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<!DOCTYPE html>
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<head>
<title>fathmm - Home</title>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta name="description" content="Predict the Functional and Phenotypic Consequences of Protein Missense Variants">
<meta name="keywords" content="Missense Mutation, Functional Effects, Inherited Disease Mutation, Cancer Associated Mutation, Amino Acid Substitutions, Hidden Markov Models, HMMs, Single Nucleotide Polymorphisms, SNPs, Non Synonymous Mutation, nsSNPs, fathmm">
<meta name="author" content="Hashem A. Shihab">
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<a class="btn btn-navbar" data-toggle="collapse" data-target=".nav-collapse">
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<a class="brand" href="">fathmm</a>
<div class="nav-collapse collapse">
<ul class="nav">
<li><a href="./index.html">Home</a></li>
<li><a href="./about.html">About</a></li>
<li><a href="https://github.com/HAShihab/fathmm">Download</a></li>
</ul>
<form class="navbar-form pull-right" action="./cgi-bin/results.cgi" method="post" enctype="multipart/form-data">
<input class="span3" type="text" id="session" name="session" placeholder="Enter Your Job/Session Identifier">
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</form>
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</div>
</div>
<div class="hero-unit">
<h2>Functional Analysis through Hidden Markov Models (v2.3)</h2>
<br />
<p>
The Functional Analysis through Hidden Markov Models (fathmm) is a high-throughput web-server capable of predicting the functional, molecular and phenotypic consequences of
protein missense variants using hidden Markov models (HMMs) representing the alignment of homologous sequences
and conserved protein domains.
</p>
</div>
<div id="info" class="modal hide fade" tabindex="-1" role="dialog" aria-labelledby="head" aria-hidden="true">
<div class="modal-header">
<h3 id="head">Description:</h3>
</div>
<div class="modal-body">
<p>
<br />
The Functional Analysis through Hidden Markov Models (fathmm) software and server is a <b>sequence-based algorithm</b> capable of predicting the
<b>functional and phenotypic consequences of protein missense variants</b> by combining sequence conservation within hidden Markov
models (HMMs), representing the alignment of homologous sequences and conserved protein domains, with <b>"pathogenicity weights"</b>, representing
the tolerance of the corresponding model to mutations.
<br /><br />
If you have found this resource useful, please cite the following work:
<br /><br />
Shihab HA, Gough J, Cooper DN, Stenson PD, Barker GLA, Edwards KJ, Day INM, Gaunt, TR. (2013). Predicting the Functional, Molecular and
Phenotypic Consequences of Amino Acid Substitutions using Hidden Markov Models. <i>Hum. Mutat.</i>, <b>34</b>, 57-65
<a href="http://www.ncbi.nlm.nih.gov/pubmed/23033316"><img src="./img/pubmed.png" /></a>
<br />
</p>
</div>
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<div class="row">
<a href="./inherited.html" style="text-decoration: none; color: #555555;">
<div class="span6">
<div class="well well-large">
<center><h4>Analyze Protein Missense Variants</h4></center>
<br />
<p>
Use this option to return predictions capable of discriminating between <b>disease-causing mutations and neutral polymorphisms</b>. In addition,
predictions on the molecular and phenotypic consequences of protein missense variants are also returned.
</p>
</div>
</div>
</a>
<a href="./cancer.html" style="text-decoration: none; color: #555555;">
<div class="span6">
<div class="well well-large">
<center><h4>Analyze Cancer-Associated Variants</h4></center>
<br />
<p>
Use this option to return predictions capable of distinguishing between <b>cancer-promoting/driver mutations, passenger mutations and
other germline polymorphisms</b>.
<br />
<br />
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<center><h4>Rank nsSNPs According to Specific Disease Concepts</h4></center>
<br />
<p>
Use this option to return a customized list of ranked variants that are <b>potentially functionally relevant to to your disease of interest</b> (disease-specific).
<br />
<br />
<br />
</p>
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</a>
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<hr>
<footer>
<p>
If you have found this resource useful, please cite the following work:
<br />
<a href="http://www.ncbi.nlm.nih.gov/pubmed/23033316">Shihab HA, Gough J, Cooper DN, Stenson PD, Barker GLA, Edwards KJ, Day INM, Gaunt, TR. (2013). Predicting the Functional, Molecular and Phenotypic Consequences of Amino Acid Substitutions using Hidden Markov Models. Hum. Mutat., <b>34</b>, 57-65 </a>
</p>
<p>
We welcome any comments and/or suggestions that you may have regarding our software and server - please send an email directly to [email protected]
</p>
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