A. Werhli

Silvia Silva da Costa Botelho, Adriano Velasque Werhli, Cristiano Rafael Steffens, 2019, 2019 IEEE 17th International Conference on Industrial Informatics (INDIN).

A comparison of classifiers for predicting the class color of fluorescent proteins

Karina dos Santos Machado, Adriano Velasque Werhli, Roger Sá da Silva, 2019, Comput. Biol. Chem..

Whole-genome sequencing as a tool for studying the microevolution of drug-resistant serial Mycobacterium tuberculosis isolates.

T. Clark, A. Pain, A. Werhli, 2021, Tuberculosis.

Inference of Genetic Regulatory Networks Using an Estimation of Distribution Algorithm

Leonardo R. Emmendorfer, Adriano Velasque Werhli, Thyago Salvá, 2013, BSB.

An adaptive machine learning approach to improve automatic iceberg detection from SAR images

Christine Wesche, Adriano V. Werhli, Mauro M. Barbat, 2019, ISPRS Journal of Photogrammetry and Remote Sensing.

A higher flexibility at the SARS-CoV-2 main protease active site compared to SARS-CoV and its potentialities for new inhibitor virtual screening targeting multi-conformers

R. S. Ferreira, A. Werhli, K. Machado, 2021, Journal of biomolecular structure & dynamics.

Decrypting Strong and Weak Single-Walled Carbon Nanotubes Interactions with Mitochondrial Voltage-Dependent Anion Channels Using Molecular Docking and Perturbation Theory

C. Munteanu, H. González-Díaz, A. Pazos, 2017, Scientific Reports.

E-Volve: understanding the impact of mutations in SARS-CoV-2 variants spike protein on antibodies and ACE2 affinity through patterns of chemical interactions at protein interfaces

A. Werhli, R. de Melo-Minardi, G. Rocha, 2022, PeerJ.

Characterization of glucose-tolerant β-glucosidases used in biofuel production under the bioinformatics perspective: a systematic review.

A. Werhli, K. Machado, R. de Melo-Minardi, 2014, Genetics and molecular research : GMR.

An Infrastructure to Mine Molecular Descriptors for Ligand Selection on Virtual Screening

Giovanni Xavier Perazzo, Ana T. Winck, Adriano V. Werhli, 2014, BioMed research international.

Estimation of Parameters of Mycobacterium tuberculosis Growth: A Multi-Agent-Based Simulation Approach

Diana F. Adamatti, Adriano Velasque Werhli, Karina S. Machado, 2014, IBERAMIA.

Multi-Agent-Based Simulation of Mycobacterium Tuberculosis Growth

Diana F. Adamatti, Adriano Velasque Werhli, Karina S. Machado, 2013, MABS.

Gene Regulatory Network Reconstruction by Bayesian Integration of Prior Knowledge and/or Different Experimental Conditions

Dirk Husmeier, Adriano Velasque Werhli, D. Husmeier, 2008, J. Bioinform. Comput. Biol..

Bayesian integration of biological prior knowledge into the reconstruction of gene regulatory networks with Bayesian networks.

Dirk Husmeier, D. Husmeier, A. Werhli, 2007, Computational systems bioinformatics. Computational Systems Bioinformatics Conference.

A framework for virtual screening

Jorge Gomes, Adriano Velasque Werhli, Karina S. Machado, 2016, SAC.

Comparative evaluation of reverse engineering gene regulatory networks with relevance networks , graphical gaussian models and bayesian networks

M. Grzegorczyk, D. Husmeier, A. Werhli, 2006 .

Inference of regulatory networks with MCMC sampler guided by mutual information

Adriano Velasque Werhli, Karina S. Machado, Nilzair M. Barreto, 2017, SAC.

Inference of regulatory networks with a convergence improved MCMC sampler

Adriano Velasque Werhli, Karina S. Machado, Nilzair Agostinho, 2015, BMC Bioinformatics.

Inferring Genetic Regulatory Networks with an Hierarchical Bayesian Model and a Parallel Sampling Algorithm

Adriano Velasque Werhli, M. R. Mendoza, A. Werhli, 2010, 2010 Eleventh Brazilian Symposium on Neural Networks.

Bayesian Network Structure Inference with an Hierarchical Bayesian Model

Adriano Velasque Werhli, A. Werhli, 2010, SBIA.

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

H. González-Díaz, R. Concu, A. Werhli, 2019, Chemical research in toxicology.

Using Probability Distributions in Parameters of Variables at Agent-Based Simulations: A Case Study for the TB Bacillus Growth Curve

Andrea von Groll, Diana Francisca Adamatti, Adriano V. Werhli, 2017 .

Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks

M. Grzegorczyk, D. Husmeier, A. Werhli, 2006, Bioinform..

Statistical Applications in Genetics and Molecular Biology

D. Husmeier, A. Werhli, 2007 .

Ensemble of Protein Stability upon Point Mutation Predictors

Adriano Velasque Werhli, Eduardo Kenji Hasegawa de Freitas, Alex Dias Camargo, 2021, BRACIS.

Statistical Applications in Genetics and Molecular Biology

M. J. Laan, M. Birkner, A. Hubbard, 2007 .

Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks

M. Grzegorczyk, D. Husmeier, A. Werhli, 2006, Bioinform..

Silencing the OCT4-PG1 pseudogene reduces OCT-4 protein levels and changes characteristics of the multidrug resistance phenotype in chronic myeloid leukemia

A. Werhli, Aline Portantiolo Lettnin, G. S. Trindade, 2019, Molecular Biology Reports.

Cytoprotection of lipoic acid against toxicity induced by saxitoxin in hippocampal cell line HT-22 through in silico modeling and in vitro assays.

A. Werhli, José María Monserrat, P. Ramos, 2018, Toxicology.