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OpenAnnotate: a web server to annotate the chromatin accessibility of genomic regions 期刊论文
NUCLEIC ACIDS RESEARCH, 2021, 卷号: 49, 期号: W1, 页码: W483-W490
Authors:  Chen, Shengquan;  Liu, Qiao;  Cui, Xuejian;  Feng, Zhanying;  Li, Chunquan;  Wang, Xiaowo;  Zhang, Xuegong;  Wang, Yong;  Jiang, Rui
Favorite  |  View/Download:1/0  |  Submit date:2021/10/26
hReg-CNCC reconstructs a regulatory network in human cranial neural crest cells and annotates variants in a developmental context 期刊论文
COMMUNICATIONS BIOLOGY, 2021, 卷号: 4, 期号: 1, 页码: 16
Authors:  Feng, Zhanying;  Duren, Zhana;  Xiong, Ziyi;  Wang, Sijia;  Liu, Fan;  Wong, Wing Hung;  Wang, Yong
Favorite  |  View/Download:20/0  |  Submit date:2021/06/01
An Integrative Framework for Combining Sequence and Epigenomic Data to Predict Transcription Factor Binding Sites Using Deep Learning 期刊论文
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2021, 卷号: 18, 期号: 1, 页码: 355-364
Authors:  Jing, Fang;  Zhang, Shao-Wu;  Cao, Zhen;  Zhang, Shihua
Favorite  |  View/Download:12/0  |  Submit date:2021/04/26
Bioinformatics  machine learning  transcription factors binding sites  convolutional neural networks  DNA accessibility  histone modification  
Prediction of enhancer–promoter interactions using the cross-cell type information and domain adversarial neural network 期刊论文
BMC Bioinformatics, 2020, 卷号: 21, 期号: 1
Authors:  Jing,Fang;  Zhang,Shao-Wu;  Zhang,Shihua
Favorite  |  View/Download:12/0  |  Submit date:2021/01/14
Enhancer–promoter interactions  Cell line  Convolutional neural network  Transfer learning  Gradient reversal layer  
Prediction of enhancer-promoter interactions using the cross-cell type information and domain adversarial neural network 期刊论文
BMC BIOINFORMATICS, 2020, 卷号: 21, 期号: 1, 页码: 16
Authors:  Jing, Fang;  Zhang, Shao-Wu;  Zhang, Shihua
Favorite  |  View/Download:13/0  |  Submit date:2021/01/14
Enhancer–  promoter interactions  Cell line  Convolutional neural network  Transfer learning  Gradient reversal layer  
Probe Efficient Feature Representation of Gapped K-mer Frequency Vectors from Sequences Using Deep Neural Networks 期刊论文
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2020, 卷号: 17, 期号: 2, 页码: 657-667
Authors:  Cao, Zhen;  Zhang, Shihua
Favorite  |  View/Download:39/0  |  Submit date:2020/05/24
DNA  Bioinformatics  Kernel  Feature extraction  Support vector machines  Genomics  Task analysis  Bioinformatics  machine learning  gapped k-mer  deep neural network  transcription factor binding site prediction  
Confidence intervals for Markov chain transition probabilities based on next generation sequencing reads data 期刊论文
QUANTITATIVE BIOLOGY, 2020, 卷号: 8, 期号: 2, 页码: 143-154
Authors:  Wan, Lin;  Kang, Xin;  Ren, Jie;  Sun, Fengzhu
Favorite  |  View/Download:63/0  |  Submit date:2021/01/14
DNA  FREQUENCIES  PREDICTION  Markov chains  next generation sequencing  transition probabilities  confidence intervals  
Simple tricks of convolutional neural network architectures improve DNA-protein binding prediction 期刊论文
BIOINFORMATICS, 2019, 卷号: 35, 期号: 11, 页码: 1837-1843
Authors:  Cao, Zhen;  Zhang, Shihua
Favorite  |  View/Download:51/0  |  Submit date:2020/01/10
The cis-trans binding strength defined by motif frequencies facilitates statistical inference of transcriptional regulation 期刊论文
BMC BIOINFORMATICS, 2019, 卷号: 20, 页码: 11
Authors:  Feng, Yance;  Zhang, Sheng;  Li, Liang;  Li, Lei M.
Favorite  |  View/Download:25/0  |  Submit date:2019/10/28
BASE  Statistical inference  Transcriptional regulation  PUFA  DHA  EPA  Binding strength  
Prevalence of cryptic species in morphologically uniform taxa - Fast speciation and evolutionary radiation in Asian frogs 期刊论文
MOLECULAR PHYLOGENETICS AND EVOLUTION, 2018, 卷号: 127, 页码: 723-731
Authors:  Liu, Zuyao;  Chen, Guoling;  Zhu, Tianqi;  Zeng, Zhaochi;  Lyu, Zhitong;  Wang, Jian;  Messenger, Kevin;  Greenberg, Anthony;  Guo, Zixiao;  Yang, Ziheng;  Shi, Suhua;  Wang, Yingyong
Favorite  |  View/Download:55/0  |  Submit date:2019/01/11
Cryptic species  Delimitation  Diversity  Megophrys  Phylogeography