The Monte Carlo Method Based on Eclectic Data as an Efficient Tool for Predictions of Endpoints for Nanomaterials - Two Examples of Application

Autores
Toropov, Andrei A.; Toropova, Alla P.; Veselinovic, Alexander M.; Veselinovic, Jovana B.; Nesmerak, Karel; Raska, Ivan, J.; Duchowicz, Pablo Román; Castro, Eduardo Alberto; Kudyshkin, Valentin O.; Lleszczynska, Danuta; Leszczynski, Jerzy
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The theoretical predictions of endpoints related to nanomaterials are attractive and moreefficient alternatives for their experimental determinations. Such type of calculations for the "usual"substances (i.e. non nanomaterials) can be carried out with molecular graphs. However, in the case ofnanomaterials, descriptors traditionally used for the quantitative structure - property/activityrelationships (QSPRs/QSARs) do not provide reliable results since the molecular structure ofnanomaterials, as a rule, cannot be expressed by the molecular graph. Innovative principles ofcomputational prediction of endpoints related to nanomaterials extracted from available eclectic data(technological attributes, conditions of the synthesis, etc.) are suggested, applied to two different sets of data, anddiscussed in this work.
Fil: Toropov, Andrei A.. IRCCS. Istituto di Ricerche Farmacologiche Mario Negri; Italia
Fil: Toropova, Alla P.. IRCCS. Istituto di Ricerche Farmacologiche Mario Negri; Italia
Fil: Veselinovic, Alexander M.. University of Nis; Serbia
Fil: Veselinovic, Jovana B.. University of Nis; Serbia
Fil: Nesmerak, Karel. Charles University in Prague. Faculty of Science; República Checa
Fil: Raska, Ivan, J.. Charles University in Prague. 3rd Department of Medicine; República Checa
Fil: Duchowicz, Pablo Román. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; Argentina. Universidad Nacional de la Plata; Argentina
Fil: Castro, Eduardo Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; Argentina. Universidad Nacional de la Plata; Argentina
Fil: Kudyshkin, Valentin O.. Uzbek Academy of Sciences; Uzbekistán
Fil: Lleszczynska, Danuta. Jackson State University; Estados Unidos
Fil: Leszczynski, Jerzy. Jackson State University; Estados Unidos
Materia
Teoria Qsar
Coral
Descriptores Moleculares
Nanomateriales
Optimal Descriptor
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/5079
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/5079
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling The Monte Carlo Method Based on Eclectic Data as an Efficient Tool for Predictions of Endpoints for Nanomaterials - Two Examples of ApplicationToropov, Andrei A.Toropova, Alla P.Veselinovic, Alexander M.Veselinovic, Jovana B.Nesmerak, KarelRaska, Ivan, J.Duchowicz, Pablo RománCastro, Eduardo AlbertoKudyshkin, Valentin O.Lleszczynska, DanutaLeszczynski, JerzyTeoria QsarCoralDescriptores MolecularesNanomaterialesOptimal Descriptorhttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1The theoretical predictions of endpoints related to nanomaterials are attractive and moreefficient alternatives for their experimental determinations. Such type of calculations for the "usual"substances (i.e. non nanomaterials) can be carried out with molecular graphs. However, in the case ofnanomaterials, descriptors traditionally used for the quantitative structure - property/activityrelationships (QSPRs/QSARs) do not provide reliable results since the molecular structure ofnanomaterials, as a rule, cannot be expressed by the molecular graph. Innovative principles ofcomputational prediction of endpoints related to nanomaterials extracted from available eclectic data(technological attributes, conditions of the synthesis, etc.) are suggested, applied to two different sets of data, anddiscussed in this work.Fil: Toropov, Andrei A.. IRCCS. Istituto di Ricerche Farmacologiche Mario Negri; ItaliaFil: Toropova, Alla P.. IRCCS. Istituto di Ricerche Farmacologiche Mario Negri; ItaliaFil: Veselinovic, Alexander M.. University of Nis; SerbiaFil: Veselinovic, Jovana B.. University of Nis; SerbiaFil: Nesmerak, Karel. Charles University in Prague. Faculty of Science; República ChecaFil: Raska, Ivan, J.. Charles University in Prague. 