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GNormPlus: An Integrative Approach for Tagging Gene, Gene Family and Protein Domain
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<h3>GNormPlus: An Integrative Approach for Tagging Gene, Gene Family and Protein Domain</h3>
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<h4>Authors: <a href="https://sites.google.com/site/chihhsuanwei/" target="_blank">Chih-Hsuan Wei</a>, <a
href="http://myweb.ncku.edu.tw/~hykao/" target="_blank">Hung-Yu Kao</a> and <a
href="/bionlp/" target="_blank">Zhiyong Lu</a> (PI)</h4>
<h4>Research highlights</h4>
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<p>
GNormPlus: an end-to-end system that handles both gene/protein name and identifier detection in
biomedical literature, including gene/protein mentions, family names and domain names. Moreover,
GNormPlus also integrates several advanced text-mining techniques (i.e., <a
href="http://ikmbio.csie.ncku.edu.tw/GN/" target="_blank">GenNorm</a>, <a
href="/CBBresearch/Lu/downloads/SR4GN/" target="_blank">SR4GN</a>,
<a href="/CBBresearch/Lu/Demo/SimConcept/"
target="_blank">SimConcept</a>, <a href="ftp://ftp.ncbi.nlm.nih.gov/pub/wilbur/" target="_blank">Ab3P</a>
and <a href="http://crfpp.googlecode.com/svn/trunk/doc/index.html?source=navbar" target="_blank">CRF++</a>)
for resolving composite gene names. On two public benchmarking datasets, we show that GNormPlus
compares favorably to the other state-of-the-art methods.
</p>
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<h4>Method overview</h4>
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<p>
Our proposed approach includes two main steps: mention recognition and concept normalization,
respectively. In the mention recognition step, we developed a new module based on CRF++, together
with our previous species recognition system (i.e., SR4GN) to recognize gene and species names and
match them accordingly. In concept normalization step, we applied our previous system, GenNorm,
combined with a composite mention simplification tool (i.e., SimConcept) and an abbreviation
resolution tool (i.e., Ab3P) for optimized performance.
</p>
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<h4>Results</h4>
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<p>
The first evaluation is a species-specific experiment where only human genes are considered.
GNormPlus was evaluated on the BioCreative II GN test set. We compared GNormPlus with several
previously reported systems, including our previous system, GenNorm. In the second experiment, we
evaluate GNormPlus in multi-species gene normalization using the BioCreative III GN task data set.
GNormPlus presents a competitive performance in both evaluations.
</p>
<table class="customtable">
<tbody>
<tr>
<td align="center"><strong>Open source tools</strong></td>
<td align="center"><strong>Precision</strong></td>
<td align="center"><strong>Recall</strong></td>
<td align="center"><strong>F-measure</strong></td>
</tr>
<tr>
<td align="center" class="best">GNormPlus</td>
<td align="center" class="best">87.1%</td>
<td align="center" class="best">86.4%</td>
<td align="center" class="best">86.7%</td>
</tr>
<tr>
<td align="center">GenNorm</td>
<td align="center">78.9%</td>
<td align="center">81.4%</td>
<td align="center">80.1%</td>
</tr>
<tr>
<td align="center">GNAT</td>
<td align="center">90.7%</td>
<td align="center">82.4%</td>
<td align="center">86.4%</td>
</tr>
</tbody>
</table>
<span><b>Table 1.</b> The evaluation of human species gene normalization on the BioCreative II GN test set.</span>
<table class="customtable">
<tbody>
<tr>
<td align="center"><strong>Open source tools</strong></td>
<td align="center"><strong>TAP-5</strong></td>
<td align="center"><strong>TAP-10</strong></td>
<td align="center"><strong>TAP-20</strong></td>
<td align="center"><strong>F-measure</strong></td>
</tr>
<tr>
<td align="center" class="best">GNormPlus</td>
<td align="center" class="best">33.3%</td>
<td align="center" class="best">36.7%</td>
<td align="center" class="best">36.7%</td>
<td align="center" class="best">50.1%</td>
</tr>
<tr>
<td align="center">GenNorm</td>
<td align="center">32.8%</td>
<td align="center">35.5%</td>
<td align="center">35.5%</td>
<td align="center">46.9%</td>
</tr>
<tr>
<td align="center">GeneTuKit</td>
<td align="center">29.7%</td>
<td align="center">31.4%</td>
<td align="center">32.5%</td>
<td align="center">-</td>
</tr>
</tbody>
</table>
<span><b>Table 2.</b> The evaluation of multiple species gene normalization on the BioCreative III GN test set.</span>
</div>
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<h4>Downloads</h4>
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GNormPlus Software in <a
href="/CBBresearch/Lu/Demo/tmTools/download/GNormPlus/GNormPlusJava.zip"
target="_blank">Java</a> or <a
href="/CBBresearch/Lu/Demo/tmTools/download/GNormPlus/GNormPlus.zip"
target="_blank">Perl</a><br/>
<a href="/CBBresearch/Lu/Demo/tmTools/download/GNormPlus/GNormPlusCorpus.zip"
target="_blank">GNormPlus Corpus</a><br/>
GNormPlus-tagged PubMed results in <a
href="/CBBresearch/Lu/Demo/PubTator/"
target="_blank">PubTator</a><br/>
<a href="/research/bionlp/APIs/">GNormPlus
RESTful API</a>
</p>
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<h4>Please cite</h4>
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<ul class="dot-list">
<li>Wei C-H, Kao H-Y, Lu Z. <b>GNormPlus: An Integrative Approach for Tagging Gene, Gene Family and
Protein Domain</b>. BioMed Research International Journal, Text Mining for Translational
Bioinformatics special issue, BioMed Research International Journal, Article ID 918710; DOI:
dx.doi.org/10.1155/2015/918710 (2015)
</li>
</ul>
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