Use of machine learning approaches for novel drug discovery.
about
Computational methods in drug discovery.Using Big Data to Discover Diagnostics and Therapeutics for Gastrointestinal and Liver Diseases.Macromolecular target prediction by self-organizing feature maps.Predicting DPP-IV inhibitors with machine learning approaches.A Computational Method for Unveiling the Target Promiscuity of Pharmacologically Active Compounds.Classification of Paediatric Inflammatory Bowel Disease using Machine LearningAn automated framework for QSAR model building.De-orphaning the marine natural product (±)-marinopyrrole A by computational target prediction and biochemical validation.Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare.Transfer and Multi-task Learning in QSAR Modeling: Advances and Challenges.Virtual screening by a new Clustering-based Weighted Similarity Extreme Learning Machine approach.Discriminate the response of Acute Myeloid Leukemia patients to treatment by using proteomics data and Answer Set Programming.Identification of Estrogen Receptor α Antagonists from Natural Products via In Vitro and In Silico Approaches.Protein design: from computer models to artificial intelligence
P2860
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P2860
Use of machine learning approaches for novel drug discovery.
description
2016 nî lūn-bûn
@nan
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
2016年论文
@zh
2016年论文
@zh-cn
name
Use of machine learning approaches for novel drug discovery.
@en
type
label
Use of machine learning approaches for novel drug discovery.
@en
prefLabel
Use of machine learning approaches for novel drug discovery.
@en
P2093
P2860
P50
P1476
Use of machine learning approaches for novel drug discovery.
@en
P2093
Angélica Nakagawa Lima
Gustavo Henrique Goulart Trossini
Vinícius Gonçalves Maltarollo
P2860
P304
P356
10.1517/17460441.2016.1146250
P407
P577
2016-01-27T00:00:00Z