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Regulatory Network

A gene (or genetic) regulatory network (GRN) is a collection of molecular regulators that interact with each other and with other substances in the cell to govern the gene expression levels of mRNA and proteins. These play a central role in morphogenesis, the creation of body structures, which in turn is central to evolutionary developmental biology (evo-devo). [Source: Wikipedia]

ccNET

Submitted by ChenLiang on Mon, 01/09/2017 - 11:39

Plant genera with both diploid and polyploid species are a common evolutionary occurrence. Polyploids, especially allopolyploids such as cotton and wheat, are a great model system for heterosis research. Here, we have integrated genome sequences and transcriptome data of Gossypium species to construct co-expression networks and identified functional modules from different cotton species, including 1155 and 1884 modules in G. arboreum and G. hirsutum, respectively. We overlayed the gene expression results onto the co-expression network.

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genYsis Toolbox

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

In the last few decades, technological and experimental advancements have enabled a more precise understanding of the mode of action of drugs with respect to human cell signaling pathways and have positively influenced the design of new drug compounds. However, as the design of compounds has become increasingly target-specific, the overall effects of a drug on adjacent cellular signaling pathways remain difficult to predict because of the complexity of the interactions involved. Off-target effects of drugs are known to influence their efficacy and safety.

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ReNE

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

One of the biggest challenges in the study of biological regulatory mechanisms is the integration, americanmodeling, and analysis of the complex interactions which take place in biological networks. Despite post transcriptional regulatory elements (i.e., miRNAs) are widely investigated in current research, their usage and visualization in biological networks is very limited. Regulatory networks are commonly limited to gene entities.

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miRsig

Submitted by ChenLiang on Mon, 01/09/2017 - 11:48

Decoding the patterns of miRNA regulation in diseases are important to properly realize its potential in diagnostic, prog- nostic, and therapeutic applications. Only a handful of studies computationally predict possible miRNA-miRNA interactions; hence, such interactions require a thorough investigation to understand their role in disease progression.

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CKDdb

Submitted by ChenLiang on Thu, 04/06/2017 - 17:37

Complex human traits such as chronic kidney disease (CKD) are a major health and financial burden in modern societies. Currently, the description of the CKD onset and progression at the molecular level is still not fully understood. Meanwhile, the prolific use of high-throughput omic technologies in disease biomarker discovery studies yielded a vast amount of disjointed data that cannot be easily collated. Therefore, we aimed to develop a molecule-centric database featuring CKD-related experiments from available literature publications.

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CyTRANSFINDER

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

Biological research increasingly relies on network models to study complex phenomena. Signal Transduction Pathways are molecular circuits that model how cells receive, process, and respond to information from the environment providing snapshots of the overall cell dynamics. Most of the attempts to reconstruct signal transduction pathways are limited to single regulator networks including only genes/proteins.

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MMpred

Submitted by ChenLiang on Tue, 01/09/2018 - 18:53

MicroRNA (miRNA) directed gene repression is an important mechanism of posttranscriptional regulation. Comprehensive analyses of how microRNA influence biological processes requires paired miRNA-mRNA expression datasets. However, a review of both GEO and ArrayExpress repositories revealed few such datasets, which was in stark contrast to the large number of messenger RNA (mRNA) only datasets. It is of interest that numerous primary miRNAs (precursors of microRNA) are known to be co-expressed with coding genes (host genes).

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plateletomics

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

There is little data considering relationships among human RNA, demographic variables, and primary human cell physiology. The platelet RNA and expression-1 study measured platelet aggregation to arachidonic acid, ADP, protease-activated receptor (PAR) 1 activation peptide (PAR1-AP), and PAR4-AP, as well as mRNA and microRNA (miRNA) levels in platelets from 84 white and 70 black healthy subjects. A total of 5911 uniquely mapped mRNAs and 181 miRNAs were commonly expressed and validated in a separate cohort.

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T-REX

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

Non-coding microRNAs (miRNAs) act as regulators of global protein output. While their major effect is on protein levels of target genes, it has been proven that they also specifically impact on the messenger RNA level of targets. Prominent interest in miRNAs strongly motivates the need for increasing the options available to detect their cellular activity.

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CSCdb

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

Cancer stem cells (CSCs), which have the ability to self-renew and differentiate into various tumor cell types, are a special class of tumor cells. Characterizing the genes involved in CSCs regulation is fundamental to understand the mechanisms underlying the biological process and develop treatment methods for tumor therapy. Recently, much effort has been expended in the study of CSCs and a large amount of data has been generated. However, to the best of our knowledge, database dedicated to CSCs is not available until now.

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