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Association

Genetic association is when one or more genotypes within a population co-occur with a phenotypic trait more often than would be expected by chance occurrence. Studies of genetic association aim to test whether single-locus alleles or genotype frequencies (or more generally, multilocus haplotype frequencies) differ between two groups of individuals (usually diseased subjects and healthy controls). [Source: Wikipedia]

DiseaseConnect

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

The DiseaseConnect (http://disease-connect.org) is a web server for analysis and visualization of a comprehensive knowledge on mechanism-based disease connectivity. The traditional disease classification system groups diseases with similar clinical symptoms and phenotypic traits. Thus, diseases with entirely different pathologies could be grouped together, leading to a similar treatment design. Such problems could be avoided if diseases were classified based on their molecular mechanisms.

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DMPred

Submitted by ChenLiang on Tue, 01/09/2018 - 16:55

Identification of disease-associated miRNAs (disease miRNAs) is critical for understanding disease etiology and pathogenesis. Since miRNAs exert their functions by regulating the expression of their target mRNAs, several methods based on the target genes were proposed to predict disease miRNA candidates. They achieved only limited success as they all suffered from the high false-positive rate of target prediction results.

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ncDR

Submitted by ChenLiang on Tue, 01/09/2018 - 16:58

As a promising field of individualized therapy, non-coding RNA pharmacogenomics promotes the understanding of different individual responses to certain drugs and acts as a reasonable reference for clinical treatment. However, relevant information is scattered across the published literature, which is inconvenient for researchers to explore non-coding RNAs that are involved in drug resistance. To address this, we systemically identified validated and predicted drug resistance-associated microRNAs and long non-coding RNAs through manual curation and computational analysis.

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GRNMF

Submitted by ChenLiang on Tue, 01/09/2018 - 17:03

MicroRNAs (miRNAs) play crucial roles in post-transcriptional regulations and various cellular processes. The identification of disease-related miRNAs provides great insights into the underlying pathogenesis of diseases at a system level. However, most existing computational approaches are biased towards known miRNA-disease associations, which is inappropriate for those new diseases or miRNAs without any known association information.

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PACdb

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

We have developed Pharmacogenomics And Cell database (PACdb), a results database that makes available relationships between single nucleotide polymorphisms, gene expression, and cellular sensitivity to various drugs in cell-based models to help determine genetic variants associated with drug response. The current version also supports summary analysis on differentially expressed genes between the HapMap samples of European and African ancestry, as well as queries for summary information of correlations between gene expression and pharmacological phenotypes.

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