典型文献
DeepCAGE:Incorporating Transcription Factors in Genome-wide Prediction of Chromatin Accessibility
文献摘要：
Although computational approaches have been complementing high-throughput biolog-ical experiments for the identification of functional regions in the human genome,it remains a great challenge to systematically decipher interactions between transcription factors(TFs)and regulatory elements to achieve interpretable annotations of chromatin accessibility across diverse cellular con-texts.To solve this problem,we propose DeepCAGE,a deep learning framework that integrates sequence information and binding statuses of TFs,for the accurate prediction of chromatin acces-sible regions at a genome-wide scale in a variety of cell types.DeepCAGE takes advantage of a den-sely connected deep convolutional neural network architecture to automatically learn sequence signatures of known chromatin accessible regions and then incorporates such features with expres-sion levels and binding activities of human core TFs to predict novel chromatin accessible regions.In a series of systematic comparisons with existing methods,DeepCAGE exhibits superior perfor-mance in not only the classification but also the regression of chromatin accessibility signals.In a detailed analysis of TF activities,DeepCAGE successfully extracts novel binding motifs and mea-sures the contribution of a TF to the regulation with respect to a specific locus in a certain cell type.When applied to whole-genome sequencing data analysis,our method successfully prioritizes puta-tive deleterious variants underlying a human complex trait and thus provides insights into the understanding of disease-associated genetic variants.
文献关键词：
中图分类号：
作者姓名：
Qiao Liu;Kui Hua;Xuegong Zhang;Wing Hung Wong;Rui Jiang
作者机构：
Ministry of Education Key Laboratory of Bioinformatics;Bioinformatics Division,Beijing National Research Center for Information Science and Technology
文献出处：
引用格式：
[1]Qiao Liu;Kui Hua;Xuegong Zhang;Wing Hung Wong;Rui Jiang-.DeepCAGE:Incorporating Transcription Factors in Genome-wide Prediction of Chromatin Accessibility)[J].基因组蛋白质组与生物信息学报（英文版）,2022(03):496-507
A类：
DeepCAGE,statuses,prioritizes
B类：
Incorporating,Transcription,Factors,Genome,wide,Prediction,Chromatin,Accessibility,Although,computational,approaches,have,been,complementing,high,throughput,biolog,experiments,identification,functional,regions,human,genome,remains,great,challenge,systematically,decipher,interactions,between,transcription,factors,TFs,regulatory,elements,achieve,interpretable,annotations,chromatin,accessibility,across,diverse,cellular,texts,To,solve,this,problem,propose,deep,learning,framework,that,integrates,sequence,information,binding,accurate,prediction,scale,variety,types,takes,advantage,sely,connected,convolutional,neural,network,architecture,automatically,signatures,known,accessible,then,incorporates,such,features,expres,levels,activities,core,novel,series,comparisons,existing,methods,exhibits,superior,perfor,mance,only,classification,also,regression,signals,detailed,analysis,successfully,extracts,motifs,mea,sures,contribution,regulation,respect,specific,locus,certain,When,applied,whole,sequencing,data,our,tive,deleterious,variants,underlying,complex,trait,thus,provides,insights,into,understanding,disease,associated,genetic
AB值：
0.617947
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