DIMENSIONALITY OF BIG DATA SETS EXPLORED BY CLUJ DESCRIPTORS

Claudiu N. LUNGU; Sara  ERSALI; Beata  SZEFLER; Atena  PÎRVAN-MOLDOVAN; Subhash  BASAK; Mircea V.  DIUDEA

doi:10.24193/subbchem.2017.3.16

DIMENSIONALITY OF BIG DATA SETS EXPLORED BY CLUJ DESCRIPTORS

Authors

Claudiu N. LUNGU Department of Chemistry, Faculty of Chemistry and Chemical Engineering, Babeș-Bolyai University; Iuliu Hațieganu University of Medicine and Pharmacy Cluj-Napoca, Romania. Email: lunguclaudiu5555@gmail.com. https://orcid.org/0000-0002-5416-3142
Sara ERSALI Department of Chemistry, Faculty of Chemistry and Chemical Engineering, Babeș-Bolyai University, Cluj-Napoca, Romania. Corresponding author: diudea@chem.ubbcluj.ro. https://orcid.org/0000-0001-9456-6678
Beata SZEFLER Department of Physical Chemistry, Faculty of Pharmacy, Collegium Medicum, Nicolaus Copernicus University, Bydgoszcz, Poland. Email: beatas@cm.umk.pl. https://orcid.org/0000-0001-8433-3520
Atena PÎRVAN-MOLDOVAN Department of Chemistry, Faculty of Chemistry and Chemical Engineering, Babeș-Bolyai University, Cluj-Napoca, Romania. Corresponding author: diudea@chem.ubbcluj.ro. https://orcid.org/0000-0002-3092-3135
Subhash BASAK Duluth Natural Resources Research Institute, Department of Chemistry and Biochemistry, University of Minnesota, USA. Corresponding author: Email: diudea@chem.ubbcluj.ro. https://orcid.org/0000-0002-2086-5867
Mircea V. DIUDEA Department of Chemistry, Faculty of Chemistry and Chemical Engineering, Babeș-Bolyai University, Cluj-Napoca, Romania. Email: diudea@chem.ubbcluj.ro. https://orcid.org/0000-0003-2556-6329

DOI:

https://doi.org/10.24193/subbchem.2017.3.16

Keywords:

topological descriptor, QSAR, data dimensionality, mutagenity, principal component analysis (PCA), Ames test

Abstract

Dimensionality of a relatively big data set (95 compounds) observed for toxicity (mutagenicity) was explored in order to compute QSAR models. Distinct molecular descriptors were used. Dimensionality of data, using PCA, correlation plots and clustering, was evaluated. Analyzing data dimensionality allowed model optimization. Docking studies and PCA were used in order to expand data dimensionality. Pearson correlation coefficient (r²) values, obtained for both perceptive and predictive models, were satisfactory.

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STUDIA UBB CHEMIA, Volume 62 (LXII), No. 3, September 2017

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Published

2017-09-29

How to Cite

LUNGU, C. N., ERSALI, S. ., SZEFLER, B. ., PÎRVAN-MOLDOVAN, A. ., BASAK, S. ., & DIUDEA, M. V. . (2017). DIMENSIONALITY OF BIG DATA SETS EXPLORED BY CLUJ DESCRIPTORS. Studia Universitatis Babeș-Bolyai Chemia, 62(3), 197–204. https://doi.org/10.24193/subbchem.2017.3.16