计算机科学
软件
数据科学
注释
蛋白质组学
资源(消歧)
领域(数学)
软件工程
人工智能
生物
计算机网络
数学
生物化学
基因
程序设计语言
纯数学
作者
Vasileios Tsiamis,Hans-Ioan Ienasescu,Dovydas Gabrielaitis,Magnus Palmblad,Veit Schwämmle,Jon Ison
标识
DOI:10.1021/acs.jproteome.9b00219
摘要
Proteomics is a highly dynamic field driven by frequent introduction of new technological approaches, leading to high demand for new software tools and the concurrent development of many methods for data analysis, processing, and storage. The rapidly changing landscape of proteomics software makes finding a tool fit for a particular purpose a significant challenge. The comparison of software and the selection of tools capable to perform a certain operation on a given type of data rely on their detailed annotation using well-defined descriptors. However, finding accurate information including tool input/output capabilities can be challenging and often heavily depends on manual curation efforts. This is further hampered by a rather low half-life of most of the tools, thus demanding the maintenance of a resource with updated information about the tools. We present here our approach to curate a collection of 189 software tools with detailed information about their functional capabilities. We furthermore describe our efforts to reach out to the proteomics community for their engagement, which further increased the catalog to >750 tools being about 70% of the estimated number of 1097 tools existing for proteomics data analysis. Descriptions of all annotated tools are available at https://proteomics.bio.tools.
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