Comparison of human cell signaling pathway databases-evolution, drawbacks and challenges

被引:66
作者
Chowdhury, Saikat [1 ,2 ]
Sarkar, Ram Rup [1 ,2 ]
机构
[1] CSIR Natl Chem Lab, Chem Engn & Proc Dev Div, Pune 411008, Maharashtra, India
[2] AcSIR, New Delhi 110001, India
来源
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION | 2015年
关键词
SYSTEMS BIOLOGY; METABOLIC PATHWAYS; OXIDATIVE STRESS; MARKUP LANGUAGE; KINETIC-MODELS; GENE-FUNCTION; HEDGEHOG; RESOURCE; GENOMICS; KEGG;
D O I
10.1093/database/bau126
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Elucidating the complexities of cell signaling pathways is of immense importance to gain understanding about various biological phenomenon, such as dynamics of gene/protein expression regulation, cell fate determination, embryogenesis and disease progression. The successful completion of human genome project has also helped experimental and theoretical biologists to analyze various important pathways. To advance this study, during the past two decades, systematic collections of pathway data from experimental studies have been compiled and distributed freely by several databases, which also integrate various computational tools for further analysis. Despite significant advancements, there exist several drawbacks and challenges, such as pathway data heterogeneity, annotation, regular update and automated image reconstructions, which motivated us to perform a thorough review on popular and actively functioning 24 cell signaling databases. Based on two major characteristics, pathway information and technical details, freely accessible data from commercial and academic databases are examined to understand their evolution and enrichment. This review not only helps to identify some novel and useful features, which are not yet included in any of the databases but also highlights their current limitations and subsequently propose the reasonable solutions for future database development, which could be useful to the whole scientific community.
引用
收藏
页数:25
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