrorism - an Overview of Synthetic Biology as an Emerging Scientific Discipline" to a “TEDx” audience of over eighty scientists and non - scientists akin.  Josi views the field as "ground breaking" and by the end of her talk, members of her audience too admit surprise at the wealth of possibilities that this new research area makes available.  There is excitement at the tantalizing proximity of reality of these ideas.</p>
 
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<h2>May 2012</h2>
 
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<p>Project ideas are discussed in greater detail and are filtered until only two research topics remain.  Those preferred ideas are: the production of Omega 3 Fatty Acids by E. Coli Cells ("E. Coli and Omega 3: A Project to Feed the Minds of Our Generation") and the production of Metal – Binding Proteins ("Resurfacing Science, Resurfacing our Roads: Cell Factories and Metal Binding Proteins Recover Pavement Platinum").</p>
 
</section>
</section>
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<!-- June
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<section id="june">
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<section id="data-analysis">
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<br>
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<div class="page-header">
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<h1>June</h1>
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<h1>Data analysis <small>What does this data actually mean?</small></h1>
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<h2><em>Week 1</em></h2>
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</div>
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<h2>4 June 2012</h2>
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<h2>Is our data usable?</h2>
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<h3>Yes. Mostly...</h3>
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<p>Full time work on Team St Andrews' iGEM Project finally begins!  After an initial Group Meeting, two thirds of our student members continue in depth research into those project ideas generated previously; the rest begin work on Team St Andrews' Wiki.</p>
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<p>Given our doubts over accuracy of Google Scholar's data, we considered it a priority to exercise caution with our search query results. This paid off: data we compiled using the search queries of IDs 5 and 2 had fatal flaws. They were rejected from further analysis (discussed below). The other data sets were found to be suitable.</p>
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<p>Our method to examine data suitability was empirical: Random samplings of each data set were passed under human eyes. For <em>most</em> queries, this observation of random subsets showed acceptably low levels of "background static" (i.e. results that Google Scholar had automatically matched to the query, which were not actually relevant). These would form only a drop of error in the ocean of relevant data.</p>
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<h2>5 June 2012</h2>
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-
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<p>"CLC bio" and "Epoch Life Science" are the latest businesses to offer support to Team St Andrews. The former promises CLC bio Main Workbenches to members of the team while the latter offers products and expertise in DNA/ RNA preparation for molecular manipulation.</p>
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<h2>Team "ω-3" weekly summary</h2>
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<p>Research into polyunsaturated fatty acids has been active for over 15 years, with successes varying from creating transgenic plants enriched in ω-3 fatty acids to expressing an entire synthetic pathway from a gene clusters extracted from marine bacteria. We want to expand on this area of research by attempting to express a aerobic synthesis of unsaturated fatty acids in E.coli, which has never been done before. By combining the genes of the cyanobacteria Synechococcus and trypanosome T. brucei into E.coli, this vector should be able to synethise a unsaturated fatty acid up to at least 22-carbon length!</p>
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<p>This week, our team has been focusing on preliminary research by reading relevant scientific papers and understanding the various pathways and methods of recombination. We’re focusing on groundwork research done in the early 1990s that appears to have fallen off the radar, and are excited to see where this path will take us!</p>
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<h2>Team "Metal Binding Protein" weekly summary</h2>
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<p>"After a short meeting (which was dominated by the excitement of receiving our very own iGEM pins) we decided to split our iGEM family of nine into three groups. Josi, Veronica and Yiwang were to look into Omega-3 production; Constantine, Michael and I were to investigate Metal Binding Proteins and Antti, Alexey and Zoe were to focus on setting up the wiki.</p> 
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<p>The wiki team duly produced a sophisticated template.</p>
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<p>The research teams, however, were unanimously agreed that biology is hard. Our motif quickly became standardised.  Read, Think, Re-read, Re-think, Repeat.</p>
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<p>After three days, our previously nomadic team settled in the University’s new Biomedical Sciences Research Complex.  This proved to be a good move as it was followed by breakthroughs on all fronts.  Metal binding peptides were located in their tens and the decision was made to try and express them on the surface of cells in display proteins as well as cytosolically. A membrane protein was found, preliminary peptides selected, and a primer design tutorial set up for the following Monday.  All this success left us with one very important and so far unanswered question- how exactly are we going to assay all this?" (Team Member Hannah Taylor, Week One Report, 12/06/2012)</p>
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<h2><em>Week 2</em></h2>
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<h2>12 June 2012: Team "Metal binding protein"</h2>
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<h3>...but <em>only</em> mostly.</h3>
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<p><strong>Query 5</strong> (<code>iGEM OR "International Genetically Engineered Machine"</code>) was found to have an unacceptably large level of static. The reason was quickly identified: Because the two quoted terms in Query ID 5 (<code>"iGEM"</code>, <code>"International Genetically Engineered Machine"</code>) were separated by a disjunction (<code>OR</code>), the query would easily match anything that contained just the acronym "IGEM"! This meant acronyms in economics such as "Inter-temporal General Equilibrium Model (IGEM)" or the British "Institution of Gas Engineers & Managers (IGEM)" and various medical terms and chemical names snuck in. The entire data set with ID 5 was dismissed from further analysis.</p>
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<p>·    Using E. Coli DH5-alpha: good at replicating vectors but not good at expression
+
<p>The lesson we took from this is not to search for short acronyms by themselves. Query 1 (<code>(“synthetic biology” OR "genetic engineering") AND (“iGEM” OR “International Genetically Engineered Machine")</code>) could be thought of as the "Version Two" of the problematic Query 5. It searches for the same terms, but includes a conjunction (<code>AND</code>) with either <em>synthetic biology</em> or <em>genetic engineering</em>, which bends results toward <em>our</em> iGEM. This tunes static down to an acceptable level.</p>
-
·    Using pGEX-6P-1 vector with internal GST tag, selected with ampicillin
+
-
http://ecoliwiki.net/colipedia/index.php/pGEX-6P-1 (further information via the “source” link)
+
-
·    Purpose:
+
-
o  First day: incorporate desired vectors into vector-replicating E.Coli and incubate them on selective plates to select out recombinant colonies with antibiotics
+
-
o  Second day: incubate the selected colonies in large quantities for vector harvesting
+
-
o  Third day: harvest vector from cell pellet thus pure vector miniprep.</p>
+
-
<h2>12-15 June 2012: Team "Metal binding protein"</h2>
+
<p><strong>Query 2</strong> (<code>synthetic biology</code>) had a different problem: It was too big. The query was an attempt to capture stats for the entire field of synthetic biology, so we could statistically determine the relative influence of the iGEM competition. However, we had forgotten the 1000-result cap imposed by Google Scholar. It is impossible to retrieve results beyond this 1k "event horizon". Google does not publish information regarding how the order of results is determined. Hence these first 1000 results (out of what are likely to be 10s or 100s of thousands of papers) are all biased by some unknown force. Were more cited papers favoured? Were papers published more recently favoured? No conclusions can be drawn from a biased and small subset of the full data. We also discounted data set 2 from any further analysis.</p>
-
<p>Using E. Coli DH5-alpha: good at replicating vectors but not good at expression
+
-
·    Using PET-15b vector: with internal His tag, selected with ampicillin
+
-
