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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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Average: 5 (1 vote)

iNMF

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

Recent advances in high-throughput omics technologies have enabled biomedical researchers to collect large-scale genomic data. As a consequence, there has been growing interest in developing methods to integrate such data to obtain deeper insights regarding the underlying biological system. A key challenge for integrative studies is the heterogeneity present in the different omics data sources, which makes it difficult to discern the coordinated signal of interest from source-specific noise or extraneous effects.

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Average: 4.5 (2 votes)

MirAncestar

Submitted by ChenLiang on Mon, 01/09/2017 - 11:03

MicroRNAs (miRNA) are short single-stranded RNA molecules derived from hairpin-forming precursors that play a crucial role as post-transcriptional regulators in eukaryotes and viruses. In the past years, many microRNA target genes (MTGs) have been identified experimentally. However, because of the high costs of experimental approaches, target genes databases remain incomplete. Although several target prediction programs have been developed in the recent years to identify MTGs in silico, their specificity and sensitivity remain low.

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Average: 5 (1 vote)

findr

Submitted by ChenLiang on Sun, 09/10/2017 - 16:57

Mapping gene expression as a quantitative trait using whole genome-sequencing and transcriptome analysis allows to discover the functional consequences of genetic variation. We developed a novel method and ultra-fast software Findr for higly accurate causal inference between gene expression traits using cis-regulatory DNA variations as causal anchors, which improves current methods by taking into consideration hidden confounders and weak regulations.

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Average: 5 (1 vote)

Vicinal

Submitted by ChenLiang on Sun, 09/10/2017 - 20:21

Non-coding (nc)RNAs are important structural and regulatory molecules. Accurate determination of the primary sequence and secondary structure of ncRNAs is important for understanding their functions. During cDNA synthesis, RNA 3' end stem-loops can self-prime reverse transcription, creating RNA-cDNA chimeras. We found that chimeric RNA-cDNA fragments can also be detected at 5' end stem-loops, although at much lower frequency.

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Average: 5 (1 vote)

miRNA_code

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

MicroRNA (miRNA), which is short non-coding RNA, plays a pivotal role in the regulation of many biological processes and affects the stability and/or translation of mRNA. Recently, machine learning algorithms were developed to predict potential miRNA targets. Most of these methods are robust but are not sensitive to redundant or irrelevant features. Despite their good performance, the relative importance of each feature is still unclear.

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Average: 5 (1 vote)

EvoRSR

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

Robustness, maintaining a constant phenotype despite perturbations, is a fundamental property of biological systems that is incorporated at various levels of biological complexity. Although robustness has been frequently observed in nature, its evolutionary origin remains unknown. Current hypotheses suggest that robustness originated as a direct consequence of natural selection, as an intrinsic property of adaptations, or as a congruent correlate of environment robustness.

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Average: 5 (1 vote)

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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Average: 5 (1 vote)

MiRSEA

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

Recent studies have shown that dysfunctional microRNAs (miRNAs) are involved in the progression of various cancers. Dysfunctional miRNAs may jointly regulate their target genes and further alter the activities of canonical biological pathways. Identification of the pathways regulated by a group of dysfunctional miRNAs could help uncover the pathogenic mechanisms of cancer and facilitate development of new drug targets. Current miRNA-pathway analyses mainly use differentially-expressed miRNAs to predict the shared pathways on which they act.

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5
Average: 5 (3 votes)

MKRMDA

Submitted by ChenLiang on Tue, 01/09/2018 - 18:50

Recently, as the research of microRNA (miRNA) continues, there are plenty of experimental evidences indicating that miRNA could be associated with various human complex diseases development and progression. Hence, it is necessary and urgent to pay more attentions to the relevant study of predicting diseases associated miRNAs, which may be helpful for effective prevention, diagnosis and treatment of human diseases.

Rating: 
Average: 5 (1 vote)

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