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Cupid

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

We introduce a method for simultaneous prediction of microRNA-target interactions and their mediated competitive endogenous RNA (ceRNA) interactions. Using high-throughput validation assays in breast cancer cell lines, we show that our integrative approach significantly improves on microRNA-target prediction accuracy as assessed by both mRNA and protein level measurements. Our biochemical assays support nearly 500 microRNA-target interactions with evidence for regulation in breast cancer tumors.

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CrossHub

Submitted by ChenLiang on Thu, 04/06/2017 - 17:40

The contribution of different mechanisms to the regulation of gene expression varies for different tissues and tumors. Complementation of predicted mRNA-miRNA and gene-transcription factor (TF) relationships with the results of expression correlation analyses derived for specific tumor types outlines the interactions with functional impact in the current biomaterial.

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MMiRNA-Tar

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

The Cancer Genome Atlas (TCGA) (http://cancergenome.nih.gov) is a valuable data resource focused on an increasing number of well-characterized cancer genomes. In part, TCGA provides detailed information about cancer-dependent gene expression changes, including changes in the expression of transcription-regulating microRNAs.

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tsmti

Submitted by ChenLiang on Thu, 04/06/2017 - 19:16

Recent studies have revealed that a small non-coding RNA, microRNA (miRNA) down-regulates its mRNA targets. This effect is regarded as an important role in various biological processes. Many studies have been devoted to predicting miRNA-target interactions. These studies indicate that the interactions may only be functional in some specific tissues, which depend on the characteristics of an miRNA. No systematic methods have been established in the literature to investigate the correlation between miRNA-target interactions and tissue specificity through microarray data.

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HNOCDB

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

In spite of the wide prevalence of head, neck and oral cancer, HNOC, there is no integrated database on genes and miRNAs associated with all the carcinoma subtypes of HNOC. The objective is to compile a multilayered and comprehensive database of HNOC as a user-friendly resource for researchers devising novel therapeutic strategies.

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PROGmiR

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

Identification of prognostic biomarkers is hallmark of cancer genomics. Since miRNAs regulate expression of multiple genes, they act as potent biomarkers in several cancers. Identification of miRNAs that are prognostically important has been done sporadically, but no resource is available till date that allows users to study prognostics of miRNAs of interest, utilizing the wealth of available data, in major cancer types.

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SurvMicro

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

MicroRNAs (miRNAs) play a key role in post-transcriptional regulation of mRNA levels. Their function in cancer has been studied by high-throughput methods generating valuable sources of public information. Thus, miRNA signatures predicting cancer clinical outcomes are emerging. An important step to propose miRNA-based biomarkers before clinical validation is their evaluation in independent cohorts. Although it can be carried out using public data, such task is time-consuming and requires a specialized analysis.

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CancerNet

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

Protein-protein interactions (PPIs) and microRNA (miRNA)-target interactions are important for deciphering the mechanisms of tumorigenesis. However, current PPI databases do not support cancer-specific analysis. Also, no available databases can be used to retrieve cancer-associated miRNA-target interactions. As the pathogenesis of human cancers is affected by several miRNAs rather than a single miRNA, it is needed to uncover miRNA synergism in a systems level.

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gbCRC

Submitted by ChenLiang on Sun, 01/08/2017 - 16:53

Colorectal cancer (CRC) is a cancer of growing incidence that associates with a high mortality rate worldwide. There is a poor understanding of the heterogeneity of CRC with regard to causative genetic mutations and gene regulatory mechanisms. Previous studies have identified several susceptibility genes in small-scale experiments. However, the information has not been comprehensively and systematically compiled and interpreted. In this study, we constructed the gbCRC, the first literature-based gene resource for investigating CRC-related human genes.

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