Gene set enrichment analysis is a popular approach for prioritising the biological processes perturbed in genomic datasets. The Bioconductor project hosts over 80 software packages capable of gene set...
Read More »Featured RNA-Seq Job – Software Development Engineer
BD (Becton, Dickinson and Company) (Menlo Park, CA) Description: Cellular Research, Inc., a biotechnology research and development company founded in 2011 by innovators from Silicon Valley and Stanford University, was recently acquired by Becton Dickinson and has become an integral ...
Read More »A Systematic Evaluation of Feature Selection and Classification Algorithms Using Simulated and Real miRNA Sequencing Data
Sequencing is widely used to discover associations between microRNAs (miRNAs) and diseases. However, the negative binomial distribution (NB) and high dimensionality of data obtained using sequencing can lead to low-power results and low reproducibility. Several statistical learning algorithms have been ...
Read More »CAMUR – Knowledge extraction from RNA-Seq cancer data through equivalent classification rules
Nowadays, knowledge extraction methods from Next Generation Sequencing data are highly requested. In this work, researchers at the National Research Council, Italy focus on RNA-seq gene expression analysis and specifically on case-control studies with rule-based supervised classification algorithms that build ...
Read More »CoSREM – a graph mining algorithm for the discovery of combinatorial splicing regulatory elements
Alternative splicing (AS) is a post-transcriptional regulatory mechanism for gene expression regulation. Splicing decisions are affected by the combinatorial behavior of different splicing factors that bind to multiple binding sites in exons and introns. These binding sites are called splicing ...
Read More »RNASequel – accurate and repeat tolerant realignment of RNA-seq reads
RNA-seq is a key technology for understanding the biology of the cell because of its ability to profile transcriptional and post-transcriptional regulation at single nucleotide resolutions. Compared to DNA sequencing alignment algorithms, RNA-seq alignment algorithms have a diminished ability to ...
Read More »An Iterative Leave-One-Out Approach to Outlier Detection in RNA-Seq Data
The discrete data structure and large sequencing depth of RNA sequencing (RNA-seq) experiments can often generate outlier read counts in one or more RNA samples within a homogeneous group. Thus, how to identify and manage outlier observations in RNA-seq data ...
Read More »The rate of new microarray studies submitted to public databases far exceeds the rate of new RNA-Seq studies
Rapidly growing public gene expression databases contain a wealth of data for building an unprecedentedly detailed picture of human biology and disease. This data comes from many diverse measurement platforms that make integrating it all difficult. Although RNA-sequencing (RNA-seq) is ...
Read More »Post-doc Position Available – Bioinformatics and Integrative Biology
Institution – University of Massachusetts Medical School Web Address – http://www.umassmed.edu Location – Worcester Responsibilities – A postdoctoral associate position is available in Dr. Konstantin Zeldovich-s laboratory in the Program in Bioinformatics and Integrative Biology. The postdoctoral associate will work ...
Read More »Rcount – simple and flexible RNA-Seq read counting
Analysis of differential gene expression by RNA sequencing (RNA-Seq) is frequently done using feature counts, i.e. the number of reads mapping to a gene. However, commonly used count algorithms (e.g. HTSeq) do not address the problem of reads aligning with ...
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