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DisBind: A database of classified functional binding sites in disordered and structured regions of intrinsically disordered proteins

Overview of attention for article published in BMC Bioinformatics, April 2017
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Title
DisBind: A database of classified functional binding sites in disordered and structured regions of intrinsically disordered proteins
Published in
BMC Bioinformatics, April 2017
DOI 10.1186/s12859-017-1620-1
Pubmed ID
Authors

Jia-Feng Yu, Xiang-Hua Dou, Yu-Jie Sha, Chun-Ling Wang, Hong-Bo Wang, Yi-Ting Chen, Feng Zhang, Yaoqi Zhou, Ji-Hua Wang

Abstract

Intrinsically unstructured or disordered proteins function via interacting with other molecules. Annotation of these binding sites is the first step for mapping functional impact of genetic variants in coding regions of human and other genomes, considering that a significant portion of eukaryotic genomes code for intrinsically disordered regions in proteins. DisBind (available at http://biophy.dzu.edu.cn/DisBind ) is a collection of experimentally supported binding sites in intrinsically disordered proteins and proteins with both structured and disordered regions. There are a total of 226 IDPs with functional site annotations. These IDPs contain 465 structured regions (ORs) and 428 IDRs according to annotation by DisProt. The database contains a total of 4232 binding residues (from UniProt and PDB structures) in which 2836 residues are in ORs and 1396 in IDRs. These binding sites are classified according to their interacting partners including proteins, RNA, DNA, metal ions and others with 2984, 258, 383, 350, and 262 annotated binding sites, respectively. Each entry contains site-specific annotations (structured regions, intrinsically disordered regions, and functional binding regions) that are experimentally supported according to PDB structures or annotations from UniProt. The searchable DisBind provides a reliable data resource for functional classification of intrinsically disordered proteins at the residue level.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 3%
Unknown 38 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 28%
Student > Ph. D. Student 8 21%
Other 4 10%
Student > Bachelor 2 5%
Professor 2 5%
Other 6 15%
Unknown 6 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 21%
Agricultural and Biological Sciences 7 18%
Chemistry 6 15%
Physics and Astronomy 3 8%
Computer Science 2 5%
Other 5 13%
Unknown 8 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 August 2017.
All research outputs
#19,013,042
of 24,226,848 outputs
Outputs from BMC Bioinformatics
#6,139
of 7,512 outputs
Outputs of similar age
#226,828
of 313,433 outputs
Outputs of similar age from BMC Bioinformatics
#87
of 115 outputs
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