Data Analysis

High-throughput sequencing technologies, such as the Illumina Hi-seq, are powerful new tools for investigating a wide range of biological and medical problems. Massive and complex data sets produced by the sequencers create a need for development of statistical and computational ...

Sample- and gene- based hierarchical cluster analyses have been widely adopted as tools for exploring gene expression data in high-throughput experiments. Gene expression values (read counts) generated by RNA sequencing technology (RNA-seq) are discrete variables with special statistical properties, such ...

RNA-sequencing (RNA-seq) has become an established way for measuring gene expression in model organisms and humans. While methods development for refining the corresponding data processing and analysis pipeline is ongoing, protocols for typical steps have been proposed and are widely ...

Various biases affect high-throughput sequencing read counts. Contrary to the general assumption, researchers from Ludwig-Maximilians-University Munich show that bias does not always cancel out when fold changes are computed and that bias affects more than 20% of genes that are ...

Biological and biomedical research relies on comprehensive understanding of protein-coding transcripts. However, the total number of human proteins is still unknown due to the prevalence of alternative splicing. Now, a team led by researchers at Shanghai Jiao Tong University have ...

The transcriptome of single cells can reveal important information about cellular states and heterogeneity within populations of cells. Recently, single-cell RNA-sequencing has facilitated expression profiling of large numbers of single cells in parallel. To fully exploit these data, it is ...

Transcript quantification is a central task in the analysis of RNA-seq data. Accurate computational methods for the quantification of transcript abundances are essential for downstream analysis. However, most existing approaches are much slower than is necessary for their degree of ...

Small ncRNAs (sncRNAs) offer great hope as biomarkers of disease and response to treatment. This has been highlighted in the context of several medical conditions such as cancer, liver disease, cardiovascular disease, and central nervous system disorders, among many others. ...

MicroRNAs are the key post-transcriptional regulators of gene expression in development and stress responses. Thus, precisely quantifying the level of each particular microRNA is of utmost importance when studying the biology of any organism. The mirEX 2.0 web portal provides ...

The latest project from a group of MU College of Engineering researchers could be a gamechanger in the world of biological research. Jianlin Cheng, associate professor of computer science, and doctoral students Jilong Li and Jie Hou — with help ...