Extended continuous similarity indices: theory and application for QSAR descriptor selection-Reference-Cited by-同舟云学术

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Extended continuous similarity indices: theory and application for QSAR descriptor selection

Published:2022-03 Issue:3 Volume:36 Page:157-173
ISSN:0920-654X
Container-title:Journal of Computer-Aided Molecular Design
language:en
Short-container-title:J Comput Aided Mol Des

Author:

Rácz Anita,Dunn Timothy B.,Bajusz Dávid,Kim Taewon D.,Miranda-Quintana Ramón Alain^ORCID,Héberger Károly

Funder

University of Florida

-National Research, Development and Innovation Office of Hungary

-Hungarian Academy of Sciences: János Bolyai Research Scholarship

-Ministry for Innovation and Technology of Hungary

Publisher

Springer Science and Business Media LLC

Subject

Physical and Theoretical Chemistry,Computer Science Applications,Drug Discovery

Link

https://link.springer.com/content/pdf/10.1007/s10822-022-00444-7.pdf

Reference45 articles.

1. Bajusz D, Rácz A, Héberger K (2017) Chemical data formats, fingerprints, and other molecular descriptions for database analysis and searching. In: Chackalamannil S, Rotella DP, Ward SE (eds) Comprehensive medicinal chemistry III. Elsevier, Oxford, pp 329–378

2. Bender A, Glen RC (2004) Molecular similarity: a key technique in molecular informatics. Org Biomol Chem 2:3204–3218

3. Bajusz D, Rácz A, Héberger K (2015) Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations? J Cheminform 7:20. https://doi.org/10.1186/s13321-015-0069-3

4. Saxena A, Prasad M, Gupta A et al (2017) A review of clustering techniques and developments. Neurocomputing 267:664–681. https://doi.org/10.1016/J.NEUCOM.2017.06.053

5. Geppert H, Vogt M, Bajorath J (2010) Current trends in ligand-based virtual screening: molecular representations, data mining methods, new application areas, and performance evaluation. J Chem Inf Model 50:205–216. https://doi.org/10.1021/ci900419k

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