Distance based algorithms for small biomolecule classification and structural similarity search | Zendy

Emre Karakoç | Zendy; Artem Cherkasov | Zendy; S. Cenk Ṣahinalp | Zendy

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Distance based algorithms for small biomolecule classification and structural similarity search

Author(s) -

Emre Karakoç,

Artem Cherkasov,

S. Cenk Ṣahinalp

Publication year - 2006

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btl259

Subject(s) - minkowski distance , classifier (uml) , nearest neighbor search , computer science , similarity (geometry) , artificial intelligence , pruning , pattern recognition (psychology) , data mining , focus (optics) , k nearest neighbors algorithm , machine learning , algorithm , mathematics , euclidean distance , image (mathematics) , biology , physics , optics , agronomy

Structural similarity search among small molecules is a standard tool used in molecular classification and in-silico drug discovery. The effectiveness of this general approach depends on how well the following problems are addressed. The notion of similarity should be chosen for providing the highest level of discrimination of compounds wrt the bioactivity of interest. The data structure for performing search should be very efficient as the molecular databases of interest include several millions of compounds.

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