0000000000324163

AUTHOR

Emili Besalú

showing 7 related works from this author

Superposing significant interaction rules (SSIR) method: a simple procedure for rapid ranking of congeneric compounds

2020

The Superposing Significant Interaction Rules (SSIR) method is revised and implemented. The method is a simple combinatorial procedure, which deals with in situ generated rules among a dichotomized congeneric molecular family, selecting the most probabilistically relevant ones. The mere counting of the number of relevant rules attached to new compounds generates a molecular ranking useful for database filtering, refinement and prediction. The algorithm only needs for a symbolic molecular representation and this allows for mining the database in a confidential manner. Third parties will not know the real compounds that are on the way to be worked out. The procedure is tested for a complete s…

Simple (abstract algebra)Computer sciencebusiness.industryQuímica combinatòriaPattern recognitionCombinatorial chemistrySSIR method; Congener series; Ranking; SAR; Balanced Leave-two-out cross validation (BL2O)General ChemistryArtificial intelligenceQuímicabusinessRanking (information retrieval)
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Checking the Efficacy of Two Basic Descriptors With a Set of Properties of Alkanes

2019

Several experimental properties of alkanes are described by means of multilinear models at the cross-validation level. The models have been obtained considering two main sets of descriptors: mathematically-based and experimental ones. The best models are obtained normally involving one of the two sets. The main goal of this work is to show how the theoretical descriptors are able to perform a competitive role against the experimental ones. This constitutes an important topic in the quantitative structure-property relationships field because the use of mathematical and in silico descriptors is validated as a proper tool for model building. Activity distributions of the properties and indices…

Set (abstract data type)Theoretical computer scienceMathematicsInternational Journal of Quantitative Structure-Property Relationships
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Molecular Rearrangement of an Aza-Scorpiand Macrocycle Induced by pH: A Computational Study †

2016

Rearrangements and their control are a hot topic in supramolecular chemistry due to the possibilities that these phenomena open in the design of synthetic receptors and molecular machines. Macrocycle aza-scorpiands constitute an interesting system that can reorganize their spatial structure depending on pH variations or the presence of metal cations. In this study, the relative stabilities of these conformations were predicted computationally by semi-empirical and density functional theory approximations, and the reorganization from closed to open conformations was simulated by using the Monte Carlo multiple minimum method Financial support by the Spanish Ministerio de Economía y Competitiv…

Models MolecularMontecarlo Mètode deMonte Carlo method01 natural sciencessupramolecular chemistryMonte Carlo Multiple Minimumlcsh:ChemistryComputational chemistryaza-scorpiandsMolecular rearrangementpH controlled; supramolecular chemistry; synthetic receptors; aza-scorpiands; semi-empirical; Density Functional Theory; Monte Carlo Multiple Minimumlcsh:QH301-705.5semi-empiricalSpectroscopyDensity Functional TheoryDensity functionalsSpatial structureChemistryGeneral MedicineHydrogen-Ion ConcentrationMolecular machineComputer Science ApplicationsMonte Carlo methodpH controlledvisual_artsynthetic receptorsvisual_art.visual_art_mediumDensity functional theoryMonte Carlo MethodMacrocyclic CompoundsSupramolecular chemistry010402 general chemistryQuímica supramolecularCatalysisArticleInorganic ChemistryMetalQuantitative Biology::Subcellular ProcessesPhysical and Theoretical ChemistryMolecular BiologyAza CompoundsFuncional de densitat Teoria del010405 organic chemistryOrganic ChemistryComputational Biology0104 chemical scienceslcsh:Biology (General)lcsh:QD1-999Synthetic ReceptorsQuantum TheorySupramolecular chemistryInternational Journal of Molecular Sciences
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A Probabilistic Analysis About the Concepts of Difficulty and Usefulness of a Molecular Ranking Classification

2013

Discerning between the concepts of difficulty and usefulness of a molecular ranking classification is of significant importance in virtual design chemistry. Here, both concepts are viewed from the statistical and practical point of view according to the standard definitions of enrichment and statistical significance p-values. These parameters are useful not only to compare distinct rankings obtained for the same molecular database, but also in order to compare the ones established in distinct molecular sets from an objective point of view.

