Bioinformatics
DBCollHIV: a database system for collaborative HIV analysis in Brazil
Authors: Luciano V. Ara�ºjo, Marcelo A. Soares, Suelene M. Oliveira, Pedro Chequer, Amilcar Tanuri, Ester C. Sabino and Jo�£o E. Ferreira
We developed a database system for collaborative HIV analysis (DBCollHIV) in Brazil. The main purpose of our DBCollHIV project was to develop an HIV-integrated database system with analytical bioinformatics tools that would support the needs of Brazilian research groups for data storage and sequence analysis. Whenever authoriz.. Read More»
- Genet. Mol. Res. 5(1):
Predicting enzyme class from protein structure using Bayesian classification
Authors: Luiz C. Borro, Stanley R.M. Oliveira, Michel E.B. Yamagishi, Adaulto L. Mancini, Jos�© G. Jardine, Ivan Mazoni, Edgard H. dos Santos, Roberto H. Higa, Paula R. Kuser and Goran Neshich
Predicting enzyme class from protein structure parameters is a challenging problem in protein analysis. We developed a method to predict enzyme class that combines the strengths of statistical and data-mining methods. This method has a strong mathematical foundation and is simple to implement, achieving an accuracy of 45%. A c.. Read More»
- Genet. Mol. Res. 5(1):
Exploring molecular networks using MONET ontology
Authors: Jo�£o Paulo M�¼ller da Silva, Ney Lemke, Jos�© Carlos Mombach, Jos�© Guilherme Camargo de Souza, Marialva Sinigaglia and Renata Vieira
The description of the complex molecular network responsible for cell behavior requires new tools to integrate large quantities of experimental data in the design of biological information systems. These tools could be used in the characterization of these networks and in the formulation of relevant biological hypotheses. The .. Read More»
- Genet. Mol. Res. 5(1):
Analysis of slipped sequences in EST projects
Authors: Christian Baudet and Zanoni Dias
Slippage is an important sequencing problem that can occur in EST projects. However, very few studies have addressed this. We propose three new methods to detect slippage artifacts: arithmetic mean method, geometric mean method, and echo coverage method. Each method is simple and has two different strategies for processing seq.. Read More»
- Genet. Mol. Res. 5(1):
An integrated model for cellular analysis
Authors: Eduardo Battistella, Jos�© G.C. de Souza, Cl�¡udia K. Barcellos, Ney Lemke and Jos�© C.M. Mombach
We present the MOlecular NETwork (MONET) ontology as a model to integrate data from different networks that govern cell function. To achieve this, different existing ontologies were analyzed and an integrated ontology was built in a way to make it possible to share and reuse knowledge, support interoperability between systems,.. Read More»
- Genet. Mol. Res. 4(3):
III Brazilian Workshop on Bioinformatics
Authors: Nat�¡lia F. Martins
-.. Read More»
- Genet. Mol. Res. 4(3):
Relative h-index to compare the scientific performance of researchers
Authors: L.A.S. Dias
I propose the Relative h-index of a scientist, which is based on his or her Hirsch’s h-index divided by the total number of published papers recorded in the database. The Relative index h allows for a comparison of the scientific output among researchers and can be very useful for research support institutions, universit.. Read More»
- Genet. Mol. Res. 11(2):
- http://dx.doi.org/2012.June.29.6
- DOI:
- http://dx.doi.org/10.4238/2012.June.29.6
Identification of conserved microRNAs and their target genes in Nile tilapia (Oreochromis niloticus) by bioinformatic analysis
Authors: X.H. Li, J.S. Wu, L.H. Tang and D. Hu
MicroRNAs (miRNAs) are a class of non-coding RNAs that play important roles in posttranscriptional regulation of target genes. miRNAs are involved in multiple biological processes by degrading targeted mRNAs or repressing mRNA translation in various organisms. Their conserved nature in various organisms makes them a good source of new miRNA discovery usin.. Read More»
- Genet. Mol. Res. 14(1):
- http://dx.doi.org/2015.March.31.8
- DOI:
- http://dx.doi.org/10.4238/2015.March.31.8
Improved method for predicting protein fold patterns with ensemble classifiers
Authors: W. Chen, X. Liu, Y. Huang, Y. Jiang, Q. Zou and C. Lin
Protein folding is recognized as a critical problem in the field of biophysics in the 21st century. Predicting protein-folding patterns is challenging due to the complex structure of proteins. In an attempt to solve this problem, we employed ensemble classifiers to improve prediction accuracy. In our experiments, 188-dimension.. Read More»
- Genet. Mol. Res. 11(1):
- http://dx.doi.org/2012.January.27.4
- DOI:
- http://dx.doi.org/10.4238/2012.January.27.4
Support vector machines for novel class detection in Bioinformatics
Authors: Eduardo J. Spinosa and Andr�© C.P.L.F. de Carvalho
Novelty detection techniques might be a promising way of dealing with high-dimensional classification problems in Bioinformatics. We present preliminary results of the use of a one-class support vector machine approach to detect novel classes in two Bioinformatics databases. The results are compatible with theory and inspire f.. Read More»
- Genet. Mol. Res. 4(3):