Tatiana T. Marquez-Lago
Orcid: 0000-0003-3279-5592
According to our database1,
Tatiana T. Marquez-Lago
authored at least 29 papers
between 2010 and 2023.
Collaborative distances:
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Bibliography
2023
Briefings Bioinform., January, 2023
2021
BastionHub: a universal platform for integrating and analyzing substrates secreted by Gram-negative bacteria.
Nucleic Acids Res., 2021
BigFiRSt: A Software Program Using Big Data Technique for Mining Simple Sequence Repeats From Large-Scale Sequencing Data.
Frontiers Big Data, 2021
Comprehensive assessment of machine learning-based methods for predicting antimicrobial peptides.
Briefings Bioinform., 2021
DeepVF: a deep learning-based hybrid framework for identifying virulence factors using the stacking strategy.
Briefings Bioinform., 2021
2020
J. Bioinform. Comput. Biol., 2020
Procleave: Predicting Protease-specific Substrate Cleavage Sites by Combining Sequence and Structural Information.
Genom. Proteom. Bioinform., 2020
PeNGaRoo, a combined gradient boosting and ensemble learning framework for predicting non-classical secreted proteins.
Bioinform., 2020
DeepCleave: a deep learning predictor for caspase and matrix metalloprotease substrates and cleavage sites.
Bioinform., 2020
A comprehensive review and performance evaluation of bioinformatics tools for HLA class I peptide-binding prediction.
Briefings Bioinform., 2020
PRISMOID: a comprehensive 3D structure database for post-translational modifications and mutations with functional impact.
Briefings Bioinform., 2020
iLearn : an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data.
Briefings Bioinform., 2020
PhosTransfer: A Deep Transfer Learning Framework for Kinase-Specific Phosphorylation Site Prediction in Hierarchy.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2020
Prediction of secondary structure population and intrinsic disorder of proteins using multitask deep learning.
Proceedings of the AMIA 2020, 2020
2019
MULTiPly: a novel multi-layer predictor for discovering general and specific types of promoters.
Bioinform., 2019
Bioinform., 2019
Computational analysis and prediction of lysine malonylation sites by exploiting informative features in an integrative machine-learning framework.
Briefings Bioinform., 2019
Systematic analysis and prediction of type IV secreted effector proteins by machine learning approaches.
Briefings Bioinform., 2019
Twenty years of bioinformatics research for protease-specific substrate and cleavage site prediction: a comprehensive revisit and benchmarking of existing methods.
Briefings Bioinform., 2019
Large-scale comparative assessment of computational predictors for lysine post-translational modification sites.
Briefings Bioinform., 2019
2018
Bastion6: a bioinformatics approach for accurate prediction of type VI secreted effectors.
Bioinform., 2018
PROSPERous: high-throughput prediction of substrate cleavage sites for 90 proteases with improved accuracy.
Bioinform., 2018
Quokka: a comprehensive tool for rapid and accurate prediction of kinase family-specific phosphorylation sites in the human proteome.
Bioinform., 2018
iFeature: a Python package and web server for features extraction and selection from protein and peptide sequences.
Bioinform., 2018
Comprehensive assessment and performance improvement of effector protein predictors for bacterial secretion systems III, IV and VI.
Briefings Bioinform., 2018
2017
POSSUM: a bioinformatics toolkit for generating numerical sequence feature descriptors based on PSSM profiles.
Bioinform., 2017
2014
PLoS Comput. Biol., 2014
2011
Stochastic adaptation and fold-change detection: from single-cell to population behavior.
BMC Syst. Biol., 2011
2010
Probability distributed time delays: integrating spatial effects into temporal models.
BMC Syst. Biol., 2010