http://ecoliwiki.net/colipedia/index.php/pET-15b (further information via the “source” link)
+
-
·    Purpose:
+
-
o  First day: incorporate desired vectors into vector-replicating E.Coli and incubate them on selective plates to select out recombinant colonies with antibiotics
+
-
o  Second day: incubate the selected colonies in large quantities for vector harvesting
+
-
o  Third day: harvest vector from cell pellet thus pure vector miniprep.</p>
+
 +
<p>To emphasize: Data sets 2 and 5 are <em>not included</em> in any further analysis.</p>
 +
<h2>What's is iGEM's impact?</h2>
 +
<p>What does "impact" mean within a scientific context? We will operate under the assumption that <em>having impact</em> correlates strongly with <em>being mentioned</em> in scholarly articles. Hence, we quantify the impact that a term is having simply by searching for that term, and summing up result counts.</p>
 +
<p>Here is a chart summarising how many papers mention various terms floating about iGEM over time:</p>
 +
<div class="row-fluid">
 +
<div class="span8">
 +
    <a class="thumbnail" href="#modal-attention-summary" data-toggle="modal">
 +
      <img src="https://static.igem.org/mediawiki/2012/a/af/DataSummaryStats.png" alt="">
 +
<p class="label-set">
 +
<span class="label" style="background-color:#ffaf2b">Number of teams</span>
 +
<span class="label" style="background-color:#d2eaa2;color:#353535">Parts submitted (10s)</span>
 +
<span class="label" style="background-color:#81ccf1">Papers mentioning iGEM</span>
 +
<span class="label" style="background-color:#7fb02b">Papers mentioning Registry of Parts</span>
 +
<span class="label" style="background-color:#cc6200">Papers mentioning specific Registry Parts</span></p>
 +
      <h5>Chart 1: <em>Summary of iGEM-related attention over time</em></h5>
 +
      <p>This chart shows the amount of "attention" the iGEM competition is receiving over time, shown relative to the growth of the competition itself (quantified by amount of registered teams). "Attention" is measured by amount of papers mentioning certain keywords deemed to be relevant to iGEM or the Registry of Standard Parts. An overall positive trend in proportion with the growth of the competition can be seen.</p>
 +
</a>
 +
</div>
-
<h2>Omega Squad Week 2 Summary</h2>
+
<div class="span4">
 +
<h3>And the answer is...</h3>
 +
<p>Things are looking good for iGEM! Since the first iGEM competition in 2003, more teams are participating each year and more parts are being submitted. The efforts to expose iGEM to the community has paid off - the amount of scientific papers mentioning iGEM and the Registry of Standard Parts has risen, proportional to the increase of the competition itself.</p>
 +
<p>Papers mentioning a specific Registry BioBrick have only begun to appear in recent years, but the numbers show growth. We hypothesize that the Registry's contents is only now reaching the critical mass to become a useful research tool. The founders' dream (<a href="https://igem.org/Press_Kit">iGEM Foundation, 2012b</a>) of "making genetics modular" is becoming reality.</p>
-
<p>This week, we took the first steps to put our grand scheme into laboratorial action! It also occurred to us that if we started calling ourselves DJ Omega 3 & the Fatty Acids, we would intimidate the other squad.</p>
+
<h3>Where this data comes from</h3>
 +
<p>Data about participating teams and number of submitted BioBricks comes from the <a href="https://igem.org/Previous_iGEM_Competitions">iGEM Foundation (2012a)</a>. The other data sets come from the results Google Scholar queries with IDs 1, 3 and 4 (see query summary table above).</p>
 +
</div>
 +
</div>
 +
<h2>Is the relationship between iGEM and the <abbr title="Registry of Standard Biological Parts">Registry</abbr> clear?</h2>
 +
<div class="row-fluid">
 +
<div class="span12 well">
 +
    <ul class="thumbnails">
 +
    <li class="span4">
 +
    <a href="#modal-igem-attention" data-toggle="modal" class="thumbnail">
 +
    <img src="https://static.igem.org/mediawiki/2012/1/12/Data1Chart_ignoresBefore2k.png" alt="">
 +
    <p class="label-set">
 +
    <span class="label" style="background-color:#ff7900">Papers published in that year</span>
 +
    <span class="label" style="background-color:#b0db54">Times those papers were cited</span>
 +
    </p>
 +
    <p><h5>Chart 2: <em>"iGEM" attention</em></h5></p>
 +
    </a>
 +
    </li>
 +
    <li class="span4">
 +
    <a href="#modal-registry-attention" data-toggle="modal" class="thumbnail">
 +
    <img src="https://static.igem.org/mediawiki/2012/3/3f/Data3Chart.png" >
 +
    <p class="label-set">
 +
    <span class="label" style="background-color:#ff7900">Papers published in that year</span>
 +
    <span class="label" style="background-color:#b0db54">Times those papers were cited</span>
 +
    </p>
 +
    <p><h5>Chart 3: <em>"Registry" attention</em></h5></p>
 +
    </a>
 +
    </li>
 +
    <li class="span4">
 +
    <a href="#modal-igem-registry-attention" data-toggle="modal" class="thumbnail">
 +
    <img src="https://static.igem.org/mediawiki/2012/e/ee/Data6Chart.png" alt="">
 +
    <p class="label-set">
 +
    <span class="label" style="background-color:#ff7900">Papers published in that year</span>
 +
    <span class="label" style="background-color:#b0db54">Times those papers were cited</span>
 +
    </p>
 +
    <p><h5>Chart 4: <em>"iGEM and Registry" attention</em></h5></p>
 +
    </a>
 +
    </li>
 +
    </ul>
 +
<p>These three graphs show the amount of papers published each year containing certain search queries, as well as the number of times these papers were cited. All graphs show positive tendencies: the competition is becoming more wide-spread and more iGEM-related papers are being published and recognized. The search queries were chosen to show which part of iGEM is usually cited: the iGEM competition, the Registry of Standard Parts, or both. The data shows that only around half of papers will cite both elements. Some far outlying data points (clear errors) were not plotted to maintain uniform scale.</p>
 +
</div>
 +
</div>
-
<p>First of all, we chose a vector to work in, pET-15B. We started looking into promoters suitable for both the vector and the chain of genes we want to express, and figured out how to use the Registry of Standard Parts. The next step was to design primers for all four of the genes of our pathway - and that was certainly a steep learning curve!</p>
+
<div class="row">
 +
<div class="span5">
 +
<h3>Expectations</h3>
 +
<p>One of the iGEM competition's important goals is to build up well-characterized BioBrick content in the Registry. Thus, the iGEM competition and the Registry are inherently linked. Hence we would expect publications that mention iGEM to also refer to the Registry. However, as the Registry is not <em>only</em> used by iGEM, we expected to also find a large number of papers that mention the Registry <em>without</em> mentioning iGEM.</p>
 +
<p>In other words, we expected:
 +
<ul>
 +
<li>a <em>large proportion</em> of papers that mention <em>iGEM and the Registry</em>,</li>
 +
<li>a <em>large proportion</em> that mention <em>only the Registry</em> and
 +
<li>only a <em>very small proportion</em> that mention <em>only iGEM</em>.</li>
 +
</ul>
 +
</p>
 +
<h3>Yes and No</h3>
 +
<p>The expected proportion of papers mentioning <em>only the Registry</em> was found. However, of the papers that mention iGEM, about half do not mention the Registry. This was a greater proportion than we expected.</p>
 +
<p>We theorise that this may be due to the iGEM Foundation and iGEM teams <em>under-emphasizing</em> their importance to part standardisation. Indeed iGEM is usually presented by the Foundation and teams as "a synthetic biology competition", when really that's just half the picture. We're not just competing, but we also exist for a greater good: <em>Make the Registry better</em> and do our part in helping organise synthetic biology!</p>
 +
</div>
 +
<div class="span7">
 +
<a href="#modal-proportional-mentions" data-toggle="modal" class="thumbnail">
 +
<img src="https://static.igem.org/mediawiki/2012/1/15/DataIgemVsRegistry.png" />
 +
    <p class="label-set">
 +
    <span class="label" style="background-color:#b0db54">Just iGEM</span>
 +
    <span class="label" style="background-color:#ff7900">iGEM and Parts Registry</span>
 +
    <span class="label" style="background-color:#81ccf1">Just Parts Registry</span>
 +
    </p>
 +
<h5>Chart 5: <em>Proportional mentions of iGEM, Registry and Both</em></h5>
 +
<p>This chart is a <strong>stacked</strong> combination of the three charts above. It shows how often <em>iGEM</em>, <em>the Registry</em> and <em>both</em> are mentioned in scientific articles (i.e. how many papers from each year match our search terms). Each of the three quantities has stayed <em>roughly equal</em> to the others throughout the years.</p>
 +
</a><!-- /thumbnail -->
 +
</div>
 +
</div><!-- Close row -->
 +
</section><!-- Close data analysis -->
-
<p>Preliminary tasks done, let’s head to the lab! We carried out a transformation, growing the vector in a DH5-α strain of E. coli with ampicillin as the antibiotic marker. Well, we attempted to carry out a transformation. It failed, much to the glee of the Metal Mickies. Fortunately, we were able to use some pET-15b grown in E. coli for a different purpose. The colonies were allowed to grow, and we then carried out a mini-prep to isolate the vectors. Visualization was done by running the DNA on an agarose gel and using UV light. Once we were sure the transformation was successful, it was time to add the restriction enzymes!</p>
 
