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Inferring tumor subtypes based on the gene expression data alone does not appear to be as powerful as expected for the lack of robustness and clinical meaning. The ultimate aim of clustering tumor samples should be to support clinical evaluation or treatment. Therefore, clustering procedure should closely integrate the clinical outcome and/or treatment information for final representation of the tumor...
Text mining refers to extract high-quality information including entities and relationships between them from text. Although several methods have been applied to extract protein interaction relationships and other information, few researches have focused on dealing with sentences for extracting precise relationships. This paper has provided several strategies in the processes of filtering the sentences...
Genome-wide association (GWA) studies based on haplo type have emerged as a new and powerful approach to identify the genetic variants involved in human complex diseases. A challenging problem after a GWA study based on haplotype is to select high-risk disease-related regions from the results that contain false association between genotype and phenotype. Haplotype similarity difference in a particular...
Genes with similar functions might lead to similar phenotypes and tend to locate in a cluster in protein- protein interaction (PPI) network. The responsible genes should be identified for cardiovascular artery disease by their combined network topological features. Here we introduced a method called CTFMining to predict candidate disease genes which based on the combined network topological features...
Increasing variety of molecular networks emerge from high-throughput genome data. In eukaryote, transcription factor is a major regulator at transcription level. Examining relations between features of these networks and their biological significance attracts attention of many researchers. While abundant quantity of studies represented connections between protein networks and topological parameters,...
Alzheimer disease (AD) is characterized by loss of memory and difficulty in learning which can be induced by dysfunction of ion channel genes. In this study, we apply the CTWC algorithm together with SPC method to microarray data measuring ion channel gene expression changes in AD tissue and the control tissue. The basic hypothesis here is that genes with similar expression patters are more likely...
Complex diseases are generally thought to be under the influence of one more mutated risk genes and jointly genetic and environmental factors, which are thought to be of key importance. And with the accumulation of high-throughput datasets, it plays a more and more important role to interpret the pathogenesis of complex diseases systematically using bioinformatics methods in life science. Many association...
Opioid is provided with the characteristics of antalgic and addiction, its primary target is opioid receptor. As for novel drug design, it is of great significance to study the structures and functions of opioid receptors by using bioinformatics methods, and it will contribute to defending and abstaining from opioid drug addiction. Bioinformatics methods such as sequence alignment, evolution analysis...
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...
Ion channels are important in many important physiological processes such as sensory transduction, action-potential generation and muscle contraction. Cardiomyopathy is a complex and multi-gene disease which hasn't been systematically analyzed by the perspective of ion channel genes. The aim of this study was to develop a bioinformatics approach to seek the transcriptional features leading to the...
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