机译:结合序列和表观胸组数据来预测使用深度学习预测转录因子结合位点的综合框架
Northwestern Polytech Univ Sch Automat Key Lab Informat Fus Technol Minist Educ Xian 710072 Shaanxi Peoples R China;
Northwestern Polytech Univ Sch Automat Key Lab Informat Fus Technol Minist Educ Xian 710072 Shaanxi Peoples R China;
Chinese Acad Sci Acad Math & Syst Sci RCSDS NCMIS CEMS Beijing 100190 Peoples R China|Univ Chinese Acad Sci Sch Math Sci Beijing 100049 Peoples R China|Chinese Acad Sci Ctr Excellence Anim Evolut & Genet Kunming 650223 Yunnan Peoples R China;
Chinese Acad Sci Acad Math & Syst Sci RCSDS NCMIS CEMS Beijing 100190 Peoples R China|Univ Chinese Acad Sci Sch Math Sci Beijing 100049 Peoples R China|Chinese Acad Sci Ctr Excellence Anim Evolut & Genet Kunming 650223 Yunnan Peoples R China;
Bioinformatics; machine learning; transcription factors binding sites; convolutional neural networks; DNA accessibility; histone modification;
机译:FementOrmet:一种深入学习框架,用于预测细胞类型特异性转录因子与核苷酸分辨率顺序数据结合的
机译:深度卷积神经网络,用于预测与DNA序列数据的白血病相关转录因子结合位点
机译:集成绑定和表达数据以预测转录因子组合功能
机译:结合序列和表观基因组数据,使用深度学习预测转录因子结合位点
机译:使用系统发育足迹和进化转换的概率框架预测转录因子结合位点
机译:整合基因组序列和结构数据进行统计学习以预测转录因子结合位点
机译:Deepd2V:一种新的基于深度学习的框架,用于预测来自组合DNA序列的转录因子结合位点