-
<p>Also, a PCR was run with the genomic DNA of Leishmania major, the trypanosomatids that are providing us with the 4th gene of our synthesis pathway. We ran 5 samples total: 3 using high-fidelity PCR at different temperatures, and 2 of Clontech’s PCR kits at 2 temperatures. We added the primers for Δ6 elongase (GenBank LmjF32.1160). This gene is around 1.200 kb large. The results show that the Clontech kit run at 48° C gave the strongest result.</p>
+
<section id="citations">
 +
<div style="background-image:url('https://static.igem.org/mediawiki/2012/6/61/Papers_colour.jpg');background-position:top right;background-repeat:no-repeat;background-size:30%" />
 +
<div class="row">
 +
<div class="span9">
 +
<div class="page-header">
 +
<h1>Citations <small>How is iGEM cited and what can we learn from it?</small></h1>
 +
</div>
 +
<div class="row-fluid">
 +
<div class="span6">
 +
<h2>Sourcing data</h2>
 +
<p>In order to analyse how exactly iGEM and the Registry are being cited, we decided to manually examine a set of the papers in our results. We had discarded Scopus and Web of Knowledge earlier when carrying out wide-range data collection. However, for this focused search, the small but certain selection of papers that Scopus and Web of Knowledge gave us was perfect!</p>
-
<h2>Omega Squad Week 3 Summary</h2>
+
<p>We manually combined the results obtained from Scopus and Web of Knowledge. We then deleted duplicates and the few remaining irrelevant publications.</p>
-
<p>This week has been a succession of PCR, digestion, PCR, PCR, digestion, vector growth, more PCR.<p>
+
 
