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TcoFBase: a comprehensive database for decoding the regulatory transcription co-factors in human and mouse

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单位： [1]The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China, [2]School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China, [3]The Key Laboratory of Molecular Biology for High Cancer Incidence Coastal Chaoshan Area, Shantou University Medical College, Shantou 515041, China, [4]School of Computer, University of South China, Hengyang, Hunan 421001, China, [5]The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China, [6]Hunan Provincial Base for Scientific and Technological Innovation Cooperation, University of South China, Hengyang, Hunan 421001, China, [7]Experimental and Translational Research Center, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China [8]Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China

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Transcription co-factors (TcoFs) play crucial roles in gene expression regulation by communicating regulatory cues from enhancers to promoters. With the rapid accumulation of TcoF associated chromatin immunoprecipitation sequencing (ChIP-seq) data, the comprehensive collection and integrative analyses of these data are urgently required. Here, we developed the TcoFBase database (http://tcof.liclab.net/TcoFbase), which aimed to document a large number of available resources for mammalian TcoFs and provided annotations and enrichment analyses of TcoFs. TcoFBase curated 2322 TcoFs and 6759 TcoFs associated ChIP-seq data from over 500 tissues/cell types in human and mouse. Importantly, TcoFBase provided detailed and abundant (epi) genetic annotations of ChIP-seq based TcoF binding regions. Furthermore, TcoFBase supported regulatory annotation information and various functional annotations for TcoFs. Meanwhile, TcoFBase embedded five types of TcoF regulatory analyses for users, including TcoF gene set enrichment, TcoF binding genomic region annotation, TcoF regulatory network analysis, TcoF-TF co-occupancy analysis and TcoF regulatory axis analysis. TcoFBase was designed to be a useful resource that will help reveal the potential biological effects of TcoFs and elucidate TcoF-related regulatory mechanisms.

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出版当年[2021]版：

大类 | 2 区

生物学

小类 | 2 区生化与分子生物学

最新[2025]版：

大类 | 2 区

生物学

小类 | 2 区生化与分子生物学

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出版当年[2020]版：

Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY

最新[2023]版：

Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY

影响因子： 最新[2023版] 16.7 最新五年平均[2021-2025] 16.1 出版当年[2020版] 16.971 出版当年五年平均[2016-2020] 15.542 出版前一年[2019版] 11.502 出版后一年[2021版] 19.16

第一作者：

第一作者单位： [1]The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China, [2]School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China,

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通讯作者：

通讯机构： [1]The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China, [2]School of Medical Informatics, Daqing Campus, Harbin Medical University, Daqing 163319, China, [4]School of Computer, University of South China, Hengyang, Hunan 421001, China, [5]The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China, [6]Hunan Provincial Base for Scientific and Technological Innovation Cooperation, University of South China, Hengyang, Hunan 421001, China,

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