Classification Of Gene Networks
Mostrando 1-12 de 12 artigos, teses e dissertações.
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1. Exploration of gene functions for esophageal squamous cell carcinoma using network-based guilt by association principle
Gene networks have been broadly used to predict gene functions based on guilt by association (GBA) principle. Thus, in order to better understand the molecular mechanisms of esophageal squamous cell carcinoma (ESCC), our study was designed to use a network-based GBA method to identify the optimal gene functions for ESCC. To identify genomic bio-signatures fo
Braz J Med Biol Res. Publicado em: 19/04/2018
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2. Comparisons Between Different Methods in Measuring Enzyme Similarity for Metabolic Network Alignment
Metabolic network alignments enable comparison of the similarities and differences between pathways in two metabolic networks and help to uncover the conserved sub-blocks therein. Such analysis is important in the understanding of metabolic networks and species evolution. The fundamental parts of metabolic network alignment algorithms all involve comparisons
Braz. arch. biol. technol.. Publicado em: 22/03/2016
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3. Transduction motif analysis of gastric cancer based on a human signaling network
To investigate signal regulation models of gastric cancer, databases and literature were used to construct the signaling network in humans. Topological characteristics of the network were analyzed by CytoScape. After marking gastric cancer-related genes extracted from the CancerResource, GeneRIF, and COSMIC databases, the FANMOD software was used for the min
Braz J Med Biol Res. Publicado em: 04/04/2014
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4. Métodos estatísticos para a análise de dados de cDNA microarray em um ambiente computacional integrado / Statistical methods for cDNA microarray data analysis in an integrated computational environment
Análise de expressão gênica em larga escala é de fundamental importância para a biologia molecular atual pois possibilita a medida dos níveis de expressão de milhares de genes simultaneamente, o que torna viável a realização de trabalhos voltados para biologia de sistemas (systems biology). Dentre as principais técnicas experimentais disponíveis
Publicado em: 2007
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5. Comparative analysis of clustering methods for gene expression data
Large scale approaches, namely proteomics and transcriptomics, will play the most important role of the so-called post-genomics. These approaches allow experiments to measure the expression of thousands of genes from a cell in distinct time points. The analysis of this data can allow the the understanding of gene function and gene regulatory networks (Eisen
Publicado em: 2003
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6. Back-propagation and counter-propagation neural networks for phylogenetic classification of ribosomal RNA sequences.
A neural network system has been developed for rapid and accurate classification of ribosomal RNA sequences according to phylogenetic relationship. The molecular sequences are encoded into neural input vectors using an n-gram hashing method. A SVD (singular value decomposition) method is used to compress and reduce the size of long and sparse n-gram input ve
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7. HOX Pro: a specialized database for clusters and networks of homeobox genes
It is now clear that the homeobox motif is well conserved across metazoan phyla. It has been established experimentally that a subset of genes containing this motif plays key roles in the orchestration of gene expression during development. Auto- and cross-regulatory functional interactions join homeobox genes into genetic networks. We have developed a speci
Oxford University Press.
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8. Gene mining: a novel and powerful ensemble decision approach to hunting for disease genes using microarray expression profiling
Current applications of microarrays focus on precise classification or discovery of biological types, for example tumor versus normal phenotypes in cancer research. Several challenging scientific tasks in the post-genomic epoch, like hunting for the genes underlying complex diseases from genome-wide gene expression profiles and thereby building the correspon
Oxford University Press.
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9. Gene flow across linguistic boundaries in Native North American populations
Cultural and linguistic groups are often expected to represent genetic populations. In this article, we tested the hypothesis that the hierarchical classification of languages proposed by J. Greenberg [(1987) Language in the Americas (Stanford Univ. Press, Stanford, CA)] also represents the genetic structure of Native North American populations. The genetic
National Academy of Sciences.
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10. Identification of coding regions in genomic DNA sequences: an application of dynamic programming and neural networks.
Dynamic programming (DP) is applied to the problem of precisely identifying internal exons and introns in genomic DNA sequences. The program GeneParser first scores the sequence of interest for splice sites and for these intron- and exon-specific content measures: codon usage, local compositional complexity, 6-tuple frequency, length distribution and periodi
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11. Analyses of cDNAs from growth and slug stages of Dictyostelium discoideum
Dictyostelium is a favored model for studying problems in cell and developmental biology. To comprehend the genetic potential and networks that direct growth and multicellular development, we are performing a large-scale analysis of Dictyostelium cDNAs. Here, we newly determine 7720 nucleotide sequences of cDNAs from the multicellular, slug stage (S) and 10
Oxford University Press.
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12. Systematic Learning of Gene Functional Classes From DNA Array Expression Data by Using Multilayer Perceptrons
Recent advances in microarray technology have opened new ways for functional annotation of previously uncharacterised genes on a genomic scale. This has been demonstrated by unsupervised clustering of co-expressed genes and, more importantly, by supervised learning algorithms. Using prior knowledge, these algorithms can assign functional annotations based on
Cold Spring Harbor Laboratory Press.