GERV: a statistical method for generative evaluation of regulatory variants for transcription factor binding.
Identifieur interne : 001240 ( Main/Exploration ); précédent : 001239; suivant : 001241GERV: a statistical method for generative evaluation of regulatory variants for transcription factor binding.
Auteurs : Haoyang Zeng ; Tatsunori Hashimoto ; Daniel D. Kang ; David K. Gifford [États-Unis]Source :
- Bioinformatics (Oxford, England) [ 1367-4811 ] ; 2016.
Descripteurs français
- KwdFr :
- Algorithmes, Annotation de séquence moléculaire, Biologie informatique (), Facteurs de transcription (métabolisme), Génome humain, Humains, Immunoprécipitation de la chromatine, Liaison aux protéines, Modèles statistiques, Polymorphisme de nucléotide simple (génétique), Sites de fixation, Séquences d'acides nucléiques régulatrices (génétique), Séquençage nucléotidique à haut débit, Étude d'association pangénomique.
- MESH :
- génétique : Polymorphisme de nucléotide simple, Séquences d'acides nucléiques régulatrices.
- métabolisme : Facteurs de transcription.
- Algorithmes, Annotation de séquence moléculaire, Biologie informatique, Génome humain, Humains, Immunoprécipitation de la chromatine, Liaison aux protéines, Modèles statistiques, Sites de fixation, Séquençage nucléotidique à haut débit, Étude d'association pangénomique.
English descriptors
- KwdEn :
- Algorithms, Binding Sites, Chromatin Immunoprecipitation, Computational Biology (methods), Genome, Human, Genome-Wide Association Study, High-Throughput Nucleotide Sequencing, Humans, Models, Statistical, Molecular Sequence Annotation, Polymorphism, Single Nucleotide (genetics), Protein Binding, Regulatory Sequences, Nucleic Acid (genetics), Transcription Factors (metabolism).
- MESH :
- chemical , metabolism : Transcription Factors.
- genetics : Polymorphism, Single Nucleotide, Regulatory Sequences, Nucleic Acid.
- methods : Computational Biology.
- Algorithms, Binding Sites, Chromatin Immunoprecipitation, Genome, Human, Genome-Wide Association Study, High-Throughput Nucleotide Sequencing, Humans, Models, Statistical, Molecular Sequence Annotation, Protein Binding.
Abstract
The majority of disease-associated variants identified in genome-wide association studies reside in noncoding regions of the genome with regulatory roles. Thus being able to interpret the functional consequence of a variant is essential for identifying causal variants in the analysis of genome-wide association studies.
DOI: 10.1093/bioinformatics/btv565
PubMed: 26476779
Affiliations:
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Le document en format XML
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Gifford</name><affiliation wicri:level="2"><nlm:affiliation>Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02142, USA and Department of Stem Cell and Regenerative Biology, Harvard University and Harvard Medical School, Cambridge, MA 02138, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02142, USA and Department of Stem Cell and Regenerative Biology, Harvard University and Harvard Medical School, Cambridge, MA 02138</wicri:regionArea><placeName><region type="state">Massachusetts</region></placeName></affiliation></author></analytic><series><title level="j">Bioinformatics (Oxford, England)</title><idno type="eISSN">1367-4811</idno><imprint><date when="2016" type="published">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Binding Sites</term><term>Chromatin Immunoprecipitation</term><term>Computational Biology (methods)</term><term>Genome, Human</term><term>Genome-Wide Association Study</term><term>High-Throughput Nucleotide Sequencing</term><term>Humans</term><term>Models, Statistical</term><term>Molecular Sequence Annotation</term><term>Polymorphism, Single Nucleotide (genetics)</term><term>Protein Binding</term><term>Regulatory Sequences, Nucleic Acid (genetics)</term><term>Transcription Factors (metabolism)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes</term><term>Annotation de séquence moléculaire</term><term>Biologie informatique ()</term><term>Facteurs de transcription (métabolisme)</term><term>Génome humain</term><term>Humains</term><term>Immunoprécipitation de la chromatine</term><term>Liaison aux protéines</term><term>Modèles statistiques</term><term>Polymorphisme de nucléotide simple (génétique)</term><term>Sites de fixation</term><term>Séquences d'acides nucléiques régulatrices (génétique)</term><term>Séquençage nucléotidique à haut débit</term><term>Étude d'association pangénomique</term></keywords><keywords scheme="MESH" type="chemical" qualifier="metabolism" xml:lang="en"><term>Transcription Factors</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Polymorphism, Single Nucleotide</term><term>Regulatory Sequences, Nucleic Acid</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Polymorphisme de nucléotide simple</term><term>Séquences d'acides nucléiques régulatrices</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Computational Biology</term></keywords><keywords scheme="MESH" qualifier="métabolisme" xml:lang="fr"><term>Facteurs de transcription</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Binding Sites</term><term>Chromatin Immunoprecipitation</term><term>Genome, Human</term><term>Genome-Wide Association Study</term><term>High-Throughput Nucleotide Sequencing</term><term>Humans</term><term>Models, Statistical</term><term>Molecular Sequence Annotation</term><term>Protein Binding</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Annotation de séquence moléculaire</term><term>Biologie informatique</term><term>Génome humain</term><term>Humains</term><term>Immunoprécipitation de la chromatine</term><term>Liaison aux protéines</term><term>Modèles statistiques</term><term>Sites de fixation</term><term>Séquençage nucléotidique à haut débit</term><term>Étude d'association pangénomique</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The majority of disease-associated variants identified in genome-wide association studies reside in noncoding regions of the genome with regulatory roles. Thus being able to interpret the functional consequence of a variant is essential for identifying causal variants in the analysis of genome-wide association studies.</div></front></TEI><affiliations><list><country><li>États-Unis</li></country><region><li>Massachusetts</li></region></list><tree><noCountry><name sortKey="Hashimoto, Tatsunori" sort="Hashimoto, Tatsunori" uniqKey="Hashimoto T" first="Tatsunori" last="Hashimoto">Tatsunori Hashimoto</name><name sortKey="Kang, Daniel D" sort="Kang, Daniel D" uniqKey="Kang D" first="Daniel D" last="Kang">Daniel D. Kang</name><name sortKey="Zeng, Haoyang" sort="Zeng, Haoyang" uniqKey="Zeng H" first="Haoyang" last="Zeng">Haoyang Zeng</name></noCountry><country name="États-Unis"><region name="Massachusetts"><name sortKey="Gifford, David K" sort="Gifford, David K" uniqKey="Gifford D" first="David K" last="Gifford">David K. Gifford</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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