R
Robson Parmezan Bonidia
Researcher at University of São Paulo
Publications - 18
Citations - 139
Robson Parmezan Bonidia is an academic researcher from University of São Paulo. The author has contributed to research in topics: Feature extraction & Feature selection. The author has an hindex of 4, co-authored 16 publications receiving 58 citations. Previous affiliations of Robson Parmezan Bonidia include Universidade Estadual de Londrina & Federal University of Technology - Paraná.
Papers
More filters
Journal ArticleDOI
Data Mining in Sports: A Systematic Review
TL;DR: A systematic review of the literature about research involving sports data mining is presented, as systematic searches were made out in five databases, resulting in 21 articles that answered a question that grounded this article.
Journal ArticleDOI
MathFeature: feature extraction package for DNA, RNA and protein sequences based on mathematical descriptors.
Robson Parmezan Bonidia,Douglas Silva Domingues,Danilo Sipoli Sanches,André C. P. L. F. de Carvalho +3 more
TL;DR: MathFeature as mentioned in this paper is a new package, which implements mathematical descriptors able to extract relevant numerical information from biological sequences, i.e. DNA, RNA and proteins (prediction of structural features along the primary sequence of amino acids).
Journal ArticleDOI
Feature extraction approaches for biological sequences: a comparative study of mathematical features.
Robson Parmezan Bonidia,Robson Parmezan Bonidia,Lucas Dias Hiera Sampaio,Douglas Silva Domingues,Douglas Silva Domingues,Alexandre Rossi Paschoal,Fabrício Martins Lopes,André C. P. L. F. de Carvalho,Danilo Sipoli Sanches +8 more
TL;DR: Bonidia et al. as mentioned in this paper proposed a new study of feature extraction approaches based on mathematical features (numerical mapping with Fourier, entropy and complex networks), and analyzed long non-coding RNA sequences.
Proceedings ArticleDOI
A Math Educacional Computer Game Using Procedural Content Generation
Journal ArticleDOI
CRISPRloci: comprehensive and accurate annotation of CRISPR–Cas systems
Omer S. Alkhnbashi,Alexander Mitrofanov,Robson Parmezan Bonidia,Martin Raden,Van Dinh Tran,Florian Eggenhofer,Shiraz A. Shah,Ekrem Öztürk,Victor Alexandre Padilha,Danilo Sipoli Sanches,André C. P. L. F. de Carvalho,Rolf Backofen +11 more
TL;DR: The CRISPRloci server as mentioned in this paper provides the first resource for the prediction and assessment of all possible CRisPR loci, which integrates a series of advanced Machine Learning tools within a seamless web interface.