Deep learning improves microRNA target prediction from sequence
MicroRNAs, or miRNAs, are small RNA molecules that help control gene expression. They work by guiding Argonaute proteins to specific RNA targets, where they can reduce the production of proteins from those genes. Predicting which RNAs a miRNA will ...
scLS – a computationally efficient differentially expressed gene detection algorithm
The proposed algorithm enables pseudotime-based dynamics without the need for explicit regression models or branch assignment Single-cell RNA sequencing (scRNA-seq) is a method to measure gene expression of individual cells, allowing observation of various cellular processes, including cell differentiation, ...
ExoShorkie – predicting RNA-seq coverage of exogenous genomes in yeast by transfer learning
RNA sequencing, or RNA-seq, allows researchers to measure which parts of a genome are being transcribed into RNA and how strongly those regions are expressed. Being able to predict RNA-seq coverage directly from DNA sequence could help scientists better ...
The Lomb–Scargle periodogram-based differentially expressed gene detection along pseudotime
Single-cell RNA sequencing has become an important tool for studying how cells change over time. Instead of measuring an average signal from millions of cells, it examines individual cells, allowing researchers to observe biological processes such as development, immune ...
Learning the grammar of gene regulation
New AI-based tool allows to predict activity of DNA sequences Deep learning approaches have transformed how scientists predict activity and function of DNA sequences in the genome. A new AI tool called Corgi (Context-aware Regulatory Genomics Inference), developed by ...
seq2ribo – structure-aware integration of machine learning and simulation to predict ribosome location profiles from RNA sequences
Proteins are made when ribosomes move along messenger RNA (mRNA) molecules, reading their genetic instructions one codon at a time. Exactly where ribosomes pause or move quickly can influence how much protein is produced, making ribosome behavior an important ...
Nanopore sequencing advances pseudouridine detection in ribosomal RNA
RNA molecules contain more than just the four standard nucleotide bases. After RNA is produced, cells often modify individual nucleotides through a variety of chemical changes that can influence RNA stability, structure, and function. One of the most common ...
Study is first demonstration of gene transcription measurement in the living brain
Tool enables monitoring of selected genes in living tissue with a blood test Cell function is determined by how DNA is expressed into proteins. That process includes two main steps — transcription, when messenger RNA (mRNA) makes copies of ...
Decima predicts gene expression at single-cell resolution
Genes are controlled by regulatory DNA sequences that determine when and where genes are turned on. Understanding how these DNA sequences influence gene expression is one of the major goals of modern genomics. Over the past several years, researchers ...
Single-cell total RNA sequencing expands our view of gene regulation
Understanding how genes are turned on and off in individual cells is essential for studying development and disease. Most single cell RNA sequencing methods focus on polyadenylated RNA, which mainly captures protein coding transcripts, but misses many important noncoding ...
RNA-Seq Products & Services
Most Shared Posts
- Upcoming Conference – The Festival of Genomics & Biodata
- Gene trajectory inference for single-cell data by optimal transport metrics
- Upcoming Workshop – Advanced Topics in Single Cell RNA-Seq Analysis: Multiomics ATAC-Seq & RNA-Seq
- BAP-seq – bioorthogonal masked acylating agents for proximity-dependent RNA labelling
- Single-cell RNA-seq of the rare virosphere reveals the native hosts of giant viruses in the marine environment
Stay Connected