RNA-Seq Blog Transcriptome Research & Industry News
Identifying essential genes on a genome scale is resource intensive and has been performed for only a few eukaryotes. For less studied organisms...
Read More »CLEARER – a machine learning approach for predicting essential genes across eukaryotes
PORE-cupine – determination of isoform-specific RNA structure with nanopore long reads
Current methods for determining RNA structure with short-read sequencing cannot capture most differences between distinct transcript isoforms. Researchers at A*STAR, Singapore present RNA structure analysis using nanopore sequencing...
Read More »Researchers leverage whole transcriptome RNA sequencing and machine learning to improve lung cancer risk stratification
Bronchoscopy for suspected lung cancer has low diagnostic sensitivity, rendering many inconclusive results. The Bronchial Genomic Classifier (BGC) was developed to help with patient management by...
Read More »scRCAT-seq reveals subtype-specific isoforms differing in transcript demarcation
The differences in transcription start sites (TSS) and transcription end sites (TES) among gene isoforms can affect the stability, localization, and translation...
Read More »Bioinformatician, Post-doctoral candidate in Bioinformatics
Introduction A full-time position is available within the laboratory for Molecular Neurogenetics (www.molecular-neurogenetics.lu.se) led by Johan Jakobsson. The Jakobsson lab is interested in how gene expression is regulated in the brain and how this process influence neurodegenerative diseases, psychiatric disorders and brain ...
Read More »Machine learning for RNA sequencing-based intrinsic subtyping of breast cancer
Stratification of breast cancer (BC) into molecular subtypes by multigene expression assays is of demonstrated clinical utility. In principle, global RNA-sequencing (RNA-seq) should enable reconstructing existing transcriptional classifications of BC samples. Yet, it is not clear whether adaptation to RNA-seq ...
Read More »Scientists have identified a set of genomic features will help others to interpret RNA sequencing data
By studying the genomes of fruit flies, scientists from the Zaugg and Furlong groups at EMBL Heidelberg have identified a set of genomic features that can predict how much the expression of a gene varies between individuals in a species. Their...
Read More »LinTIMaT – a novel statistical learning approach for tracing cell lineage
Our body consists of numerous cells that are functioning continuously to keep us alive. Even though the cells in different organs contain almost similar DNA, they can perform different functions. While the cells perform different functions, their...
Read More »RNA-Seq, machine learning test enables diagnosis of lung disease when results from high-resolution CT imaging are not definitive
Veracyte, Inc. announced today the publication of an independent study showing that the Envisia Genomic Classifier enables physicians to more confidently diagnose idiopathic pulmonary fibrosis (IPF)...
Read More »Single-cell RNA sequencing and machine learning identify major target of SARS-CoV-2 infection
Scientists at the Yale School of Medicine (YSM) are using single-cell RNA sequencing to learn how SARS-CoV-2 interacts with a host cell. The two senior...
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