-
<p>We can confidently say that we now know how to set up and run agarose gels! Looking on the bright side of things, we made a lot of mistakes these last few days that we hope to evade in the future: buffers need to be diluted, instructions followed, labels clearly written, and don’t lick the metal poles in the -80° freezer. Just don’t.</p>
+
<p>The keyword “iGEM” gave <strong>41</strong> publications combined from Scopus and <acronym title="Web of Knowledge">WoK</acronym>. Of these, we discarded 16 publications for various reasons:
-
<p>In order to learn all these valuable lessons, we had to sacrifice one thing: results. Many of our PCRs were unsatisfactory, plasmids did not digest properly, E. coli wouldn’t take up the vectors, and it turns out we have a knack for mysteriously making PCRs disappear on agarose gels.</p>
+
<ul>
-
<p>Not until Friday after lunchtime did we finally have some successes:  we found a PCR and the conditions that worked for the gene we are currently working on, the D6 elongase from L. major. Plus, we managed to grow a decent amount of vector and restrict it with enzymes. We hope that we’ve set a good foundation to build on next week – nowhere to go but up!</p>
+
<li>5 texts were non-research articles, such as magazine articles</li>
-
 
+
<li>2 were articles on bioethics that mentioned iGEM only in passing</li>
 +
<li>1 article cited an articles with “iGEM” in the title but was itself unrelated</li>
 +
<li>6 were articles we couldn’t locate or access despite the University of St Andrews having subscriptions to various publishers</li>
 +
<li>2 were in French.</li>
 +
</ul>
 +
</p>
 +
 
 +
<p>This left <strong>25</strong> articles.</p>
 +
</div>
 +
<div class="span6">
 +
<h2>Discussion</h2>
 +
 
 +
<p>We considered citations <em>sufficient</em> when they cited the Registry or named the specific BioBricks used (when appropriate) <em>and</em> citing either the Knight or Endy paper about BioBrick assembly.</p>
 +
 
 +
<p>We examined those 25 articles for how they cited iGEM and the Registry. We found that <strong>11</strong> articles cited iGEM and/or the Registry of Standard Biological Parts satisfactorily.</p>
 +
 
 +
<p>There were two common forms of citation:</p>
 +
<p>
 +
<ul>
 +
<li><em>Registry of Standard Biological Parts [http://www.partsregistry.org].</em></li>
 +
<li><em>Knight, T. F. (2003). Idempotent Vector Design for Standard Assembly of Biobricks.<br />
 +
DOI: 1721.1/21168.</em></li>
 +
</ul>
 +
</p>
 +
 
 +
<p>5 articles did not cite the Registry or BioBricks sufficiently according to our demands.  For one of them, we question its content relevancy. The remaining 4 show examples of simple in-text citation of the Registry, with or without a hyperlink, no mention of the specific BioBrick used, or no mention of BioBricks at all. Surprisingly, each of these papers was associated with an iGEM team.</p>
 +
 
 +
<p>There are 9 additional papers we found in the journal IELTS Synthetic Biology, all of which show vast variations in content, research, and citation quality. The journal seems to have been published once, and seems to have asked all 2006 iGEM finalists to submit a paper based on their research. This resulted in some sub-par articles. Because they weren't peer-reviewed and due to their strong biasing affiliation with iGEM, we disregarded them from our overall data set.</p>
 +
</div>
 +
</div>
 +
</div>
 +
<div class="span3"></div>
 +
</div>
 +
<div class="well">
 +
<h2>Our recommendations</h2>
 +
<p>Reviewing the data, we have concluded that there are standard methods of citation being used by the scientific community to refer to the Parts Registry. In order for the Registry to uphold <em>referencing standards</em> as well as Parts standards within synthetic biology, we think this method of referencing should be officially recommended on the Registry and iGEM website.</p>
 +
 
 +
<p>A clear and standard citation method would support teams who are attempting to publish and let them set an example of citation style to the rest of the scientific community. Additionally, clearly stating a standard method of citation would make citing of the Registry easier and so motivate its citation in general. Of course, more citations means more attention and adoption within the field of synthetic biology.</p>
 +
 
 +
<p>Teams participating in iGEM should be encouraged to cite properly and to try to publish their work. A tutorial of some kind hosted on the iGEM website would help. Such things (among many other bright ideas) were proposed in 2008  by <a href="http://openwetware.org/wiki/User:Macowell/Making_iGEM_Better">Cowell</a>, but haven't been implemented. We see a standardised citation method as a high priority for maximising iGEM's scientific influence.</p>
 +
</div>
</section>
</section>
-
    </div><!-- /container -->
+
<section id="conclusion">
 +
<div class="page-header">
 +
<h1>Conclusion <small>Our <em>Human Practices</em> in a nutshell...</small></h1>
 +
</div>
 +
<p>We found that <span style="background-color:#ecf7d5"><strong>the iGEM competition is making a positive impact.</strong></span> The competition is growing in size and scope, and both iGEM and the Registry are netting a proportionally increasing amount of attention from the scientific community. We are doing well!</p>
-
   </body>
+
<p>However, we also found that <span style="background-color:#d1edf9"><strong>quite a number of discussions of iGEM <em>miss</em> the important connection between our iGEM competition and the Parts Registry</strong></span>. We recommend that the iGEM Foundation and future teams emphasise the iGEM competition's <abbr title="reason for existence">raison d'être</abbr> clearly in the future.</p>
 +
 
 +
<p>We also noticed that <span style="background-color:#ffe6cd"><strong>some papers do not give sufficient or clear credit to the Registry.</strong></span> We interpret this as confusion as to how the Registry should be cited. We recommend that a standardised referencing should be introduced. This would support the publishing process for inexperienced undergraduates involved in the competition, gather greater attention for the iGEM Foundation and Parts Registry and hence further our aims of synthetic biology standardisation. ∎</p>
 +
</section>
 +
 
 +
<!-- References
 +
================================================== -->
 +
<section id="references">
 +
<div class="page-header">
 +
<h1>References</h1>
 +
</div>
 +
 
 +
<p><strong>"Ael 2" and "Vulpecula", 2012.</strong> h-index (Hirsch). <i>Wikipedia</i>. [image online] Available at: &lt;<a href="http://en.wikipedia.org/wiki/File:H-index-en.svg">http://en.wikipedia.org/wiki/File:H-index-en.svg</a>&gt; [Accessed Jul 27, 2012].</p>
 +
 
 +
<p><strong>"Ael 2", 2012.</strong> Illustrated example for the g-index proposed by Egghe. <i>Wikipedia</i> [image online]  Available at: &lt;<a href="http://en.wikipedia.org/wiki/File:Gindex1.jpg">http://en.wikipedia.org/wiki/File:Gindex1.jpg</a>&gt; [Accessed Jul 27, 2012].</p>
 +
 
