M
Maria Cristina Andreazza Costa
Researcher at State University of Campinas
Publications - 18
Citations - 154
Maria Cristina Andreazza Costa is an academic researcher from State University of Campinas. The author has contributed to research in topics: Quantitative structure–activity relationship & Partial least squares regression. The author has an hindex of 6, co-authored 18 publications receiving 128 citations. Previous affiliations of Maria Cristina Andreazza Costa include Federal University of São Carlos.
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Journal ArticleDOI
Quantification of mineral composition of Brazilian bee pollen by near infrared spectroscopy and PLS regression.
Maria Cristina Andreazza Costa,Marcelo Antonio Morgano,Márcia M. C. Ferreira,Raquel Fernanda Milani +3 more
TL;DR: The results indicated that NIR spectroscopy can be useful for an approximate quantification of these minerals in bee pollen samples and can be used as a faster alternative to the standard methodologies.
Journal ArticleDOI
Analysis of bee pollen constituents from different Brazilian regions: Quantification by NIR spectroscopy and PLS regression
Maria Cristina Andreazza Costa,Marcelo Antonio Morgano,Márcia M. C. Ferreira,Raquel Fernanda Milani +3 more
TL;DR: In this article, partial least square regression (PLS) models were built for quantification of the major components of 154 Brazilian bee pollen samples, and the calibration models exhibited the determination coefficients, R 2 ǫ> 0.94.
Journal ArticleDOI
In vitro cytotoxicity and structure-activity relationship approaches of ent-kaurenoic acid derivatives against human breast carcinoma cell line.
Ricardo M. da Costa,Jairo Kenupp Bastos,Maria Cristina Andreazza Costa,Márcia M. C. Ferreira,Cassia S. Mizuno,Giovanni F. Caramori,Glaucio R. Nagurniak,Marília R. Simão,Raquel Alves dos Santos,Rodrigo Cassio Sola Veneziani,Sérgio Ricardo Ambrósio,Renato L. T. Parreira +11 more
TL;DR: The positive relationship between these orbitals and the activity suggests that the ent-kaurenoic acid analogues interaction with the target involves charge displacement, which is entirely consistent with the literature.
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Sar analysis of synthetic neolignans and related compounds which are anti-leishmaniasis active compounds using pattern recognition methods
TL;DR: In this paper, a group of synthetic substances for which the biological activities against leishmaniasis are known were compared to those for which only about half a dozen out of more than twenty parameters were found to be efficient for the classification of the compounds into active and inactive groups.
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A comparative study of principal component and linear multiple regression analysis in SAR and QSAR applied to 1,4-dihydropyridine calcium channel antagonists (nifedipine analogues)
TL;DR: In this paper, principal component analysis (PCA) was used to classify 1,4-dihydropyridine derivatives into high active and low active groups for various different sets of compounds.