383 lines
42 KiB
HTML
383 lines
42 KiB
HTML
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<meta name="title" property="og:title" content="Senior Investigator, Computational Biology Branch, NCBI">
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<title>NLM Intramural Research Program - Stephen Altschul, PhD</title>
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<meta name="DC.Date.Issued" content="2019-12-05" />
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<h1 class="forstaffpages" style="opacity: 1;">Stephen Altschul, PhD</h1>
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<h2>About</h2>
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<h3>Stephen Altschul, PhD</h3>
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Senior Investigator, Computational Biology Branch, NCBI
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<p>My research centers on the comparison and analysis of DNA and protein sequences, with a recent focus on multiple alignments and the correlations among positions within protein superfamilies. </p>
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<h3>Contact Information</h3>
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<p>Building 38A, 8600 Rockville Pike MSC 6075 Bethesda, MD 20894</p>
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<p>Tel: (301) 435-7803</p>
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<p><a href="mailto:altschul@nih.gov">altschul@nih.gov</a></p>
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<h2>Research Interests</h2>
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<p>Correlations in amino acid usage among sequence positions are evident in very large multiple sequence alignments (MSAs). Two distinct hypotheses for how these correlations arise lead to distinct mathematical approaches to their description, recognition and analysis. The first imagines the homologous proteins within a large MSA as having a common three-dimensional structure, and that correlations are due to the physical interaction of residues near to one another within this structure. This approach, in which correlations are modeled directly using pairwise coupling terms, has been extensively studied for many years. It has gained notable recent success with the introduction of Direct Coupling Analysis (DCA), which mitigates the confounding effects of indirect correlations, in which contacting positions i & j and j & k, lead to correlation between non-contacting positions i & k. The second hypothesis imagines the homologous proteins within a large MSA as falling into related families and sub-families, whose divergent but related functions impose different constraints on their constituent members. Under this model, correlations can be completely explained by the hierarchical structure of family and subfamily divergence, without the need to assume correlations between sequence positions within any particular subfamily. The MSA definition and associated statistical model that correspond to this view have been much less widely studied, and have been a principle focus of my recent research.<p>
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<h2>Publications</h2>
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<div class="citation-wrap">
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<div class="ncbi-docsum">
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<span class="authors">
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Neuwald AF, Altschul SF.
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</span><a href="https://pubmed.ncbi.nlm.nih.gov/pubmed/30596639/">
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Statistical investigations of protein residue direct couplings.
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</a><span class="source">PLoS Comput Biol</span>.
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<span class="pubdate">2018 Dec;</span><span class="volume">14</span><span class="issue">(12)</span><span class="pages">:e1006237</span><span>. </span><span class="doi">doi: 10.1371/journal.pcbi.1006237. </span><span class="pubstatus">eCollection 2018 Dec. </span><span class="pmid">PubMed PMID:
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30596639</span><span class="pmcid">; PubMed Central PMCID:
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PMC6329532</span><span>. </span>
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<div class="ncbi-docsum">
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<span class="authors">
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Shah N, Altschul SF, Pop M.
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</span><a href="https://pubmed.ncbi.nlm.nih.gov/pubmed/29588650/">
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Outlier detection in BLAST hits.
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</a><span class="source">Algorithms Mol Biol</span>.
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<span class="pubdate">2018;</span><span class="volume">13</span><span class="pages">:7</span><span>. </span><span class="doi">doi: 10.1186/s13015-018-0126-3. </span><span class="pubstatus">eCollection 2018. </span><span class="pmid">PubMed PMID:
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29588650</span><span class="pmcid">; PubMed Central PMCID:
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PMC5863388</span><span>. </span>
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pmid="28771374"
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<div class="ncbi-docsum">
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<span class="authors">
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Altschul SF, Neuwald AF.
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</span><a href="https://pubmed.ncbi.nlm.nih.gov/pubmed/28771374/">
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Initial Cluster Analysis.
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</a><span class="source">J Comput Biol</span>.
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<span class="pubdate">2018 Feb;</span><span class="volume">25</span><span class="issue">(2)</span><span class="pages">:121-129</span><span>. </span><span class="doi">doi: 10.1089/cmb.2017.0050. </span><span class="pubstatus">Epub 2017 Aug 3. </span><span class="pmid">PubMed PMID:
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28771374</span><span class="pmcid">; PubMed Central PMCID:
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PMC5806593</span><span>. </span>
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<div class="ncbi-docsum">
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<span class="authors">
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Neuwald AF, Aravind L, Altschul SF.
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</span><a href="https://pubmed.ncbi.nlm.nih.gov/pubmed/29336305/">
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Inferring joint sequence-structural determinants of protein functional specificity.
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</a><span class="source">Elife</span>.
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<span class="pubdate">2018 Jan 16;</span><span class="volume">7</span><span>. </span><span class="doi">doi: 10.7554/eLife.29880. </span><span class="pmid">PubMed PMID:
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29336305</span><span class="pmcid">; PubMed Central PMCID:
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PMC5770160</span><span>. </span>
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<h3><a href="https://pubmed.ncbi.nlm.nih.gov/?cmd=Search&term=altschul+sf%5Bau%5D">More</a></h3>
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