 +
<p><strong>Cowell, M.L., 2008.</strong> Making iGEM Better. [web page] Available at &lt;<a href="http://openwetware.org/wiki/User:Macowell/Making_iGEM_Better">http://openwetware.org/wiki/User:Macowell/Making_iGEM_Better</a>&gt; [Accessed Jul 19, 2012].</p>
 +
 
 +
<p><strong>Egghe, L., 2006.</strong> Theory and practise of the g-index. <i>Scientometrics</i> [online], Volume 69 (Issue 1), p.131-152. Available at: &lt;<a href="www.springerlink.com/content/4119257t25h0852w/?MUD=MP">www.springerlink.com/content/4119257t25h0852w/?MUD=MP</a>&gt; [Accessed Jun 7, 2012].</p>
 +
 
 +
<p><strong>Harzing, A.W., 2007.</strong> Publish or Perish. [computer program] Available from &lt;<a href="http://www.harzing.com/pop.htm">http://www.harzing.com/pop.htm</a>&gt;</p>
 +
 
 +
<p><strong>Hirsch, J.E., 2005.</strong> An index to quantify an individual's scientific research output. <i>Proceedings of the National Academy of Sciences of the United States of America</i>, Volume 102 (Issue 46). [online] Available at: http://&lt;<a href="www.ncbi.nlm.nih.gov/pmc/articles/PMC1283832/?tool=pmcentrez">www.ncbi.nlm.nih.gov/pmc/articles/PMC1283832/?tool=pmcentrez</a>&gt; [Accessed 5th Jul, 2012]</p>
 +
 
 +
<p><strong>iGEM Foundation, 2012a.</strong> Previous iGEM Competitions. [web page] Available at: &lt;<a href="https://igem.org/Previous_iGEM_Competitions">https://igem.org/Previous_iGEM_Competitions</a>&gt; [Accessed Jul 30, 2012]</p>
 +
 
 +
<p><strong>iGEM Foundation, 2012b.</strong> Press Kit. [web page] Available at: &lt;<a href="https://igem.org/Press_Kit">https://igem.org/Press_Kit</a>&gt; [Accessed Aug 3, 2012]</p>
 +
 
 +
<p><strong>Iselid, L., 2006.</strong> Research on citation search in Web of Science, Scopus and Google Scholar. <i>One Entry to Research</i> [blog] Available at: &lt;<a href="http://oneentry.wordpress.com/2006/08/11/research-on-citation-search-in-web-of-science-scopus-and-google-scholar/">http://oneentry.wordpress.com/2006/08/11/research-on-citation-search-in-web-of-science-scopus-and-google-scholar/</a>&gt; [Accessed Jun 20, 2012].</p>
 +
 
 +
<p><strong>Péter J., 2006.</strong> Dubious hit counts and cuckoo's eggs. <i>Online Information Review</i> [online] Volume 30 (Issue 2) p.188-193. Available at: &lt;<a href="http://www.emeraldinsight.com/journals.htm?articleid=1550726&show=abstract">http://www.emeraldinsight.com/journals.htm?articleid=1550726&show=abstract</a>&gt; [Accessed Jun 20, 2012].</p>
 +
 
 +
<p><strong>Zhou  Y., Liyan L. and Menghui L., 2012.</strong> Quantifying the influence of scientists and their publications: distinguishing between prestige and popularity. <i>New Journal of Physics</i>, [online] Volume 14 (March 2012) Available at: &lt;<a href="http://iopscience.iop.org/1367-2630/14/3/033033/">http://iopscience.iop.org/1367-2630/14/3/033033/</a>&gt; [Accessed Jun 7, 2012].</p>
 +
 
 +
</section><!-- Close references -->
 +
 
 +
 
 +
</div><!-- /container -->
 +
 
 +
<!-- Chart modals -->
 +
 
 +
<div class="modal large hide" id="modal-attention-summary">
 +
   <div class="modal-header">
 +
    <button type="button" class="close" data-dismiss="modal">×</button>
 +
    <h3>Chart zoom: <em>iGEM success summary</em></h3>
 +
  </div>
 +
  <div class="modal-body">
 +
    <img src="https://static.igem.org/mediawiki/2012/a/af/DataSummaryStats.png" alt="">
 +
  </div>
 +
</div>
 +
 
 +
<div class="modal large hide" id="modal-igem-attention">
 +
  <div class="modal-header">
 +
    <button type="button" class="close" data-dismiss="modal">×</button>
 +
    <h3>Chart zoom: <em>iGEM attention</em></h3>
 +
  </div>
 +
  <div class="modal-body">
 +
    <img src="https://static.igem.org/mediawiki/2012/1/12/Data1Chart_ignoresBefore2k.png" alt="">
 +
  </div>
 +
</div>
 +
 
 +
 
 +
<div class="modal large hide" id="modal-igem-registry-attention">
 +
  <div class="modal-header">
 +
    <button type="button" class="close" data-dismiss="modal">×</button>
 +
    <h3>Chart zoom: <em>iGEM and Registry attention</em></h3>
 +
  </div>
 +
  <div class="modal-body">
 +
    <img src="https://static.igem.org/mediawiki/2012/e/ee/Data6Chart.png" alt="">
 +
  </div>
 +
</div>
 +
 
 +
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Latest revision as of 20:00, 26 September 2012

St Andrews iGEM '12

Scientific impact of iGEM

"Most influential synthetic biology competition" vs. "Just some kids playing"?

Introduction

We wanted to determine how relevant the iGEM competition is for the greater SynBio community. So we investigated the scientific attention garnered by both the iGEM and the Registry of Standard Parts. A data-driven approach was chosen: We extracted data from search results using various queries (such as ("iGEM" OR "International Genetically Engineered Machine") AND ("synthetic biology" OR "genetic engineering")) from various publication search engines. We searched Web of Knowledge, Scopus, PubMed and Google Scholar. Google Scholar was chosen to perform more detailed data analysis, as we found the alternatives to have various shortcomings.

We found that our data results are conclusive with our initial hypothesis: iGEM is an important contributor to the SynBio community. These findings have some implications for the iGEM competition, which we discuss.

