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 ...
Read More »iDIRECT – disentangling direct from indirect relationships in association networks
Networks are vital tools for understanding and modeling interactions in complex systems in science and engineering, and direct and indirect...
Read More »LocCSN – constructing local cell-specific networks from single-cell data
Gene coexpression networks yield critical insights into biological processes, and single-cell RNA sequencing provides an opportunity to target...
Read More »Learning interpretable cellular and gene signature embeddings from single-cell transcriptomic data
The advent of single-cell RNA sequencing (scRNA-seq) technologies has revolutionized transcriptomic studies. However, large-scale integrative analysis...
Read More »DeepDRIM – a deep neural network to reconstruct cell-type-specific gene regulatory network using single-cell RNA-seq data
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...
Read More »Inference and analysis of cell-cell communication using CellChat
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...
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