Prioritization of enhancer mutations by combining allele-specific chromatin accessibility with deep learning

Prioritization of non-coding genome variation benefits from explainable AI to predict and interpret the impact of a mutation on gene regulation. Here we apply a specialized deep learning model to phased melanoma genomes and identify functional enhancer mutations with allelic imbalance of chromatin a...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	bioRxiv 2019
Hauptverfasser:	Atak, Zeynep Kalender, Taskiran, Ibrahim Ihsan, Flerin, Christopher, Mauduit, David, Minnoye, Liesbeth, Hulsemans, Gert, Christiaens, Valerie, Ghanem, Ghanem-Elias, Wouters, Jasper, Aerts, Stein
Format:	Text Resource
Sprache:	eng
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

container_end_page
container_issue
container_start_page
container_title	bioRxiv
container_volume
creator	Atak, Zeynep Kalender Taskiran, Ibrahim Ihsan Flerin, Christopher Mauduit, David Minnoye, Liesbeth Hulsemans, Gert Christiaens, Valerie Ghanem, Ghanem-Elias Wouters, Jasper Aerts, Stein
description	Prioritization of non-coding genome variation benefits from explainable AI to predict and interpret the impact of a mutation on gene regulation. Here we apply a specialized deep learning model to phased melanoma genomes and identify functional enhancer mutations with allelic imbalance of chromatin accessibility and gene expression.
format	Text Resource
fullrecord	<record><control><sourceid>kuleuven_FZOIL</sourceid><recordid>TN_cdi_kuleuven_dspace_123456789_680406</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>123456789_680406</sourcerecordid><originalsourceid>FETCH-kuleuven_dspace_123456789_6804063</originalsourceid><addsrcrecordid>eNqNjL0OgjAURrs4GPQd7uZgSFAQcTYaRwf3plwucmNpSVtUfHp_4gMwneTL-c5U6LNj6zjwSwW2BmwNZBplkBy0ffiNHsoB0LYlGzZXUFqTpth3hFwzAjbOth_RgEIk77lkzWGAB4cGKqIONCn3vc7EpFba0_zPSCyOh8v-FN96Tf2djKx8p5Dkap1mm3xb7GReJFmSp5FYjjNleIZ0fPcNE8RUJw</addsrcrecordid><sourcetype>Institutional Repository</sourcetype><iscdi>true</iscdi><recordtype>text_resource</recordtype></control><display><type>text_resource</type><title>Prioritization of enhancer mutations by combining allele-specific chromatin accessibility with deep learning</title><source>Lirias (KU Leuven Association)</source><creator>Atak, Zeynep Kalender ; Taskiran, Ibrahim Ihsan ; Flerin, Christopher ; Mauduit, David ; Minnoye, Liesbeth ; Hulsemans, Gert ; Christiaens, Valerie ; Ghanem, Ghanem-Elias ; Wouters, Jasper ; Aerts, Stein</creator><creatorcontrib>Atak, Zeynep Kalender ; Taskiran, Ibrahim Ihsan ; Flerin, Christopher ; Mauduit, David ; Minnoye, Liesbeth ; Hulsemans, Gert ; Christiaens, Valerie ; Ghanem, Ghanem-Elias ; Wouters, Jasper ; Aerts, Stein</creatorcontrib><description>Prioritization of non-coding genome variation benefits from explainable AI to predict and interpret the impact of a mutation on gene regulation. Here we apply a specialized deep learning model to phased melanoma genomes and identify functional enhancer mutations with allelic imbalance of chromatin accessibility and gene expression.</description><language>eng</language><publisher>Cold Spring Harbor Laboratory</publisher><ispartof>bioRxiv, 2019</ispartof><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,776,27837</link.rule.ids><linktorsrc>$$Uhttps://lirias.kuleuven.be/handle/123456789/680406$$EView_record_in_KU_Leuven_Association$$FView_record_in_$$GKU_Leuven_Association$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Atak, Zeynep Kalender</creatorcontrib><creatorcontrib>Taskiran, Ibrahim Ihsan</creatorcontrib><creatorcontrib>Flerin, Christopher</creatorcontrib><creatorcontrib>Mauduit, David</creatorcontrib><creatorcontrib>Minnoye, Liesbeth</creatorcontrib><creatorcontrib>Hulsemans, Gert</creatorcontrib><creatorcontrib>Christiaens, Valerie</creatorcontrib><creatorcontrib>Ghanem, Ghanem-Elias</creatorcontrib><creatorcontrib>Wouters, Jasper</creatorcontrib><creatorcontrib>Aerts, Stein</creatorcontrib><title>Prioritization of enhancer mutations by combining allele-specific chromatin accessibility with deep learning</title><title>bioRxiv</title><description>Prioritization of non-coding genome variation benefits from explainable AI to predict and interpret the impact of a mutation on gene regulation. Here we apply a specialized deep learning model to phased melanoma genomes and identify functional enhancer mutations with allelic imbalance of chromatin accessibility and gene expression.