In order to quantify these results further, we analyzed how exactly iGEM and the Registry has been cited. Examining around 50 papers in closer detail, we recommend all papers published by iGEM teams or related to iGEM or the Registry to use a standard citation.

Data collection Data and where to find it

Query summary

Here's a quick breakdown of what we queried for on Google Scholar and what sort of data was returned. (The ID matches the name of the data set in our data tables). The h- and g-indexes are explained just below!

Dataset ID Plain English query Query Nº Papers Nº Citations h-index g-index Query date
1 Papers mentioning iGEM in context of synbio (“synthetic biology” OR "genetic engineering") AND (“iGEM” OR “International Genetically Engineered Machine") 770 3253 26 45 17/7/2012
2 All synthetic biology synthetic biology 1000 68482 127 214 17/7/2012
3 Papers mentioning Registry of Parts "Registry of Standard Biological Parts" OR "partsregistry.org" OR "parts.mit.edu" 751 6442 39 69 17/7/2012
4 Papers citing a particular Part partsregistry.org/Part: 54 263 5 16 17/7/2012
5 Papers mentioning iGEM iGEM OR "International Genetically Engineered Machine" 1000 9095 36 64 17/7/2012
6 Papers mentioning iGEM and Registry ("iGEM" OR "International Genetically Engineered Machine") AND("Registry of Standard Biological Parts" OR "partsregistry.org" OR "parts.mit.edu") 330 2208 23 42 17/7/2012

Note Searches were capped at a maximum of 1000 results. Hence getting 1000 results for a query implies that more exist! Those first 1000 are only the ones the search engine judged most relevant.

Why we used Google Scholar

All in all, we found Google Scholar to most closely meet our analytic needs.

As WoK, Scopus and PubMed are strictly curated databases and limited in scope, they missed many obviously relevant publications. We also found their search options unsuitable: Many of them did not support either full text search (they looked at titles, keywords and abstracts only) or boolean operators. But for the following reasons, we needed a search to include both:

  • iGEM cannot be expected to always be the main subject of a paper, hence full text search.
  • There are many relevant terms floating about iGEM, hence boolean operators like "OR" to allow treating papers that contain "International Genetically Engineered Machine" or the acronym "iGEM" equally.

Just how much wider is Google's search scope? Here is an example: PubMed gave so few results (16 for iGEM genetic*) that we quickly discarded it. Manually merging the Web of Knowledge and Scopus results for the query iGEM AND genetic* (discarding obviously irrelevant results) gave 43 results. Then we queried Google Scholar. It gave us 770 for (“synthetic biology” OR "genetic engineering") AND (“iGEM” OR “International Genetically Engineered Machine").

Of course, Google Scholar too is but a bronze bullet: It brings its own drawbacks. It is engineered to pick up things that only seem like scholarly articles. Like Google's search results in general, the results are not curated by a human. This has been criticised in the literature (Péter J., 2006.). We found the occasional hilarious total miss. Google Scholar is also known to somewhat overestimate citation counts (Iselid, L., 2006.). However, we concluded from empirical manual examination of a random sample that the majority of the results are plausible and (most importantly) far greater in scope than searches in curated databases. Taking these aspects into consideration, we found Google Scholar best fulfilled our requirements.

Caveat! We only wanted to identify trends. Large and coarse pieces of data with some error were sufficient for this. These values should not be taken as exact!

Browse the data

...are online in a nifty and very usable Google Docs folder.

An introduction is included in case you get lost or want more information.

On extraction tools

We made extensive use of Harzing Publish or Perish (Harzing, A.W., 2007.) to scrape Google Scholar results. The tool has many limitations. However, in our experience it is the best available resource for managing the many locations in which scientific publications are deposited.

We did try other things: Manual methods were too slow for hundreds of papers. Various Firefox browser plugins failed due to the search APIs having changed, were extremely awkward to use or produced clearly erroneous results. The Mac OS program Papers was easy to use and found large numbers of papers (as like Google Scholar it could access many sources), but had unacceptably high rates of error, problems with duplicates and could not export the results into a form we could easily process. Hence Publish or Perish.

Metrics Quantifying scientific impact

Once we had scraped our data from Google Scholar, we needed a method to quantify the relevance of a given scientific article. There are many ways you can quantify success of a paper. Here are a few we investigated:

Plain citation count

High citation count can generally be taken as an indicator of a high-quality or high-impact paper. This is the most traditional method of ranking the influence of papers.

The main disadvantage of the "citation count"-method is its lack of consistent standards. Even papers within a distinct scientific fields will have differing reference approaches and citation counts. It is also significant that old papers have an edge over newer papers, as they've had more time to be cited.

h-index

The h-index is an integer unique to a set of papers. It is used to measure the output and influence of a set of scientists. A greater h-index implies more productive and more influential authors. It was invented by physicist J.E. Hirsch (2005) and has since been automatically calculated by many citation databases. Here is its definition: "A set of papers has h-index h if h papers out of that set have been cited at least h times." An image ("Ael 2" and "Vulpecula", 2012.) clarifies:

g-index

The g-index is a citation index meant to quantify the influence of papers. It was proposed by Leo Egghe (2006) as a variation to the h-index. It puts more emphasis on the most cited papers and Egghe argues that it ranks highly cited authors more fairly. He gives the following definition: "A set of papers has a g-index g if g is the highest rank such that the top g papers have, together, at least g² citations." Here's a clarifying image by our Polish friend ("Ael 2", 2012.) again:

Algorithmic methods

It's worth noting that there are many other ways of quantifying productivity and impact of a set of papers or scientists. For example, Y.B. Zhou et al (2012) propose a more complete method for "distinguishing prestige from popularity". In their algorithm, the weight of a citation to the influence of a paper is also dependent on the (already calculated) influences of the citing papers and their authors. This requires running a recursive algorithm on sufficiently complete bipartite network of papers and their authors.

Though the alternatives look enticing, we ended up looking mainly at citation count.

The algorithmic methods were beyond our reach of data availability: We would have had to find the names of every involved person in every iGEM team and all papers they've written, filtering out large amounts of false matches. This was impracticable.

The h and g-indexes don't actually show more than the raw citation counts when it comes to tendencies over time. Also, we had relatively few search queries to compare against each other, given that two were discarded for having various flaws (discussed just below). This meant that the h and g-index, while valuable methods, were not suitable for our particular data analysis.

