The Monte Carlo method based on eclectic data as an efficient tool for predictions of endpoints for nanomaterials-two examples of application

Combinatorial Chemistry and High Throughput Screening

Volumn 18, Issue 4, 2015, Pages 376-386

  Toropov, Andrey A ^a   Toropova, Alla P ^a   Veselinović, Aleksandar M ^b   Veselinović, Jovana B ^b   Nesmerak, Karel ^c   Raska, Ivan ^d   Duchowicz, Pablo R ^e   Castro, Eduardo A ^e   Kudyshkin, Valentin O ^f   Leszczynska, Danuta ^g   Leszczynski, Jerzy ^h  

^a MARIO NEGRI INSTITUTE FOR PHARMACOLOGICAL RESEARCH   (Italy)

^b UNIVERSITY OF NI   (Serbia)

^c CHARLES UNIVERSITY   (Czech Republic)

^d CHARLES UNIVERSITY   (Czech Republic)

^e INSTITUTO DE INVESTIGACIONES FISICOQUÍMICAS TEÓRICAS Y APLICADAS INIFTA   (Argentina)

^f Institute of Polymer Chemistry and Physics Academy of Science of the Republic Uzbekistan   (Uzbekistan)

^g JACKSON STATE UNIVERSITY   (United States)

^h Jackson State University   (United States)

Author keywords

CORAL software; Optimal descriptor; Quasi QSPR QSAR

Indexed keywords

FULLERENE; NANOMATERIAL; TITANIUM DIOXIDE;

ARTICLE; ESCHERICHIA COLI; MONTE CARLO METHOD; NANOANALYSIS; NONHUMAN; PREDICTION; PRIORITY JOURNAL; QUANTITATIVE STRUCTURE ACTIVITY RELATION; QUANTITATIVE STRUCTURE PROPERTY RELATION; REVERTANT; SYNTHESIS; CHEMICAL STRUCTURE; CHEMISTRY;

MOLECULAR STRUCTURE; MONTE CARLO METHOD; NANOSTRUCTURES; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 84931263505     PISSN: 13862073     EISSN: 18755402     Source Type: Journal    
DOI: 10.2174/1386207318666150305125044     Document Type: Article

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