RNA-sequencing technology provides an effective tool for understanding miRNA regulation in complex human diseases, including cancers. A large number of computational methods have been developed to...
Read More »Pathway Analysis with OmicsBox: Analyzing a Salamander Limb Regeneration Transcriptomics Dataset
Researchers widely use pathway analyses as a tool for understanding the underlying biological mechanisms when dealing with a large number of features. One major issue is that they require pathway annotation data, which is usually only available for model or common organisms, making it difficult to analyze other lesser-known species...
Read More »QIAGEN launches RNA-seq Analysis portal with integrated Pathway Analysis
QIAGEN has launched the RNA-seq analysis portal (https://geneglobe.qiagen.com/us/analyze/rnaseq-analysis-and-biomarker-discovery-portal) which provides read-mapping and Ingenuity Pathway Analysis analysis to researchers looking for an easier way to go from Fastq file to biological insights. The portal is provided with the purchase of QIAseq ...
Read More »New method developed to infer gene regulatory networks from single-cell transcriptomic data
Single-cell RNA-sequencing (scRNA-seq) technologies offer the opportunity to understand regulatory mechanisms at single-cell resolution. Gene regulatory networks (GRNs) provide a crucial blueprint of regulatory mechanisms in cellular...
Read More »Single-cell gene set enrichment analysis and transfer learning for functional annotation of scRNA-seq data
Although an essential step, cell functional annotation often proves particularly challenging from single-cell transcriptional data. Several methods have been developed to accomplish this task. However, in most...
Read More »IReNA – Integrated regulatory network analysis of single-cell transcriptomes and chromatin accessibility profiles
Recently, single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) have been developed to separately measure transcriptomes...
Read More »BoT-Net – a lightweight bag of tricks-based neural network for efficient LncRNA–miRNA interaction prediction
Interactions of long non-coding ribonucleic acids (lncRNAs) with micro-ribonucleic acids (miRNAs) play an essential role in gene regulation, cellular metabolic, and pathological processes. Existing purely...
Read More »CLIPreg – Constructing translational regulatory networks from CLIP-, Ribo- and RNA-seq
The creation and analysis of gene regulatory networks have been the focus of bioinformatics research and underpins much of what is known...
Read More »SPIRAL – Significant Process InfeRence ALgorithm for single cell RNA-sequencing and spatial transcriptomics
Gene expression data is complex and may hold information regarding multiple biological processes at once. Researchers at Technion – Israel Institute of Technology have developed SPIRAL, an algorithm...
Read More »blitzGSEA: efficient computation of gene set enrichment analysis in Python
The identification of pathways and biological processes from differential gene expression is central for interpretation of data collected by transcriptomics assays. Gene set enrichment analysis (GSEA) is the most commonly used algorithm to calculate the significance of the relevancy of ...
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