3rd Department of Medicine; República ChecaFil: Duchowicz, Pablo Román. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; Argentina. Universidad Nacional de la Plata; ArgentinaFil: Castro, Eduardo Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; Argentina. Universidad Nacional de la Plata; ArgentinaFil: Kudyshkin, Valentin O.. Uzbek Academy of Sciences; UzbekistánFil: Lleszczynska, Danuta. Jackson State University; Estados UnidosFil: Leszczynski, Jerzy. Jackson State University; Estados UnidosBentham Science Publishers2015-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/5079Toropov, Andrei A.; Toropova, Alla P.; Veselinovic, Alexander M.; Veselinovic, Jovana B.; Nesmerak, Karel; et al.; The Monte Carlo Method Based on Eclectic Data as an Efficient Tool for Predictions of Endpoints for Nanomaterials - Two Examples of Application; Bentham Science Publishers; Combinatorial Chemistry & High Throughput Screening; 4; 18; 3-2015; 376-3861386-2073enginfo:eu-repo/semantics/altIdentifier/pmid/25747446info:eu-repo/semantics/altIdentifier/doi/info:eu-repo/semantics/altIdentifier/url/http://www.ingentaconnect.com/content/ben/cchts/2015/00000018/00000004/art00006info:eu-repo/semantics/altIdentifier/url/http://www.eurekaselect.com/129189/articleinfo:eu-repo/semantics/altIdentifier/doi//10.2174/1386207318666150305125044info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:07:49Zoai:ri.conicet.gov.ar:11336/5079instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:07:49.932CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv The Monte Carlo Method Based on Eclectic Data as an Efficient Tool for Predictions of Endpoints for Nanomaterials - Two Examples of Application
title The Monte Carlo Method Based on Eclectic Data as an Efficient Tool for Predictions of Endpoints for Nanomaterials - Two Examples of Application
spellingShingle The Monte Carlo Method Based on Eclectic Data as an Efficient Tool for Predictions of Endpoints for Nanomaterials - Two Examples of Application
Toropov, Andrei A.
Teoria Qsar
Coral
Descriptores Moleculares
Nanomateriales
Optimal Descriptor
title_short The Monte Carlo Method Based on Eclectic Data as an Efficient Tool for Predictions of Endpoints for Nanomaterials - Two Examples of Application
title_full The Monte Carlo Method Based on Eclectic Data as an Efficient Tool for Predictions of Endpoints for Nanomaterials - Two Examples of Application
title_fullStr The Monte Carlo Method Based on Eclectic Data as an Efficient Tool for Predictions of Endpoints for Nanomaterials - Two Examples of Application
title_full_unstemmed The Monte Carlo Method Based on Eclectic Data as an Efficient Tool for Predictions of Endpoints for Nanomaterials - Two Examples of Application
title_sort The Monte Carlo Method Based on Eclectic Data as an Efficient Tool for Predictions of Endpoints for Nanomaterials - Two Examples of Application
dc.creator.none.fl_str_mv Toropov, Andrei A.
Toropova, Alla P.
Veselinovic, Alexander M.
Veselinovic, Jovana B.
Nesmerak, Karel
Raska, Ivan, J.
Duchowicz, Pablo Román
Castro, Eduardo Alberto
Kudyshkin, Valentin O.
Lleszczynska, Danuta
Leszczynski, Jerzy
author Toropov, Andrei A.
author_facet Toropov, Andrei A.
Toropova, Alla P.
Veselinovic, Alexander M.
Veselinovic, Jovana B.
Nesmerak, Karel
Raska, Ivan, J.
Duchowicz, Pablo Román
Castro, Eduardo Alberto
Kudyshkin, Valentin O.
Lleszczynska, Danuta
Leszczynski, Jerzy
author_role author
author2 Toropova, Alla P.
Veselinovic, Alexander M.
Veselinovic, Jovana B.
Nesmerak, Karel
Raska, Ivan, J.
Duchowicz, Pablo Román
Castro, Eduardo Alberto
Kudyshkin, Valentin O.
