BENCHMARKING SMALL-DATASET STRUCTURE-ACTIVITY-RELATIONSHIP MODELS FOR PREDICTION OF WNT SIGNALING INHIBITION

BENCHMARKING SMALL-DATASET STRUCTURE-ACTIVITY-RELATIONSHIP MODELS FOR PREDICTION OF WNT SIGNALING INHIBITION

Quantitative structure-activity relationship (QSAR) models based on machine learning algorithms are powerful tools to expedite drug discovery processes and therapeutics development. Given the cost in acquiring large-sized training datasets, it is useful to examine if QSAR analysis can reasonably pre...

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Bibliographic Details
Main Author: Kokabi, Mahtab
Format: Others
Published: ScholarWorks@UMass Amherst 2021
Subjects:
Bioactivity prediction
drug discovery
machine learning
molecular fingerprint
quantitative structure-activity relationship
Wnt signaling
Biomedical
Computational Engineering
Computer Engineering
Electrical and Computer Engineering
Online Access:https://scholarworks.umass.edu/masters_theses_2/1139
https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=2153&context=masters_theses_2

Internet

https://scholarworks.umass.edu/masters_theses_2/1139
https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=2153&context=masters_theses_2

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