Data analysis What does this data actually mean?

Is our data usable?

Yes. Mostly...

Given our doubts over accuracy of Google Scholar's data, we considered it a priority to exercise caution with our search query results. This paid off: data we compiled using the search queries of IDs 5 and 2 had fatal flaws. They were rejected from further analysis (discussed below). The other data sets were found to be suitable.

Our method to examine data suitability was empirical: Random samplings of each data set were passed under human eyes. For most queries, this observation of random subsets showed acceptably low levels of "background static" (i.e. results that Google Scholar had automatically matched to the query, which were not actually relevant). These would form only a drop of error in the ocean of relevant data.

...but only mostly.

Query 5 (iGEM OR "International Genetically Engineered Machine") was found to have an unacceptably large level of static. The reason was quickly identified: Because the two quoted terms in Query ID 5 ("iGEM", "International Genetically Engineered Machine") were separated by a disjunction (OR), the query would easily match anything that contained just the acronym "IGEM"! This meant acronyms in economics such as "Inter-temporal General Equilibrium Model (IGEM)" or the British "Institution of Gas Engineers & Managers (IGEM)" and various medical terms and chemical names snuck in. The entire data set with ID 5 was dismissed from further analysis.

The lesson we took from this is not to search for short acronyms by themselves. Query 1 ((“synthetic biology” OR "genetic engineering") AND (“iGEM” OR “International Genetically Engineered Machine")) could be thought of as the "Version Two" of the problematic Query 5. It searches for the same terms, but includes a conjunction (AND) with either synthetic biology or genetic engineering, which bends results toward our iGEM. This tunes static down to an acceptable level.

Query 2 (synthetic biology) had a different problem: It was too big. The query was an attempt to capture stats for the entire field of synthetic biology, so we could statistically determine the relative influence of the iGEM competition. However, we had forgotten the 1000-result cap imposed by Google Scholar. It is impossible to retrieve results beyond this 1k "event horizon". Google does not publish information regarding how the order of results is determined. Hence these first 1000 results (out of what are likely to be 10s or 100s of thousands of papers) are all biased by some unknown force. Were more cited papers favoured? Were papers published more recently favoured? No conclusions can be drawn from a biased and small subset of the full data. We also discounted data set 2 from any further analysis.

To emphasize: Data sets 2 and 5 are not included in any further analysis.

What's is iGEM's impact?

What does "impact" mean within a scientific context? We will operate under the assumption that having impact correlates strongly with being mentioned in scholarly articles. Hence, we quantify the impact that a term is having simply by searching for that term, and summing up result counts.

Here is a chart summarising how many papers mention various terms floating about iGEM over time:

Number of teams Parts submitted (10s) Papers mentioning iGEM Papers mentioning Registry of Parts Papers mentioning specific Registry Parts

Chart 1: Summary of iGEM-related attention over time

This chart shows the amount of "attention" the iGEM competition is receiving over time, shown relative to the growth of the competition itself (quantified by amount of registered teams). "Attention" is measured by amount of papers mentioning certain keywords deemed to be relevant to iGEM or the Registry of Standard Parts. An overall positive trend in proportion with the growth of the competition can be seen.

And the answer is...

Things are looking good for iGEM! Since the first iGEM competition in 2003, more teams are participating each year and more parts are being submitted. The efforts to expose iGEM to the community has paid off - the amount of scientific papers mentioning iGEM and the Registry of Standard Parts has risen, proportional to the increase of the competition itself.

Papers mentioning a specific Registry BioBrick have only begun to appear in recent years, but the numbers show growth. We hypothesize that the Registry's contents is only now reaching the critical mass to become a useful research tool. The founders' dream (iGEM Foundation, 2012b) of "making genetics modular" is becoming reality.

Where this data comes from

Data about participating teams and number of submitted BioBricks comes from the iGEM Foundation (2012a). The other data sets come from the results Google Scholar queries with IDs 1, 3 and 4 (see query summary table above).

Is the relationship between iGEM and the Registry clear?

These three graphs show the amount of papers published each year containing certain search queries, as well as the number of times these papers were cited. All graphs show positive tendencies: the competition is becoming more wide-spread and more iGEM-related papers are being published and recognized. The search queries were chosen to show which part of iGEM is usually cited: the iGEM competition, the Registry of Standard Parts, or both. The data shows that only around half of papers will cite both elements. Some far outlying data points (clear errors) were not plotted to maintain uniform scale.

Expectations

One of the iGEM competition's important goals is to build up well-characterized BioBrick content in the Registry. Thus, the iGEM competition and the Registry are inherently linked. Hence we would expect publications that mention iGEM to also refer to the Registry. However, as the Registry is not only used by iGEM, we expected to also find a large number of papers that mention the Registry without mentioning iGEM.

In other words, we expected:

  • a large proportion of papers that mention iGEM and the Registry,
  • a large proportion that mention only the Registry and
  • only a very small proportion that mention only iGEM.

Yes and No

The expected proportion of papers mentioning only the Registry was found. However, of the papers that mention iGEM, about half do not mention the Registry. This was a greater proportion than we expected.

We theorise that this may be due to the iGEM Foundation and iGEM teams under-emphasizing their importance to part standardisation. Indeed iGEM is usually presented by the Foundation and teams as "a synthetic biology competition", when really that's just half the picture. We're not just competing, but we also exist for a greater good: Make the Registry better and do our part in helping organise synthetic biology!

Just iGEM iGEM and Parts Registry Just Parts Registry

Chart 5: Proportional mentions of iGEM, Registry and Both

This chart is a stacked combination of the three charts above. It shows how often iGEM, the Registry and both are mentioned in scientific articles (i.e. how many papers from each year match our search terms). Each of the three quantities has stayed roughly equal to the others throughout the years.

Citations How is iGEM cited and what can we learn from it?

Sourcing data

In order to analyse how exactly iGEM and the Registry are being cited, we decided to manually examine a set of the papers in our results. We had discarded Scopus and Web of Knowledge earlier when carrying out wide-range data collection. However, for this focused search, the small but certain selection of papers that Scopus and Web of Knowledge gave us was perfect!

We manually combined the results obtained from Scopus and Web of Knowledge. We then deleted duplicates and the few remaining irrelevant publications.

