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SubpathwayGMir

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

MicroRNAs (miRNAs) regulate disease-relevant metabolic pathways. However, most current pathway identification methods fail to consider miRNAs in addition to genes when analyzing pathways. We developed a powerful method called Subpathway-GMir to construct miRNA-regulated metabolic pathways and to identify miRNA-mediated subpathways by considering condition-specific genes, miRNAs, and pathway topologies. We used Subpathway-GMir to analyze two liver hepatocellular carcinomas (LIHC), one stomach adenocarcinoma (STAD), and one type 2 diabetes (T2D) data sets.

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SignaFish

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

Understanding living systems requires an in-depth knowledge of the signaling networks that drive cellular homeostasis, regulate intercellular communication, and contribute to cell fates during development. Several resources exist to provide high-throughput data sets or manually curated interaction information from human or invertebrate model organisms. We previously developed SignaLink, a uniformly curated, multi-layered signaling resource containing information for human and for the model organisms nematode Caenorhabditis elegans and fruit fly Drosophila melanogaster.

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GED

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

Reproductive infertility affects seventh of couples, which is most attributed to the obstacle of gametogenesis. Characterizing the epigenetic modification factors involved in gametogenesis is fundamental to understand the molecular mechanisms and to develop treatments for human infertility. Although the genetic factors have been implicated in gametogenesis, no dedicated bioinformatics resource for gametogenesis is available.

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GO-Elite

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

We introduce GO-Elite, a flexible and powerful pathway analysis tool for a wide array of species, identifiers (IDs), pathways, ontologies and gene sets. In addition to the Gene Ontology (GO), GO-Elite allows the user to perform over-representation analysis on any structured ontology annotations, pathway database or biological IDs (e.g. gene, protein or metabolite). GO-Elite exploits the structured nature of biological ontologies to report a minimal set of non-overlapping terms. The results can be visualized on WikiPathways or as networks.

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Wormnet

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

An integrated gene network for Caenorhabditis elegans using data from multiple genome-wide screens encompasses most protein-coding genes and can accurately predict their phenotypes.[1]

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AraPath

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

Studying plants using high-throughput genomics technologies is becoming routine, but interpretation of genome-wide expression data in terms of biological pathways remains a challenge, partly due to the lack of pathway databases. To create a knowledgebase for plant pathway analysis, we collected 1683 lists of differentially expressed genes from 397 gene-expression studies, which constitute a molecular signature database of various genetic and environmental perturbations of Arabidopsis.

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PD map

Submitted by ChenLiang on Thu, 04/06/2017 - 17:21

Parkinson's disease (PD) is a major neurodegenerative chronic disease, most likely caused by a complex interplay of genetic and environmental factors. Information on various aspects of PD pathogenesis is rapidly increasing and needs to be efficiently organized, so that the resulting data is available for exploration and analysis. Here we introduce a computationally tractable, comprehensive molecular interaction map of PD.

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miRUPnet

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

With the rapid accumulation of microRNA (miRNAs), a class of newly identified small noncoding RNAs, in silico inference of miRNA functions has become one of the central tasks in miRNA bioinformatics. Traditional methods have helped in the understanding of miRNAs, but they also have limitations.

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CHRONOS

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

In the era of network medicine and the rapid growth of paired time series mRNA/microRNA expression experiments, there is an urgent need for pathway enrichment analysis methods able to capture the time- and condition-specific 'active parts' of the biological circuitry as well as the microRNA impact. Current methods ignore the multiple dynamical 'themes'-in the form of enriched biologically relevant microRNA-mediated subpathways-that determine the functionality of signaling networks across time.

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Average: 4.5 (2 votes)

CePa

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

CePa is an R package aiming to find significant pathways through network topology information. The package has several advantages compared with current pathway enrichment tools. First, pathway node instead of single gene is taken as the basic unit when analysing networks to meet the fact that genes must be constructed into complexes to hold normal functions. Second, multiple network centralities are applied simultaneously to measure importance of nodes from different aspects to make a full view on the biological system.

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