</description><fulltext>true</fulltext><rsrctype>text_resource</rsrctype><creationdate>2019</creationdate><recordtype>text_resource</recordtype><sourceid>FZOIL</sourceid><recordid>eNqNjL0OgjAURrs4GPQd7uZgSFAQcTYaRwf3plwucmNpSVtUfHp_4gMwneTL-c5U6LNj6zjwSwW2BmwNZBplkBy0ffiNHsoB0LYlGzZXUFqTpth3hFwzAjbOth_RgEIk77lkzWGAB4cGKqIONCn3vc7EpFba0_zPSCyOh8v-FN96Tf2djKx8p5Dkap1mm3xb7GReJFmSp5FYjjNleIZ0fPcNE8RUJw</recordid><startdate>20191223</startdate><enddate>20191223</enddate><creator>Atak, Zeynep Kalender</creator><creator>Taskiran, Ibrahim Ihsan</creator><creator>Flerin, Christopher</creator><creator>Mauduit, David</creator><creator>Minnoye, Liesbeth</creator><creator>Hulsemans, Gert</creator><creator>Christiaens, Valerie</creator><creator>Ghanem, Ghanem-Elias</creator><creator>Wouters, Jasper</creator><creator>Aerts, Stein</creator><general>Cold Spring Harbor Laboratory</general><scope>FZOIL</scope></search><sort><creationdate>20191223</creationdate><title>Prioritization of enhancer mutations by combining allele-specific chromatin accessibility with deep learning</title><author>Atak, Zeynep Kalender ; Taskiran, Ibrahim Ihsan ; Flerin, Christopher ; Mauduit, David ; Minnoye, Liesbeth ; Hulsemans, Gert ; Christiaens, Valerie ; Ghanem, Ghanem-Elias ; Wouters, Jasper ; Aerts, Stein</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-kuleuven_dspace_123456789_6804063</frbrgroupid><rsrctype>text_resources</rsrctype><prefilter>text_resources</prefilter><language>eng</language><creationdate>2019</creationdate><toplevel>online_resources</toplevel><creatorcontrib>Atak, Zeynep Kalender</creatorcontrib><creatorcontrib>Taskiran, Ibrahim Ihsan</creatorcontrib><creatorcontrib>Flerin, Christopher</creatorcontrib><creatorcontrib>Mauduit, David</creatorcontrib><creatorcontrib>Minnoye, Liesbeth</creatorcontrib><creatorcontrib>Hulsemans, Gert</creatorcontrib><creatorcontrib>Christiaens, Valerie</creatorcontrib><creatorcontrib>Ghanem, Ghanem-Elias</creatorcontrib><creatorcontrib>Wouters, Jasper</creatorcontrib><creatorcontrib>Aerts, Stein</creatorcontrib><collection>Lirias (KU Leuven Association)</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Atak, Zeynep Kalender</au><au>Taskiran, Ibrahim Ihsan</au><au>Flerin, Christopher</au><au>Mauduit, David</au><au>Minnoye, Liesbeth</au><au>Hulsemans, Gert</au><au>Christiaens, Valerie</au><au>Ghanem, Ghanem-Elias</au><au>Wouters, Jasper</au><au>Aerts, Stein</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>Prioritization of enhancer mutations by combining allele-specific chromatin accessibility with deep learning</atitle><jtitle>bioRxiv</jtitle><date>2019-12-23</date><risdate>2019</risdate><abstract>Prioritization of non-coding genome variation benefits from explainable AI to predict and interpret the impact of a mutation on gene regulation. Here we apply a specialized deep learning model to phased melanoma genomes and identify functional enhancer mutations with allelic imbalance of chromatin accessibility and gene expression.</abstract><pub>Cold Spring Harbor Laboratory</pub><oa>free_for_read</oa></addata></record>
fulltext	fulltext_linktorsrc
identifier
ispartof	bioRxiv, 2019
issn
language	eng
recordid	cdi_kuleuven_dspace_123456789_680406
source	Lirias (KU Leuven Association)
title	Prioritization of enhancer mutations by combining allele-specific chromatin accessibility with deep learning
url	https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-04T08%3A59%3A32IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-kuleuven_FZOIL&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=Prioritization%20of%20enhancer%20mutations%20by%20combining%20allele-specific%20chromatin%20accessibility%20with%20deep%20learning&rft.jtitle=bioRxiv&rft.au=Atak,%20Zeynep%20Kalender&rft.date=2019-12-23&rft_id=info:doi/&rft_dat=%3Ckuleuven_FZOIL%3E123456789_680406%3C/kuleuven_FZOIL%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true