Tatiana T. Marquez-Lago

According to our database1, Tatiana T. Marquez-Lago authored at least 27 papers between 2010 and 2021.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 


On csauthors.net:


BastionHub: a universal platform for integrating and analyzing substrates secreted by Gram-negative bacteria.
Nucleic Acids Res., 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

PROSPECT: A web server for predicting protein histidine phosphorylation sites.
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

MULTiPly: a novel multi-layer predictor for discovering general and specific types of promoters.
Bioinform., 2019

Bastion3: a two-layer ensemble predictor of type III secreted effectors.
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

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

POSSUM: a bioinformatics toolkit for generating numerical sequence feature descriptors based on PSSM profiles.
Bioinform., 2017

The Long and Viscous Road: Uncovering Nuclear Diffusion Barriers in Closed Mitosis.
PLoS Comput. Biol., 2014

Stochastic adaptation and fold-change detection: from single-cell to population behavior.
BMC Syst. Biol., 2011

Probability distributed time delays: integrating spatial effects into temporal models.
BMC Syst. Biol., 2010