A probabilistic molecular fingerprint for big data settings

A probabilistic molecular fingerprint for big data settings

Abstract Background Among the various molecular fingerprints available to describe small organic molecules, extended connectivity fingerprint, up to four bonds (ECFP4) performs best in benchmarking drug analog recovery studies as it encodes substructures with a high level of detail. Unfortunately, E...

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Bibliographic Details
Main Authors: Daniel Probst, Jean-Louis Reymond
Format: Article
Language:English
Published: BMC 2018-12-01
Series:Journal of Cheminformatics
Subjects:
Virtual screening
Similarity search
Fingerprints
Locality sensitive hashing
Approximate k-nearest neighbor search
Online Access:http://link.springer.com/article/10.1186/s13321-018-0321-8

Internet

http://link.springer.com/article/10.1186/s13321-018-0321-8

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