K. Guimaraes

发表

Reporting Exact and Approximate Regular Expression Matches

Eugene W. Myers, Paulo Oliva, Katia S. Guimarães, 1998, CPM.

Predicting domain-domain interactions using a parsimony approach

K. Guimaraes, Raja Jothi, E. Zotenko, 2006, Genome Biology.

Protein secondary structure prediction: efficient neural network and feature extraction approaches

George D. C. Cavalcanti, K. Guimaraes, J.C.B. Melo, 2004 .

Copy Number Variations Detection: Unravelling the Problem in Tangible Aspects

Katia S. Guimarães, Francisco do Nascimento, K. Guimaraes, 2017, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Identification in silico of putative damage responsive elements (DRE) in promoter regions of the yeast genome

K. Guimaraes, AndreR.O. Cavalcanti, M. A. Morais, 2005 .

Regene: Automatic Construction of a Multiple Component Dirichlet Mixture Priors Covariance Model to Identify Non-coding RNA

Maria Emilia Telles Walter, Marcelo M. Brigido, Felipe Lessa, 2011, ISBRA.

Interrogating domain-domain interactions with parsimony based approaches

Teresa M. Przytycka, Katia S. Guimarães, K. Guimaraes, 2008, BMC Bioinformatics.

Protein Interaction Network Based Prediction of Domain-Domain and Domain-Peptide Interactions

Teresa M. Przytycka, Katia S. Guimarães, K. Guimaraes, 2008, Protein-protein Interactions and Networks.

Combining few neural networks for effective secondary structure prediction

George D. C. Cavalcanti, Katia S. Guimarães, Jeane C. B. Melo, 2003, Third IEEE Symposium on Bioinformatics and Bioengineering, 2003. Proceedings..

A Novel Approach Based on Relevance Learning Vector Quantization Applied to the Inference of High-Order SNPs Interactions

Kátia Silva Guimaraes, Flavia Roberta Barbosa de Araujo, K. Guimaraes, 2017, 2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI).

Inference of High-Order Epistatic Interactions Using Generalized Relevance Learning Vector Quantization with Parametric Adjustment

Kátia Silva Guimaraes, Flavia Roberta Barbosa de Araujo, K. Guimaraes, 2016, 2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI).

Decomposition of overlapping protein complexes: A graph theoretical method for analyzing static and dynamic protein associations

Teresa M. Przytycka, Raja Jothi, Elena Zotenko, 2005, Algorithms for Molecular Biology.

IMSPeptider: A computational peptide collision cross‐section area calculator based on a novel molecular dynamics simulation protocol

Katia S. Guimarães, Roberto D. Lins, Ranieri V. de Carvalho, 2013, J. Comput. Chem..

Insights on prediction of patients' response to anti-HIV therapies through machine learning

Katia S. Guimarães, Rogério S. Rosa, Rafael H. S. Santos, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Associating Genotype Sequence Properties to Haplotype Inference Errors

Katia S. Guimarães, Rogério S. Rosa, Rafael H. S. Santos, 2012, BSB.

PCA feature extraction for protein structure prediction

George D. C. Cavalcanti, J.C.B. Melo, G.D.C. Cavalcanti, 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

Insights on Haplotype Inference on Large Genotype Datasets

Katia S. Guimarães, Rogério S. Rosa, K. Guimaraes, 2010, BSB.

Efficient representation and P-value computation for high-order Markov motifs

Marie-France Sagot, Katia S. Guimarães, Paulo G. S. da Fonseca, 2008, ECCB.