0000000000261677

AUTHOR

Gladys Casas Cardoso

showing 3 related works from this author

Nucleotide's bilinear indices: Novel bio-macromolecular descriptors for bioinformatics studies of nucleic acids. I. Prediction of paromomycin's affin…

2009

A new set of nucleotide-based bio-macromolecular descriptors are presented. This novel approach to bio-macromolecular design from a linear algebra point of view is relevant to nucleic acids quantitative structure-activity relationship (QSAR) studies. These bio-macromolecular indices are based on the calculus of bilinear maps on Re(n)[b(mk)(x (m),y (m)):Re(n) x Re(n)--Re] in canonical basis. Nucleic acid's bilinear indices are calculated from kth power of non-stochastic and stochastic nucleotide's graph-theoretic electronic-contact matrices, M(m)(k) and (s)M(m)(k), respectively. That is to say, the kth non-stochastic and stochastic nucleic acid's bilinear indices are calculated using M(m)(k)…

Models MolecularStatistics and ProbabilityPure mathematicsQuantitative structure–activity relationshipParomomycinMolecular Sequence DataDNA FootprintingQuantitative Structure-Activity RelationshipBilinear interpolationGeneral Biochemistry Genetics and Molecular BiologyInterpretation (model theory)DNA PackagingLinear regressionOrder (group theory)MathematicsStochastic ProcessesBase SequenceGeneral Immunology and MicrobiologyApplied MathematicsComputational BiologyGeneral MedicineModeling and SimulationDNA ViralLinear algebraStandard basisHIV-1Nucleic acidRNA ViralGeneral Agricultural and Biological SciencesAlgorithmJournal of Theoretical Biology
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QSAR models for tyrosinase inhibitory activity description applying modern statistical classification techniques: A comparative study

2010

Abstract Cluster analysis (CA), Linear and Quadratic Discriminant Analysis (L(Q)DA), Binary Logistic Regression (BLR) and Classification Tree (CT) are applied on two datasets for description of tyrosinase inhibitory activity from molecular structures. The first set included 701 tyrosinase inhibitors (TI) that are used for performance of inhibitory and non-inhibitory activity and the second one is for potency estimation of active compounds. 2D TOMOCOMD-CARDD atom-based quadratic indices are computed as molecular descriptors. CA is used to “rational” design of training (TS) and prediction set (PS) but it shows of not being adequate as classification technique. On the first data, the overall a…

Quantitative structure–activity relationshipReceiver operating characteristicProcess Chemistry and TechnologyDecision tree learningPosterior probabilityQuadratic classifierComputer Science ApplicationsAnalytical ChemistrySet (abstract data type)Statistical classificationMolecular descriptorStatisticsSpectroscopySoftwareMathematicsChemometrics and Intelligent Laboratory Systems
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A Comparative Study of Nonlinear Machine Learning for the "In Silico" Depiction of Tyrosinase Inhibitory Activity from Molecular Structure.

2011

In the preset report, for the first time, support vector machine (SVM), artificial neural network (ANN), Baye- sian networks (BNs), k-nearest neighbor (k-NN) are applied and compared on two "in-house" datasets to describe the tyrosinase inhibitory activity from the molecular structure. The data set Data I is used for the identification of tyrosi- nase inhibitors (TIs) including 701 active and 728 inactive compounds. Data II consists of active chemicals for potency estimation of TIs. The 2D TOMOCOMD-CARDD atom-based quadratic indices are used as molecular descriptors. The de- rived models show rather encouraging results with the areas under the Receiver Operating Characteristic (AURC) curve …

Virtual screeningArtificial neural networkComputer sciencebusiness.industryOrganic ChemistryMachine learningcomputer.software_genreComputer Science ApplicationsSupport vector machineData setStructural BiologyMolecular descriptorTest setDrug DiscoveryMultiple comparisons problemMolecular MedicineArtificial intelligencebusinesscomputerChemical databaseMolecular informatics
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