Publikationen, an denen er mitarbeitet Riccardo Concu (16)

2019

  1. Computational MitoTarget Scanning Based on Topological Vacancies of Single-Walled Carbon Nanotubes with the Human Mitochondrial Voltage-Dependent Anion Channel (hVDAC1)

    Chemical Research in Toxicology, Vol. 32, Núm. 4, pp. 566-577

  2. MitoTarget Modeling Using ANN-Classification Models Based on Fractal SEM Nano-Descriptors: Carbon Nanotubes as Mitochondrial F0F1-ATPase Inhibitors

    Journal of Chemical Information and Modeling, Vol. 59, Núm. 1, pp. 86-97

  3. PTML Model of Enzyme Subclasses for Mining the Proteome of Biofuel Producing Microorganisms

    Journal of Proteome Research, Vol. 18, Núm. 7, pp. 2735-2746

2017

  1. Machine Learning Approach to Predict Enzyme Subclasses

    Multi-Scale Approaches in Drug Discovery: From Empirical Knowledge to In silico Experiments and Back (Elsevier Inc.), pp. 37-53

2013

  1. Patents of bio-active compounds based on computer-aided drug discovery techniques

    Frontiers in Bioscience - Elite, Vol. 5 E, Núm. 2, pp. 399-407

2012

  1. From QSAR models of drugs to complex networks: State-of-art review and introduction of new markov-spectral moments indices

    Current Topics in Medicinal Chemistry, Vol. 12, Núm. 8, pp. 927-960

  2. Generalized string pseudo-folding lattices in bioinformatics: State-of-art review, new model for enzyme sub-classes, and study of ESTs on trichinella spiralis

    Current Bioinformatics, Vol. 7, Núm. 1, pp. 7-34

2011

  1. NL mind-best: aweb server for ligands and proteins discovery; theoretic experimental study of proteins of giardia lamblia

    Proteómica: revista de la Sociedad Española de Proteómica, Núm. 7, pp. 170-170

  2. Review of computer-aided models for predicting collagen stability

    Current Computer-Aided Drug Design, Vol. 7, Núm. 4, pp. 287-303

2010

  1. A new computational chemistry and complex networks approach to structure-function and similarity relationships in protein enzymes

    Handbook of Computational Chemistry Research (Nova Science Publishers, Inc.), pp. 387-408

  2. Experimental-theoretic study of peptide fingerprints in Leishmania parasites

    Proteómica: revista de la Sociedad Española de Proteómica, Núm. 5, pp. 147-148

  3. Review of MARCH-INSIDE & complex networks prediction of drugs: ADMET, anti-parasite activity, metabolizing enzymes and cardiotoxicity proteome biomarkers

    Current Drug Metabolism, Vol. 11, Núm. 4, pp. 379-406

  4. Review of QSAR models for Enzyme classes of drug targets: Theoretical background and applications in parasites, hosts and other organisms

    Current Pharmaceutical Design, Vol. 16, Núm. 24, pp. 2710-2723

2009

  1. 3D entropy and moments prediction of enzyme classes and experimental-theoretic study of peptide fingerprints in Leishmania parasites

    Biochimica et Biophysica Acta - Proteins and Proteomics, Vol. 1794, Núm. 12, pp. 1784-1794

  2. Computational chemistry study of 3D-structure-function relationships for enzymes based on markov models for protein electrostatic, HINT, and van der waals potentials

    Journal of Computational Chemistry, Vol. 30, Núm. 9, pp. 1510-1520

  3. Prediction of enzyme classes from 3D structure: A general model and examples of experimental-theoretic scoring of peptide mass fingerprints of Leishmania proteins

    Journal of Proteome Research, Vol. 8, Núm. 9, pp. 4372-4382