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We developed a procedure for indentifying transcriptional master regulators (MRs) related to special biological phenomena, such as diseases, in conjunction with network screening and inference. Network screening is a system for detecting activated transcriptional regulatory networks under particular conditions, based on the estimation of the graph structure consistency with the measured data. Since...
Most loci discovered through genome-wide association analyses are predicted to affect gene expression, the integrative approach of genome-wide analysis with gene expression data is becoming essential procedure for discovering genetic effect of disease development. Many studies have been performed to discover significant SNP-gene associations, but most of them are limited to consider only cis-associations...
Several flaviviruses are important human pathogens, including dengue virus, a disease against which neither a vaccine nor specific antiviral therapies currently exist. QSAR study was carried out with the purpose of searching new competitive dengue inhibitors with similar properties to the existence inhibitors (i.e. data set). The approach began with the development of rigorously validated QSAR model...
The traditional methods for identification potential SNP related to trait on highly polymorphic gene sequence needs complex SNP statistic and analytical procedure with the premise that positive data and negative data all fulfill, but sometime we only get a small quantity sequence data of positive trait individuals for time, difficulty or other causes and may be unable to get complete negative trait...
The identification of significant disease-related genes and networks is an important issue in understanding underlying mechanisms of cells. We integrate phenotype networks, protein networks and efficiently utilize gene expression data to identify human disease networks. We use prostate cancer data as our test domain. In comparison with statistical methods such as t-test and Wilcoxon test, our method...
Bioinformatics is an interesting combination of biology and computational sciences, which help scientists and researchers to do more biological experiments to improve the life of living being. Gene expression is fundamental biological basics of cell biology. It is also responsible for genetic as well as physical or biochemical characteristics of an organism. The study of gene expression analysis helps...
Inspired by recent discovery that human disease phenome shows a modular organization on the genetic landscape, we introduce a network-module based method towards phenotype-genotype association inference and disease-gene identification. This approach integrates protein-protein interaction network, phenotype similarity network and known phenotype-genotype associations, and then decomposes the resulted...
Abstract-We present a novel Bayesian network (BN) to classify strains of Mycobacterium tuberculosis complex (MTBC) into six major genetic lineages using mycobacterial interspersed repetitive units (MIRUs), a high-throughput biomarker. MTBC is the causative agent of tuberculosis (TB), which remains one of the leading causes of disease and morbidity world-wide. DNA fingerprinting methods such as MIRU...
We combine text mining with methods of systems biology for the first time, to predict functional networks for therapeutic mechanisms of Traditional Chinese Medicine in rheumatoid arthritis. The text mining results indicated rheumatoid arthritis highly associated with Tripterygium wilfordii, and eleven genes associated with both. Protein interaction information for these genes from databases and Literature...
It has become very important to study non-coding RNAs in the recent years. The Z curve is a very useful method for visualizing and analyzing DNA sequences among the approaches of researching ncRNAs. It is a three-dimensional space curve that constitutes a unique representation of a given DNA sequence, i.e., both the Z-curve and the given DNA sequence can be uniquely reconstructed from the other. Using...
In this study, we developed a systematic method to find risk alleles and relative gene for rheumatoid arthritis (RA). The method consists of three steps: 1) genome-wide case-control association studying based on haplotypes; 2) genome-wide association mapping based on directly mining haplotypes produced from case-control data via a density-based clustering algorithm; 3) candidate genes within 1 Mb...
Genome-wide high-throughput mass spectrometry has emerged as an important new source of data on biological systems. This technology yields global information about the proteins expressed by an organism; consequently, biological processes can be studied without prior assumptions about the proteins that are involved. A profile of up- and down-regulated proteins is obtained which can be used to discover...
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