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icTAIR

Submitted by ChenLiang on Thu, 04/06/2017 - 17:57

Gene expression regulators, such as transcription factors (TFs) and microRNAs (miRNAs), have varying regulatory targets based on the tissue and physiological state (context) within which they are expressed. While the emergence of regulator-characterizing experiments has inferred the target genes of many regulators across many contexts, methods for transferring regulator target genes across contexts are lacking. Further, regulator target gene lists frequently are not curated or have permissive inclusion criteria, impairing their use.

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RAIN

Submitted by ChenLiang on Thu, 04/06/2017 - 18:52

Protein association networks can be inferred from a range of resources including experimental data, literature mining and computational predictions. These types of evidence are emerging for non-coding RNAs (ncRNAs) as well. However, integration of ncRNAs into protein association networks is challenging due to data heterogeneity. Here, we present a database of ncRNA-RNA and ncRNA-protein interactions and its integration with the STRING database of protein-protein interactions.

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RIDDLE

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

The growing availability of large-scale functional networks has promoted the development of many successful techniques for predicting functions of genes. Here we extend these network-based principles and techniques to functionally characterize whole sets of genes. We present RIDDLE (Reflective Diffusion and Local Extension), which uses well developed guilt-by-association principles upon a human gene network to identify associations of gene sets.

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TriplexRna

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

MicroRNAs (miRNAs) are an integral part of gene regulation at the post-transcriptional level. Recently, it has been shown that pairs of miRNAs can repress the translation of a target mRNA in a cooperative manner, which leads to an enhanced effectiveness and specificity in target repression. However, it remains unclear which miRNA pairs can synergize and which genes are target of cooperative miRNA regulation.

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GARNET

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

Gene set analysis is a powerful method of deducing biological meaning for an a priori defined set of genes. Numerous tools have been developed to test statistical enrichment or depletion in specific pathways or gene ontology (GO) terms. Major difficulties towards biological interpretation are integrating diverse types of annotation categories and exploring the relationships between annotation terms of similar information.

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IntmiR

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

IntmiR is a manually curated database of published intronic miRNAs of Human and Mouse genome. Each entry in the database, aims at providing a complete resource of intronic miRNA with their target gene and deregulation in various diseases with related tissues and pathways. The current release contains 426 intronic miRNA loci from human and 76 from mouse, expressing distinct target mRNA sequences. Database gives information on an intronic miRNA-disease relationship, including miRNA ID, pathaway connected and related tissues.

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RegNetwork

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

Transcriptional and post-transcriptional regulation of gene expression is of fundamental importance to numerous biological processes. Nowadays, an increasing amount of gene regulatory relationships have been documented in various databases and literature. However, to more efficiently exploit such knowledge for biomedical research and applications, it is necessary to construct a genome-wide regulatory network database to integrate the information on gene regulatory relationships that are widely scattered in many different places.

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CSmiRTar

Submitted by ChenLiang on Sun, 09/10/2017 - 16:52

MicroRNAs (miRNAs) are functional RNA molecules which play important roles in the post-transcriptional regulation. miRNAs regulate their target genes by repressing translation or inducing degradation of the target genes' mRNAs. Many databases have been constructed to provide computationally predicted miRNA targets. However, they cannot provide the miRNA targets expressed in a specific tissue and related to a specific disease at the same time. Moreover, they cannot provide the common targets of multiple miRNAs and the common miRNAs of multiple genes at the same time.

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ToppCluster

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

ToppCluster is a web server application that leverages a powerful enrichment analysis and underlying data environment for comparative analyses of multiple gene lists. It generates heatmaps or connectivity networks that reveal functional features shared or specific to multiple gene lists. ToppCluster uses hypergeometric tests to obtain list-specific feature enrichment P-values for currently 17 categories of annotations of human-ortholog genes, and provides user-selectable cutoffs and multiple testing correction methods to control false discovery.

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MIRNA-DISTILLER

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

MicroRNAs (miRNA) are small non-coding RNA molecules of ~22 nucleotides which regulate large numbers of genes by binding to seed sequences at the 3'-untranslated region of target gene transcripts. The target mRNA is then usually degraded or translation is inhibited, although thus resulting in posttranscriptional down regulation of gene expression at the mRNA and/or protein level.

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