BC-TFdb: a database of transcription factor drivers in breast cancer

Author:

Khan Abbas1ORCID,Khan Taimoor1,Nasir Syed Nouman2,Ali Syed Shujait2,Suleman Muhammad2,Rizwan Muhammad2,Waseem Muhammad3,Ali Shahid2,Zhao Xia4,Wei Dong-Qing156

Affiliation:

1. Department of Bioinformatics and Biological Statistics, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, P.R. China

2. Center for Biotechnology and Microbiology, University of Swat, Swat, KP 19200, Pakistan

3. Faculty of Rehabilitation and Allied Health Science, Riphah International University, Islamabad 44000, Pakistan

4. Department of Microbiology, Army Medical University, Chongqing 400044, P.R. China

5. State Key Laboratory of Microbial Metabolism, Shanghai-Islamabad-Belgrade Joint Innovation Center on Antibacterial Resistances, Joint International Research Laboratory of Metabolic and Developmental Sciences and School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, P.R. China

6. Peng Cheng Laboratory, Vanke Cloud City Phase I Building 8, Xili Street, Nanshan District, Shenzhen, Guangdong 518055, P.R. China

Abstract

Abstract Transcription factors (TFs) are DNA-binding proteins, which regulate many essential biological functions. In several cancer types, TF function is altered by various direct mechanisms, including gene amplification or deletion, point mutations, chromosomal translocations, expression alterations, as well as indirectly by non-coding DNA mutations influencing the binding of the TF. TFs are also actively involved in breast cancer (BC) initiation and progression. Herein, we have developed an open-access database, BC-TFdb (Breast Cancer Transcription Factors database), of curated, non-redundant TF involved in BC. The database provides BC driver TFs related information including genomic sequences, proteomic sequences, structural data, pathway information, mutations information, DNA binding residues, survival and therapeutic resources. The database will be a useful platform for researchers to obtain BC-related TF–specific information. High-quality datasets are downloadable for users to evaluate and develop computational methods for drug designing against BC. Database URL: https://www.dqweilab-sjtu.com/index.php.

Funder

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Information Systems

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