V
Valmir C. Barbosa
Researcher at Federal University of Rio de Janeiro
Publications - 194
Citations - 2790
Valmir C. Barbosa is an academic researcher from Federal University of Rio de Janeiro. The author has contributed to research in topics: Distributed algorithm & Heuristics. The author has an hindex of 26, co-authored 186 publications receiving 2562 citations. Previous affiliations of Valmir C. Barbosa include IBM.
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Book
An Introduction to Distributed Algorithms
TL;DR: A senior undergraduate or graduate level computer science textbook on algorithm design for distributed computer systems.
Journal ArticleDOI
Integrated analysis of shotgun proteomic data with PatternLab for proteomics 4.0
Paulo C. Carvalho,Diogo B. Lima,Felipe da Veiga Leprevost,Felipe da Veiga Leprevost,Marlon D.M. Santos,Juliana de Saldanha da Gama Fischer,Priscila F Aquino,James J. Moresco,John R. Yates,Valmir C. Barbosa +9 more
TL;DR: The PatternLab for proteomics 4.0 package brings together several previously published modules for the analysis of shotgun proteomics data in a self-contained software environment, which allows for complete proteomic data analysis and the display of results in a variety of graphical formats.
Journal ArticleDOI
PatternLab for proteomics: a tool for differential shotgun proteomics
Paulo C. Carvalho,Juliana de Saldanha da Gama Fischer,Emily I. Chen,John R. Yates,Valmir C. Barbosa +4 more
TL;DR: PatternLab offers an easy and unified access to a variety of feature selection and normalization strategies, each having its own niche, and suggests that nSVM's niche comprises projects that select a minimum set of proteins for classification purposes.
Journal ArticleDOI
Identifying differences in protein expression levels by spectral counting and feature selection
TL;DR: Combinations of normalization and statistical methods on spectral counting data showed that Z-normalization combined with SVM-F correctly identified which and how many protein markers were added to the yeast lysates for all different concentrations.
Journal ArticleDOI
Search engine processor: Filtering and organizing peptide spectrum matches.
Paulo C. Carvalho,Juliana de Saldanha da Gama Fischer,Tao Xu,Daniel Cociorva,Tiago Santana Balbuena,Richard H. Valente,Jonas Perales,John R. Yates,Valmir C. Barbosa +8 more
TL;DR: By using the semi‐labeled decoy approach for benchmarking, it is shown that SEPro significantly outperforms a commercially available competitor.