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Cited by 159

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Stigmata: An Algorithm To Determine Structural Commonalities in Diverse Datasets

Shemetulskis, N. E., Weininger, D., Blankley, C. J., Yang, J. J., Humblet, C.·1996·Journal of Chemical Information and Computer Sciences
DOI 10.1021/ci950169+
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Abstract

An algorithm, Stigmata, is described, which extracts structural commonalities from chemical datasets. It is discussed using several illustrative examples and a pharmaceutically interesting set of dopamine D2 agonists. The commonalities are determined using two-dimensional topological chemical descriptions and are incorporated into the key feature of the algorithm, the modal fingerprint. Flexibility is built into the algorithm by means of a user-defined threshold value, which affects the information content of the modal fingerprint. The use of the modal fingerprint as a diversity assessment tool, as a database similarity query, and as a basis for color mapping the determined commonalities back onto the chemical structures is demonstrated.

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Metadata

Authors
Shemetulskis, N. E., Weininger, D., Blankley, C. J., Yang, J. J., & Humblet, C.
Venue
Journal of Chemical Information and Computer Sciences
Publisher
American Chemical Society (ACS)
Published
1996-01-01
Volume
36
Issue
4
Pages
862-871
ISSN
0095-2338 (ISSN-L)
DOI
10.1021/ci950169+
OpenAlex
W2085126686
Cited by
159
References
0
FWCI
8.76
Type
journal article
Language
en
Open access
closed

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