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Cancer/Tumor

CREAM

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

Abstract is not available.[1]

 

 

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miREC

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

Endometrial cancer (EC) is the most frequently diagnosed gynecological malignancy and the fourth most common cancer diagnosis overall among women. As with many other forms of cancer, it has been shown that certain miRNAs are differentially expressed in EC and these miRNAs are believed to play important roles as regulators of processes involved in the development of the disease.

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MCMG

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

MicroRNAs (miRNAs) play a crucial role in tumorigenesis and development through their effects on target genes. The characterization of miRNA-gene interactions will lead to a better understanding of cancer mechanisms. Many computational methods have been developed to infer miRNA targets with/without expression data. Because expression datasets are in general limited in size, most existing methods concatenate datasets from multiple studies to form one aggregated dataset to increase sample size and power.

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ProNet

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

Cancer is a complex disease, triggered by mutations in multiple genes and pathways. There is a growing interest in the application of systems biology approaches to analyze various types of cancer-related data to understand the overwhelming complexity of changes induced by the disease.

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BCGSC miRNA Profiling Pipeline

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

The comprehensive multiplatform genomics data generated by The Cancer Genome Atlas (TCGA) Research Network is an enabling resource for cancer research. It includes an unprecedented amount of microRNA sequence data: ~11 000 libraries across 33 cancer types. Combined with initiatives like the National Cancer Institute Genomics Cloud Pilots, such data resources will make intensive analysis of large-scale cancer genomics data widely accessible.

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Pancreatic Cancer Database

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

Pancreatic cancer is the fourth leading cause of cancer-related death in the world. The etiology of pancreatic cancer is heterogeneous with a wide range of alterations that have already been reported at the level of the genome, transcriptome, and proteome. The past decade has witnessed a large number of experimental studies using high-throughput technology platforms to identify genes whose expression at the transcript or protein levels is altered in pancreatic cancer.

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OncomiRdbB

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

Given the estimate that 30% of our genes are controlled by microRNAs, it is essential that we understand the precise relationship between microRNAs and their targets. OncomiRs are microRNAs (miRNAs) that have been frequently shown to be deregulated in cancer. However, although several oncomiRs have been identified and characterized, there is as yet no comprehensive compilation of this data which has rendered it underutilized by cancer biologists.

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Structuring osteosarcoma knowledge

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

Osteosarcoma (OS) is the most common primary bone cancer exhibiting high genomic instability. This genomic instability affects multiple genes and microRNAs to a varying extent depending on patient and tumor subtype. Massive research is ongoing to identify genes including their gene products and microRNAs that correlate with disease progression and might be used as biomarkers for OS. However, the genomic complexity hampers the identification of reliable biomarkers.

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iSubgraph

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

The high tumor heterogeneity makes it very challenging to identify key tumorigenic pathways as therapeutic targets. The integration of multiple omics data is a promising approach to identify driving regulatory networks in patient subgroups. Here, we propose a novel conceptual framework to discover patterns of miRNA-gene networks, observed frequently up- or down-regulated in a group of patients and to use such networks for patient stratification in hepatocellular carcinoma (HCC).

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decodeRNA

Submitted by ChenLiang on Tue, 01/09/2018 - 17:45

Although the long non-coding RNA (lncRNA) landscape is expanding rapidly, only a small number of lncRNAs have been functionally annotated. Here, we present decodeRNA (http://www.decoderna.org), a database providing functional contexts for both human lncRNAs and microRNAs in 29 cancer and 12 normal tissue types.

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