Drug discovery FAQs: workflows for answering multidomain drug discovery questions

Chichester Christine; Digles Daniela; Siebes Ronald; Loizou Antonis; Groth Paul; Harland Lee

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Drug discovery FAQs: workflows for answering multidomain drug discovery questions

机译：药物发现常见问题解答：回答多域药物发现问题的工作流程

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Modern data-driven drug discovery requires integrated resources to support decision-making and enable new discoveries. The Open PHACTS Discovery Platform (http://dev.openphacts.org) was built to address this requirement by focusing on drug discovery questions that are of high priority to the pharmaceutical industry. Although complex, most of these frequently asked questions (FAQs) revolve around the combination of data concerning compounds, targets, pathways and diseases. Computational drug discovery using workflow tools and the integrated resources of Open PHACTS can deliver answers to most of these questions. Here, we report on a selection of workflows used for solving these use cases and discuss some of the research challenges. The workflows are accessible online from myExperiment (http://www.myexperiment.org) and are available for reuse by the scientific community.

机译：现代数据驱动的药物发现需要综合资源来支持决策并实现新发现。开放的Phacts Discovery平台（http://dev.openphacts.org）是通过专注于制药行业优先考虑的药物发现问题来解决这一要求。虽然复杂，但大多数这些常见问题（常见问题解答）围绕了关于化合物，靶，途径和疾病的数据的组合。使用工作流程工具的计算药物发现和开放式手机的综合资源可以为大多数问题提供答案。在这里，我们报告了用于解决这些用例的工作流程，并讨论一些研究挑战。工作流程可从Myoxperiment（http://www.myexperiment.org）在线访问，并且可以通过科学界可用。

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《Drug discovery today》 |2015年第4期|共7页
作者
Chichester Christine; Digles Daniela; Siebes Ronald; Loizou Antonis; Groth Paul; Harland Lee;
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作者单位

Swiss Inst Bioinformat CALIPHO Grp CMU CH-1211 Geneva Switzerland;

Univ Vienna Dept Med Chem Pharmacoinformat Res Grp A-1090 Vienna Austria;

Vrije Univ Amsterdam NL-1081 HV Amsterdam Netherlands;

Vrije Univ Amsterdam NL-1081 HV Amsterdam Netherlands;

Vrije Univ Amsterdam NL-1081 HV Amsterdam Netherlands;

Connected Discovery Ltd London WC1N 3AX England;

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原文格式 PDF
正文语种 eng
中图分类药学;
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1. Drug discovery FAQs: workflows for answering multidomain drug discovery questions [J] . Chichester Christine, Digles Daniela, Siebes Ronald, Drug discovery today . 2015,第4期

机译：药物发现常见问题解答：回答多域药物发现问题的工作流程
2. Drug discovery FAQs: workflows for answering multidomain drug discovery questions [J] . Chichester Christine, Digles Daniela, Siebes Ronald, Drug discovery today . 2015,第4期

机译：药物发现常见问题解答：回答多域药物发现问题的工作流程
3. Drug discovery FAQs: workflows for answering multidomain drug discovery questions [J] . Christine Chichester, Daniela Digles, Ronald Siebes, Drug discovery today . 2015,第2期

机译：药物发现常见问题解答：回答多域药物发现问题的工作流程
4. Causality Discovery with Domain Knowledge for Drug-Drug Interactions Discovery [C] . Sitthichoke Subpaiboonkit, Xue Li, Xin Zhao, International Conference on Advanced Data Mining and Applications . 2019

机译：具有域知识的因果关系发现，用于药物相互作用
5. Discovery and analysis of patterns in molecular networks: Link prediction, network analysis, and applications to novel drug target discovery. [D] . Zhang, Minlu. 2012

机译：在分子网络中发现和分析模式：链接预测，网络分析以及在新型药物靶点发现中的应用。
6. Connecting proteins with drug-like compounds: Open source drug discovery workflows with BindingDB and KNIME [O] . George Nicola, Michael R. Berthold, Michael P. Hedrick, 2015

机译：将蛋白质与类药物化合物连接：带有BindingDB和KNIME的开源药物发现工作流程
7. Drug discovery FAQs: workflows for answering multidomain drug discovery questions [O] . Chichester Christine, Digles Daniela, Siebes Ronald, 2015

机译：药物发现常见问题解答：回答多域药物发现问题的工作流程

Drug discovery FAQs: workflows for answering multidomain drug discovery questions

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