Lleszczynska, Danuta
Leszczynski, Jerzy
author2_role author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Teoria Qsar
Coral
Descriptores Moleculares
Nanomateriales
Optimal Descriptor
topic Teoria Qsar
Coral
Descriptores Moleculares
Nanomateriales
Optimal Descriptor
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The theoretical predictions of endpoints related to nanomaterials are attractive and moreefficient alternatives for their experimental determinations. Such type of calculations for the "usual"substances (i.e. non nanomaterials) can be carried out with molecular graphs. However, in the case ofnanomaterials, descriptors traditionally used for the quantitative structure - property/activityrelationships (QSPRs/QSARs) do not provide reliable results since the molecular structure ofnanomaterials, as a rule, cannot be expressed by the molecular graph. Innovative principles ofcomputational prediction of endpoints related to nanomaterials extracted from available eclectic data(technological attributes, conditions of the synthesis, etc.) are suggested, applied to two different sets of data, anddiscussed in this work.
Fil: Toropov, Andrei A.. IRCCS. Istituto di Ricerche Farmacologiche Mario Negri; Italia
Fil: Toropova, Alla P.. IRCCS. Istituto di Ricerche Farmacologiche Mario Negri; Italia
Fil: Veselinovic, Alexander M.. University of Nis; Serbia
Fil: Veselinovic, Jovana B.. University of Nis; Serbia
Fil: Nesmerak, Karel. Charles University in Prague. Faculty of Science; República Checa
Fil: Raska, Ivan, J.. Charles University in Prague. 3rd Department of Medicine; República Checa
Fil: Duchowicz, Pablo Román. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; Argentina. Universidad Nacional de la Plata; Argentina
Fil: Castro, Eduardo Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; Argentina. Universidad Nacional de la Plata; Argentina
Fil: Kudyshkin, Valentin O.. Uzbek Academy of Sciences; Uzbekistán
Fil: Lleszczynska, Danuta. Jackson State University; Estados Unidos
Fil: Leszczynski, Jerzy. Jackson State University; Estados Unidos
description The theoretical predictions of endpoints related to nanomaterials are attractive and moreefficient alternatives for their experimental determinations. Such type of calculations for the "usual"substances (i.e. non nanomaterials) can be carried out with molecular graphs. However, in the case ofnanomaterials, descriptors traditionally used for the quantitative structure - property/activityrelationships (QSPRs/QSARs) do not provide reliable results since the molecular structure ofnanomaterials, as a rule, cannot be expressed by the molecular graph. Innovative principles ofcomputational prediction of endpoints related to nanomaterials extracted from available eclectic data(technological attributes, conditions of the synthesis, etc.) are suggested, applied to two different sets of data, anddiscussed in this work.
publishDate 2015
dc.date.none.fl_str_mv 2015-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/5079
Toropov, Andrei A.; Toropova, Alla P.; Veselinovic, Alexander M.; Veselinovic, Jovana B.; Nesmerak, Karel; et al.; The Monte Carlo Method Based on Eclectic Data as an Efficient Tool for Predictions of Endpoints for Nanomaterials - Two Examples of Application; Bentham Science Publishers; Combinatorial Chemistry & High Throughput Screening; 4; 18; 3-2015; 376-386
1386-2073
url http://hdl.handle.net/11336/5079
identifier_str_mv Toropov, Andrei A.; Toropova, Alla P.; Veselinovic, Alexander M.; Veselinovic, Jovana B.; Nesmerak, Karel; et al.; The Monte Carlo Method Based on Eclectic Data as an Efficient Tool for Predictions of Endpoints for Nanomaterials - Two Examples of Application; Bentham Science Publishers; Combinatorial Chemistry & High Throughput Screening; 4; 18; 3-2015; 376-386
1386-2073
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/pmid/25747446
info:eu-repo/semantics/altIdentifier/doi/
info:eu-repo/semantics/altIdentifier/url/http://www.ingentaconnect.com/content/ben/cchts/2015/00000018/00000004/art00006
info:eu-repo/semantics/altIdentifier/url/http://www.eurekaselect.com/129189/article
info:eu-repo/semantics/altIdentifier/doi//10.2174/1386207318666150305125044
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Bentham Science Publishers
publisher.none.fl_str_mv Bentham Science Publishers
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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