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Development of a Large-Scale Chemogenomics Database to Improve Drug Candidate Selection

ChEBI2005-05-31 更新2026-07-21 收录

化学基因组学

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数据链接：

https://www.ebi.ac.uk/biostudies/ArrayExpress/studies/E-GEOD-2409 数据链接链接失效反馈

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资源简介：

Development of a Large-Scale Chemogenomics Database to Improve Drug Candidate Selection

应用场景：

创建时间：

2005-05-31

ATP检测

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The detection of small amounts (nanomoles) of inorganic phosphate has a great interest in biochemistry. In particular, phosphate detection is useful to evaluate the rate of hydrolysis of phosphatases,

NIAID Data Ecosystem60

Identification, docking energy score, source, and therapeutic applications of the top five chosen compounds and control (fruquintinib).

分子对接

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Identification, docking energy score, source, and therapeutic applications of the top five chosen compounds and control (fruquintinib).

NIAID Data Ecosystem20

Saccharomyces cerevisiae deletion and DAmP collections chemogenomic screen with Selenomethionine

化学基因组学

酵母表型分析

Growth assay in the presence of Selenomethionine that uses the barcoded collections of yeast gene modification (deletion or DamP) to identify strains that are hypersensitive to the presence of the ami

Alliance of Genome Resources10

Data_Sheet_2_Systematic Prediction of Antifungal Drug Synergy by Chemogenomic Screening in Saccharomyces cerevisiae.ZIP

抗真菌药物

化学基因组学

Since the earliest days of using natural remedies, combining therapies for disease treatment has been standard practice. Combination treatments exhibit synergistic effects, broadly defined as a greate

NIAID Data Ecosystem40

Comparative viability scoring for CPD2: Expert annotations versus computational approaches (Approach 1 and Approach 2 with MSE and Triplet Margin Loss).

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分析方法比较

Comparative viability scoring for CPD2: Expert annotations versus computational approaches (Approach 1 and Approach 2 with MSE and Triplet Margin Loss).

NIAID Data Ecosystem10

Development of a Large-Scale Chemogenomics Database to Improve Drug Candidate Selection

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