Models StatisticalPoint (typography)Computer sciencebusiness.industryGeneral MedicineMachine learningcomputer.software_genrePharmaceutical PreparationsRankingDrug DesignDrug DiscoveryComputer-Aided DesignMolecular MedicineProbabilistic analysis of algorithmsArtificial intelligencebusinesscomputerAlgorithmsCurrent Computer Aided-Drug Design
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Internal Test Sets Studies in a Group of Antimalarials

2006

Topological indices have been applied to build QSAR models for a set of 20 an- timalarial cyclic peroxy cetals. In order to evalua te the reliability of the proposed linear models leave-n-out and Internal Test Sets (ITS) approaches have b een considered. The pro- posed procedure resulted in a robust and consensued prediction equation and here it is shown why it is superior to the employed standard c ross-validation algorithms involving multilinear regression models.

Internal test sets method; topological indices; linear models; QSAR; statistical validation.Quantitative structure–activity relationshipMultilinear mapInternal test sets methodLinear models (Statistics)CatalysisInorganic ChemistrySet (abstract data type)lcsh:ChemistryQSAR (Bioquímica)Order (group theory)Applied mathematicsPhysical and Theoretical ChemistryMolecular Biologylcsh:QH301-705.5SpectroscopyReliability (statistics)Mathematicsstatistical validation.Group (mathematics)QSAROrganic ChemistryLinear modelRegression analysisGeneral MedicineComputer Science Applicationslcsh:Biology (General)lcsh:QD1-999Models lineals (Estadística)topological indiceslinear modelsInternational Journal of Molecular Sciences
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Ranking Series of Cancer-Related Gene Expression Data by Means of the Superposing Significant Interaction Rules Method

2020

The Superposing Significant Interaction Rules (SSIR) method is a combinatorial procedure that deals with symbolic descriptors of samples. It is able to rank the series of samples when those items are classified into two classes. The method selects preferential descriptors and, with them, generates rules that make up the rank by means of a simple voting procedure. Here, two application examples are provided. In both cases, binary or multilevel strings encoding gene expressions are considered as descriptors. It is shown how the SSIR procedure is useful for ranking the series of patient transcription data to diagnose two types of cancer (leukemia and prostate cancer) obtaining Area Under Recei…

Male0301 basic medicineKey genesComputer sciencelcsh:QR1-502Binary numberBiochemistrylcsh:MicrobiologyArticlePattern Recognition AutomatedStructure-Activity Relationship03 medical and health sciencesBig data0302 clinical medicinerankingData MiningHumanscancergene expressionsRelated geneCàncerMolecular BiologyOligonucleotide Array Sequence AnalysisCancerPròstata -- CàncerLeukemiaReceiver operating characteristicbusiness.industryGene Expression ProfilingleukemiaProstatic NeoplasmsLeucèmiaDades massivesPattern recognitionprostate cancerExpressió gènicaSSIR method030104 developmental biologyROC Curvemultilevel fingerprintsExpression dataData Interpretation Statistical030220 oncology & carcinogenesisProstate -- CancerArtificial intelligenceGene expressionbusinessAlgorithms
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Equivalence of the Pecka–Ponec Correlation Probability and the Statistical F Significance for MLR Models

2004

In an article of this journal Pecka and Ponec [J. Math. Chem. 27 (2000) 13] have proposed, by means of a probability calculation, a method to evaluate the statistical importance of correlations obtained from multilinear regression equations involving an arbitrary number of experimental points and parameters. Here, it is demonstrated how this probability exactly coincides with a more general concept: the confidence probability of an F distribution having the appropriate degrees of freedom.

Multilinear mapApplied MathematicsMathematical statisticsGeneral ChemistryF-distributionsymbols.namesakeJoint probability distributionStatisticssymbolsProbability mass functionProbability distributionApplied mathematicsRandom variableMathematicsProbability measureJournal of Mathematical Chemistry
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