The keyword “iGEM” gave 41 publications combined from Scopus and WoK. Of these, we discarded 16 publications for various reasons:

  • 5 texts were non-research articles, such as magazine articles
  • 2 were articles on bioethics that mentioned iGEM only in passing
  • 1 article cited an articles with “iGEM” in the title but was itself unrelated
  • 6 were articles we couldn’t locate or access despite the University of St Andrews having subscriptions to various publishers
  • 2 were in French.

This left 25 articles.

Discussion

We considered citations sufficient when they cited the Registry or named the specific BioBricks used (when appropriate) and citing either the Knight or Endy paper about BioBrick assembly.

We examined those 25 articles for how they cited iGEM and the Registry. We found that 11 articles cited iGEM and/or the Registry of Standard Biological Parts satisfactorily.

There were two common forms of citation:

  • Registry of Standard Biological Parts [http://www.partsregistry.org].
  • Knight, T. F. (2003). Idempotent Vector Design for Standard Assembly of Biobricks.
    DOI: 1721.1/21168.

5 articles did not cite the Registry or BioBricks sufficiently according to our demands. For one of them, we question its content relevancy. The remaining 4 show examples of simple in-text citation of the Registry, with or without a hyperlink, no mention of the specific BioBrick used, or no mention of BioBricks at all. Surprisingly, each of these papers was associated with an iGEM team.

There are 9 additional papers we found in the journal IELTS Synthetic Biology, all of which show vast variations in content, research, and citation quality. The journal seems to have been published once, and seems to have asked all 2006 iGEM finalists to submit a paper based on their research. This resulted in some sub-par articles. Because they weren't peer-reviewed and due to their strong biasing affiliation with iGEM, we disregarded them from our overall data set.

Our recommendations

Reviewing the data, we have concluded that there are standard methods of citation being used by the scientific community to refer to the Parts Registry. In order for the Registry to uphold referencing standards as well as Parts standards within synthetic biology, we think this method of referencing should be officially recommended on the Registry and iGEM website.

A clear and standard citation method would support teams who are attempting to publish and let them set an example of citation style to the rest of the scientific community. Additionally, clearly stating a standard method of citation would make citing of the Registry easier and so motivate its citation in general. Of course, more citations means more attention and adoption within the field of synthetic biology.

Teams participating in iGEM should be encouraged to cite properly and to try to publish their work. A tutorial of some kind hosted on the iGEM website would help. Such things (among many other bright ideas) were proposed in 2008 by Cowell, but haven't been implemented. We see a standardised citation method as a high priority for maximising iGEM's scientific influence.

Conclusion Our Human Practices in a nutshell...

We found that the iGEM competition is making a positive impact. The competition is growing in size and scope, and both iGEM and the Registry are netting a proportionally increasing amount of attention from the scientific community. We are doing well!

However, we also found that quite a number of discussions of iGEM miss the important connection between our iGEM competition and the Parts Registry. We recommend that the iGEM Foundation and future teams emphasise the iGEM competition's raison d'être clearly in the future.

We also noticed that some papers do not give sufficient or clear credit to the Registry. We interpret this as confusion as to how the Registry should be cited. We recommend that a standardised referencing should be introduced. This would support the publishing process for inexperienced undergraduates involved in the competition, gather greater attention for the iGEM Foundation and Parts Registry and hence further our aims of synthetic biology standardisation. ∎

References

"Ael 2" and "Vulpecula", 2012. h-index (Hirsch). Wikipedia. [image online] Available at: <http://en.wikipedia.org/wiki/File:H-index-en.svg> [Accessed Jul 27, 2012].

"Ael 2", 2012. Illustrated example for the g-index proposed by Egghe. Wikipedia [image online] Available at: <http://en.wikipedia.org/wiki/File:Gindex1.jpg> [Accessed Jul 27, 2012].

Cowell, M.L., 2008. Making iGEM Better. [web page] Available at <http://openwetware.org/wiki/User:Macowell/Making_iGEM_Better> [Accessed Jul 19, 2012].

Egghe, L., 2006. Theory and practise of the g-index. Scientometrics [online], Volume 69 (Issue 1), p.131-152. Available at: <www.springerlink.com/content/4119257t25h0852w/?MUD=MP> [Accessed Jun 7, 2012].

Harzing, A.W., 2007. Publish or Perish. [computer program] Available from <http://www.harzing.com/pop.htm>

Hirsch, J.E., 2005. An index to quantify an individual's scientific research output. Proceedings of the National Academy of Sciences of the United States of America, Volume 102 (Issue 46). [online] Available at: http://<www.ncbi.nlm.nih.gov/pmc/articles/PMC1283832/?tool=pmcentrez> [Accessed 5th Jul, 2012]

iGEM Foundation, 2012a. Previous iGEM Competitions. [web page] Available at: <https://igem.org/Previous_iGEM_Competitions> [Accessed Jul 30, 2012]

iGEM Foundation, 2012b. Press Kit. [web page] Available at: <https://igem.org/Press_Kit> [Accessed Aug 3, 2012]

Iselid, L., 2006. Research on citation search in Web of Science, Scopus and Google Scholar. One Entry to Research [blog] Available at: <http://oneentry.wordpress.com/2006/08/11/research-on-citation-search-in-web-of-science-scopus-and-google-scholar/> [Accessed Jun 20, 2012].

Péter J., 2006. Dubious hit counts and cuckoo's eggs. Online Information Review [online] Volume 30 (Issue 2) p.188-193. Available at: <http://www.emeraldinsight.com/journals.htm?articleid=1550726&show=abstract> [Accessed Jun 20, 2012].

Zhou Y., Liyan L. and Menghui L., 2012. Quantifying the influence of scientists and their publications: distinguishing between prestige and popularity. New Journal of Physics, [online] Volume 14 (March 2012) Available at: <http://iopscience.iop.org/1367-2630/14/3/033033/> [Accessed Jun 7, 2012].

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University of St Andrews, 2012.

Contact us: igem2012@st-andrews.ac.uk, Twitter, Facebook

This iGEM team has been funded by the MSD Scottish Life Sciences Fund. The opinions expressed by this iGEM team are those of the team members and do not necessarily represent those of Merck Sharp & Dohme Limited, nor its Affiliates.

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