Software and Analytical Tools:
A Web Tool for Endogenous and Exogenous MicroRNA Discovery Based on Deep Sequencing Data Analysis: miRDis
To facilitate the discovery of transported dietary microRNA, our group has developed a novel next-generation sequence (NGS) analytical pipeline that focuses on the cross-species exogenous microRNA detection (http://sbbi.unl.edu/miRDis/). This work has been recently published in Briefings in Bioinformatics. More
Zhang HY, Silva B, Cui J#. MiRDis: A Web Tool for Endogenous and Exogenous MicroRNA Discovery Based on Deep Sequencing Data Analysis. Briefings in Bioinformatics. Jan. 2017, page 1-10, doi: 10.1093/bib/bbw140 (The 2nd ranked journal in the Mathematical & Computational Biology. IF: 8.3).
We have developed a new method to quantitatively measure the functional relevance among microRNAs that is solely based on the Gene Ontology and integrated functional annotation data from public pathways and PFam gene databases. The complete results and the similarity assessment system can be freely accessed at http://sbbi.unl.edu/microRNASim. More
Han JC, Shu J, Cui J#. A New System For Human MicroRNA Functional Evaluation and Network Construction. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Shengzhen, China, 15 - 18 December 2016.2016
It is a tool for sequence motif identification on the short nucleotide sequences. MDS2 integrates the graph algorithms and large-scale sampling techniques to detect the sequence motif on the short sequences. It balances the specificity and sensitivity of motif and utilizes the statistical evaluation to minimize the risk of false identification. It has been proven that MDS2 is capable of predicting the motifs as short as 4bp-long, which are usually overlooked by other motif finding tools, such as MEME and DREME. Tool is available at http://sbbi.unl.edu/MDS2/. More
Development of the first Dietary MicroRNA Database (DMD), an archive database and analytic tool for food-borne microRNAs. Specifically, we conducted a comprehensive meta-analysis of food-borne microRNAs aggregated from literatures and public data resources and created a new publicly accessible database in the form of a web service around those results. The database can be assessed at http://sbbi.unl.edu/dmd/. More
Chiang K, Shu J, Zempleni J, Cui J#. Dietary MicroRNA Database (DMD): An archive database and analytic tool for microRNAs in human foods. PLoS ONE, 2015 Jun 1;10(6):e0128089.
Specifically, this new pipeline was built based on a meta-Lasso regression model and the proof-of-concept study was performed based on a large-scale genomic dataset from ~4,200 patients with 9 cancer types. We have developed a microRNA Dynamic Regulation Database (miRDR) to archive all the identified miRNA regulatory modules in each cancer, which can be accessed at http://sbbi.unl.edu/miRDR. The discovery has been documented in a manuscript that is currently under review. More
Shu J, Silva B, Cui J#. Dynamic and Modularized MicroRNA Regulation and Its Implication in Human Cancer. (under revision at Scientific Report).