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ORCA

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

Often during the analysis of biological data, it is of importance to interpret the correlation structure that exists between variables. Such correlations may reveal patterns of co-regulation that are indicative of biochemical pathways or common mechanisms of response to a related set of treatments. However, analyses of correlations are usually conducted by either subjective interpretation of the univariate covariance matrix or by applying multivariate modeling techniques, which do not take prior biological knowledge into account.

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iJRF

Submitted by ChenLiang on Sun, 09/10/2017 - 17:08

Integrative approaches characterizing the interactions among different types of biological molecules have been demonstrated to be useful for revealing informative biological mechanisms. One such example is the interaction between microRNA (miRNA) and messenger RNA (mRNA), whose deregulation may be sensitive to environmental insult leading to altered phenotypes. The goal of this work is to develop an effective data integration method to characterize deregulation between miRNA and mRNA due to environmental toxicant exposures.

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BioSeq-Analysis

Submitted by ChenLiang on Tue, 01/09/2018 - 17:37

With the avalanche of biological sequences generated in the post-genomic age, one of the most challenging problems is how to computationally analyze their structures and functions. Machine learning techniques are playing key roles in this field. Typically, predictors based on machine learning techniques contain three main steps: feature extraction, predictor construction and performance evaluation. Although several Web servers and stand-alone tools have been developed to facilitate the biological sequence analysis, they only focus on individual step.

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NanoStringNorm

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

The NanoString nCounter Platform is a new and promising technology for measuring nucleic acid abundances. It has several advantages over PCR-based techniques, including avoidance of amplification, direct sequence interrogation and digital detection for absolute quantification. These features minimize aspects of experimental error and hold promise for dealing with challenging experimental conditions such as archival formalin-fixed paraffin-embedded samples.

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ESPSearch

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

ESPSearch is a computer program for rapidly identifying nucleic acid or amino acid sequences of any length within any source sequence from promoters to entire genomes to protein libraries. ESPSearch utilizes a user-constructed database to identify many sequences simultaneously, including target sequences with wildcards and mismatches and user-specified patterns of those recognized sequences.

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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)

iScreen

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

High-throughput RNA interference (RNAi) screening has opened up a path to investigating functional genomics in a genome-wide pattern. However, such studies are often restricted to assays that have a single readout format. Recently, advanced image technologies have been coupled with high-throughput RNAi screening to develop high-content screening, in which one or more cell image(s), instead of a single readout, were generated from each well.

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Average: 5 (1 vote)

deepSOM

Submitted by ChenLiang on Sun, 01/08/2017 - 16:51

The computational prediction of novel microRNA within a full genome involves identifying sequences having the highest chance of being a miRNA precursor (pre-miRNA). These sequences are usually named candidates to miRNA. The well-known pre-miRNAs are usually only a few in comparison to the hundreds of thousands of potential candidates to miRNA that have to be analyzed, which makes this task a high classimbalance classification problem.

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5
Average: 5 (2 votes)

MLSeq

Submitted by ChenLiang on Sun, 09/10/2017 - 17:14

RNA sequencing (RNA-Seq) is a powerful technique for the gene-expression profiling of organisms that uses the capabilities of next-generation sequencing technologies. Developing gene-expression-based classification algorithms is an emerging powerful method for diagnosis, disease classification and monitoring at molecular level, as well as providing potential markers of diseases. Most of the statistical methods proposed for the classification of gene-expression data are either based on a continuous scale (eg. microarray data) or require a normal distribution assumption.

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Average: 4 (1 vote)

CCmiR

Submitted by ChenLiang on Tue, 01/09/2018 - 17:39

The identification of microRNA (miRNA) target sites is important. In the past decade, dozens of computational methods have been developed to predict miRNA target sites. Despite their existence, rarely does a method consider the well-known competition and cooperation among miRNAs when attempts to discover target sites. To fill this gap, we developed a new approach called CCmiR, which takes the cooperation and competition of multiple miRNAs into account in a statistical model to predict their target sites.

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