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MOST: Most-similar ligand based approach to target prediction
Tao Huang
, Hong Mi
, Cheng Yuan Lin
, Ling Zhao
, Lidan ZHONG
, Feng bin Liu
,
Ge ZHANG
,
Aiping LYU
,
Zhaoxiang BIAN
*
, Shuhai LIN
, Man Zhang
, Yan hong Li
, Dong dong Hu
, Chung Wah Cheng
, MZRW Group
*
Corresponding author for this work
Chinese Medicine - Clinical Division
School of Chinese Medicine
Centre for Chinese Herbal Medicine Drug Development Limited
Chinese Medicine - Teaching and Research Division
Chinese Medicine Clinical Study Centre
Research output
:
Contribution to journal
›
Journal article
›
peer-review
39
Citations (Scopus)
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Dive into the research topics of 'MOST: Most-similar ligand based approach to target prediction'. Together they form a unique fingerprint.
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Keyphrases
Bioactivity
100%
Ligand-based Approaches
100%
Target Prediction
100%
Morgan Fingerprint
42%
Logistic Regression
42%
Action Targets
28%
False Discovery Rate Control
28%
Control Method
28%
Similarity Search
28%
Chemical Similarity
28%
Multi-target
28%
Mechanism of Action
28%
Nave Bayes
14%
Acetylcholinesterase
14%
Training Model
14%
Regression Forest
14%
Drug Repurposing
14%
Temporal Validation
14%
Machine Learning Techniques
14%
Computational Approach
14%
Prediction Power
14%
Reverse Docking
14%
Laxative Effect
14%
Prediction Accuracy
14%
Bioactivity Data
14%
Robust Index
14%
Fingerprint Matching
14%
Ligand-based
14%
Inference Approach
14%
Drug Mechanism
14%
Prediction Scenarios
14%
Random Forest Method
14%
ChEMBL
14%
Human Target
14%
Machine Learning
14%
Spectral Analysis
14%
Highly Accurate
14%
Aloe-emodin
14%
Agricultural and Biological Sciences
Fingerprint
100%
Learning System
40%
Machine Learning
40%
in Vivo Studies
20%
Aloe
20%
Acetylcholinesterase
20%
Drug Repositioning
20%