药物发现中的大数据。

Q1 Pharmacology, Toxicology and Pharmaceutics
Progress in medicinal chemistry Pub Date : 2018-01-01 Epub Date: 2018-02-24 DOI:10.1016/bs.pmch.2017.12.003
Nathan Brown, Jean Cambruzzi, Peter J Cox, Mark Davies, James Dunbar, Dean Plumbley, Matthew A Sellwood, Aaron Sim, Bryn I Williams-Jones, Magdalena Zwierzyna, David W Sheppard
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引用次数: 33

摘要

在药物发现领域,大数据的解释应该通过改进早期决策来缩短项目时间,减少临床损耗。我们遇到的问题始于庞大的数据量,以及在构建存储数据的基础设施之前如何首先摄取数据,以便以高效和富有成效的方式使用数据。数据本身有许多问题,包括一般的可重复性,但通常情况下,实验成功的关键是周围的环境。需要人工智能(AI)形式的帮助来理解和翻译上下文。在自然语言处理管道的背后,人工智能也被用于通过将数据连接在一起来前瞻性地生成新的假设。我们从生物学、化学和临床试验的角度来解释大数据,展示了一些令人印象深刻的公共领域来源和倡议,现在可以用于审讯。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Big Data in Drug Discovery.

Interpretation of Big Data in the drug discovery community should enhance project timelines and reduce clinical attrition through improved early decision making. The issues we encounter start with the sheer volume of data and how we first ingest it before building an infrastructure to house it to make use of the data in an efficient and productive way. There are many problems associated with the data itself including general reproducibility, but often, it is the context surrounding an experiment that is critical to success. Help, in the form of artificial intelligence (AI), is required to understand and translate the context. On the back of natural language processing pipelines, AI is also used to prospectively generate new hypotheses by linking data together. We explain Big Data from the context of biology, chemistry and clinical trials, showcasing some of the impressive public domain sources and initiatives now available for interrogation.

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来源期刊
Progress in medicinal chemistry
Progress in medicinal chemistry Pharmacology, Toxicology and Pharmaceutics-Pharmacology
CiteScore
15.60
自引率
0.00%
发文量
6
期刊介绍: This series has a long established reputation for excellent coverage of almost every facet of Medicinal Chemistry and is one of the most respected and instructive sources of information on the subject. The latest volume certifies to the continuing success of a unique series reflecting current progress in a broadly developing field of science.
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