Pathway Analysis

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...

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 ...

Networks are vital tools for understanding and modeling interactions in complex systems in science and engineering, and direct and indirect...

Gene coexpression networks yield critical insights into biological processes, and single-cell RNA sequencing provides an opportunity to target...

The advent of single-cell RNA sequencing (scRNA-seq) technologies has revolutionized transcriptomic studies. However, large-scale integrative analysis...

Researchers from Hong Kong Baptist University have developed a novel supervised deep neural network which utilizes the image of the target TF-gene pair and the ones of the potential neighbors to reconstruct...

Understanding global communications among cells requires accurate representation of cell-cell signaling links and effective systems-level analyses of those links. Researchers from the University of California...

The reduction in costs associated with performing RNA-sequencing has driven an increase in the application of this analytical technique; however...

Circular RNAs, a family of covalently circularized RNAs with tissue-specific expression, were recently demonstrated to play important roles in mammalian biology. Regardless of extensive research to predict...

Understanding the functions of genes requires the investigation of the structure of their regulatory networks of interactions. Single-cell RNA sequencing...