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fast-db

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

Most human genes produce several transcripts with different exon contents by using alternative promoters, alternative polyadenylation sites and alternative splice sites. Much effort has been devoted to describing known gene transcripts through the development of numerous databases. Nevertheless, owing to the diversity of the transcriptome, there is a need for interactive databases that provide information about the potential function of each splicing variant, as well as its expression pattern.

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Average: 5 (1 vote)

IntNetLncSim

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

Increasing evidence indicated that long non-coding RNAs (lncRNAs) were involved in various biological processes and complex diseases by communicating with mRNAs/miRNAs each other. Exploiting interactions between lncRNAs and mRNA/miRNAs to lncRNA functional similarity (LFS) is an effective method to explore function of lncRNAs and predict novel lncRNA-disease associations.

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5
Average: 4.5 (2 votes)

PceRBase

Submitted by ChenLiang on Mon, 01/09/2017 - 11:38

Competition for microRNA (miRNA) binding between RNA molecules has emerged as a novel mechanism for the regulation of eukaryotic gene expression. Competing endogenous RNA (ceRNA) can act as decoys for miRNA binding, thereby forming a ceRNA network by regulating the abundance of other RNA transcripts which share the same or similar microRNA response elements. Although this type of RNA cross talk was first described in Arabidopsis, and was subsequently shown to be active in animal models, there is no database collecting potential ceRNA data for plants.

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Average: 5 (1 vote)

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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metaMIR

Submitted by ChenLiang on Tue, 01/09/2018 - 16:53

MicroRNAs (miRNAs) are key regulators of cell-fate decisions in development and disease with a vast array of target interactions that can be investigated using computational approaches. For this study, we developed metaMIR, a combinatorial approach to identify miRNAs that co-regulate identified subsets of genes from a user-supplied list. We based metaMIR predictions on an improved dataset of human miRNA-target interactions, compiled using a machine-learning-based meta-analysis of established algorithms.

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Average: 5 (1 vote)

BiCliques Merging

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

MicroRNAs (miRNAs) are post-transcriptional regulators that repress the expression of their targets. They are known to work cooperatively with genes and play important roles in numerous cellular processes. Identification of miRNA regulatory modules (MRMs) would aid deciphering the combinatorial effects derived from the many-to-many regulatory relationships in complex cellular systems. Here, we develop an effective method called BiCliques Merging (BCM) to predict MRMs based on bicliques merging.

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4
Average: 4 (2 votes)

DPMIND

Submitted by ChenLiang on Tue, 01/09/2018 - 17:48

MicroRNAs (miRNAs) play essential roles in plant growth, development and stress responses through post-transcriptionally regulating the expression levels of their target mRNAs. Although some tools and databases were developed for predicting the relationships between miRNAs and their targets (miR-Tar), most of them were dependent on computational methods without experimental validations. With development of degradome sequencing techniques, researchers can identify potential interactions based on degradome sequencing data.

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Average: 5 (1 vote)

EPLMI

Submitted by ChenLiang on Tue, 01/09/2018 - 17:50

The interaction of miRNA and lncRNA is known to be important for gene regulations. However, not many computational approaches have been developed to analyse known interactions and predict the unknown ones. Given that there are now more evidences that suggest that lncRNA-miRNA interactions are closely related to their relative expression levels in the form of a titration mechanism, we analyzed the patterns in large-scale expression profiles of known lncRNA-miRNA interactions.

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EDMRP

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

Plants are continuously subjected to infection by pathogens, including bacteria and viruses. Bacteria can inject a variety of effector proteins into the host to reprogram host defense mechanism. It is known that microRNAs participate in plant disease resistance to bacterial pathogens and previous studies have suggested that some bacterial effectors have evolved to disturb the host's microRNA-regulated pathways; and so enabling infection.

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Average: 5 (1 vote)

m6AVar

Submitted by ChenLiang on Tue, 01/09/2018 - 18:45

Identifying disease-causing variants among a large number of single nucleotide variants (SNVs) is still a major challenge. Recently, N6-methyladenosine (m6A) has become a research hotspot because of its critical roles in many fundamental biological processes and a variety of diseases. Therefore, it is important to evaluate the effect of variants on m6A modification, in order to gain a better understanding of them.

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