Genomic Statistics
Mostrando 1-12 de 21 artigos, teses e dissertações.
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1. PrevalÃncia dos subtipos do vÃrus da imunodeficiÃncia humana do tipo 1 (HIV-1) no estado do Piauà - Brasil e o perfil de resistÃncia das cepas identificadas. / Subtipes prevalence of human imunodeficient virus type 1 (HIV-1) in Piauà state/Brazil and the resistance profile of the studies virus.
HIV-1 genetic variability is a wellkown problem that makes diagnosis and treatment difficult to manage. Also, this variability is a problem for trasmission, disease progression and for the development of vaccines, being important to know the subtypes presented in each population worldwilde and in Brazil to provide more effective treatment. The present study
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 07/10/2011
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2. The use of Monte Carlo simulation via Markov chains in genetic breeding / O uso de simulação de Monte Carlo via cadeias de Markov no melhoramento genético
Este trabalho teve por objetivo fornecer um referencial teórico e aplicado sobre os principais métodos de simulação de Monte Carlo via cadeias de Markov (MCMC), buscando dar ênfase em aplicações no melhoramento genético. Assim, apresentaram-se os algoritmos de Metropolis-Hastings, simulated annealing e amostrador de Gibbs. Os aspectos teóricos dos m
Publicado em: 2009
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3. Mapeamento genético em famílias simuladas de irmãos completos / Genetic mapping in simulate full siblings family
O mapeamento genético facilita o trabalho de melhoramento, uma vez que uma ou mais marcas podem estar associadas a genes controladores de características qualitativas e quantitativas (QTL), podendo ser utilizada na seleção assistida. O estabelecimento de mapas genéticos em populações exogâmicas apresenta determinadas complicações não encontradas a
Publicado em: 2008
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4. BLOOM BLAST Object Oriented Management: uma solução integrada para gerenciamento dos resultados do BLAST por meio de um paradigma orientado a objetos
Considered a special subject since the beginning of the 80s, bioinformatics can be defined as a way that covers all aspects of acquisition, processing, storage, distribution, analysis and interpretation of biological information. All this happens in a narrow sinergy with the molecular biology fundamental paradigm, which postulates that the genetic informatio
Publicado em: 2003
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5. POCUS: mining genomic sequence annotation to predict disease genes
POCUS (prioritization of candidate genes using statistics) is a novel computational approach to prioritize candidate disease genes that is based on over-representation of functional annotation between loci for the same disease.
BioMed Central.
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6. Methods and algorithms for statistical analysis of protein sequences.
We describe several protein sequence statistics designed to evaluate distinctive attributes of residue content and arrangement in primary structure. Considered are global compositional biases, local clustering of different residue types (e.g., charged residues, hydrophobic residues, Ser/Thr), long runs of charged or uncharged residues, periodic patterns, cou
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7. Searching for RNA genes using base-composition statistics
The hypothesis that genomic regions rich in non-protein-coding RNAs (ncRNAs) can be identified using local variations in single-base and dinucleotide statistics has been investigated. (G+C)%, (G–C)% difference, (A–T)% difference and dinucleotide-frequency statistics were compared among seven classes of ncRNAs and three genomes. Significant variations wer
Oxford University Press.
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8. RECON: a program for prediction of nucleosome formation potential
The program RECON has been designed for constructing profiles of nucleosome potential, characterizing the probability of nucleosome formation along DNA sequences. The program used for recognition of nucleosome formation sites in genomic DNA sequences. It was developed using discriminant analysis based on a genetic algorithm method utilizing statistics for di
Oxford University Press.
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9. Statistical signals in bioinformatics
The Arthur M. Sackler Colloquium of the National Academy of Sciences, “Frontiers in Bioinformatics: Unsolved Problems and Challenges,” organized by David Eisenberg, Russ Altman, and myself, was held October 15-17, 2004, to provide a forum for discussing concepts and methods in bioinformatics serving the biological and medical sciences. The deluge of geno
National Academy of Sciences.
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10. An Efficient and Robust Statistical Modeling Approach to Discover Differentially Expressed Genes Using Genomic Expression Profiles
We have developed a statistical regression modeling approach to discover genes that are differentially expressed between two predefined sample groups in DNA microarray experiments. Our model is based on well-defined assumptions, uses rigorous and well-characterized statistical measures, and accounts for the heterogeneity and genomic complexity of the data. I
Cold Spring Harbor Laboratory Press.
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11. iProClass: an integrated, comprehensive and annotated protein classification database
The iProClass database is an integrated resource that provides comprehensive family relationships and structural and functional features of proteins, with rich links to various databases. It is extended from ProClass, a protein family database that integrates PIR superfamilies and PROSITE motifs. The iProClass currently consists of more than 200 000 no
Oxford University Press.
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12. SUPERFAMILY: HMMs representing all proteins of known structure. SCOP sequence searches, alignments and genome assignments
The SUPERFAMILY database contains a library of hidden Markov models representing all proteins of known structure. The database is based on the SCOP ‘superfamily’ level of protein domain classification which groups together the most distantly related proteins which have a common evolutionary ancestor. There is a public server at http://supfam.org which pr
Oxford University Press.