Glioblastoma Multimodal Analysis
AI Cancer Profiling
Mitochondrial RNA Processing
Combining RNA sequencing and pathology images identifies glioblastoma subgroups linked to survival
RNA sequencing combined with digital pathology and deep learning identifies distinct glioblastoma subgroups associated with substantial differences in patient survival...
Novel AI model trained on RNA-Seq data accurately detects key gene mutations and predicts biomarkers across 32 cancer types
RNA sequencing and pathology imaging data helped train an AI model to predict TP53 mutations, gene expression, cancer type, and clinical outcomes across solid tumors...
MitoClipSplice – machine learning improves RNA sequencing analysis of mitochondrial RNA processing
RNA sequencing combined with machine learning identifies mitochondrial RNA cleavage sites from soft-clipped reads, providing a new approach for investigating mitochondrial RNA...
Transcriptomic aging clock reveals age-related molecular patterns in opioid dependence
The study was led by first author Hai Duc Nguyen from the Division of Microbiology, Tulane National Biomedical Research Center, Tulane University. The corresponding author is Woong-Ki Kim, who is affiliated with the Division of Microbiology, Tulane National Biomedical Research ...
Machine learning improves RNA sequencing annotation of active genes
Understanding which parts of the genome are active is essential for studying how cells develop, specialize, and respond to disease. RNA sequencing provides researchers with information about gene activity, but turning sequencing signals into accurate maps of genes and ...
RNA sequencing helps predict stem cell transplant benefit in pediatric AML
Pediatric acute myeloid leukemia (AML) is a severe hematological malignancy where allogeneic hematopoietic stem cell transplantation (allo-HSCT) serves as a critical, life-saving intervention. However, selecting the appropriate candidates for this intensive procedure remains a clinical challenge. Current clinical decision-making ...
Protein ‘switch’ determines whether liposarcoma cells will become aggressive
Discovery highlights potential targets to help manage this rare cancer, which frequently recurs despite treatment New research from an expert in cancer biology explains what triggers liposarcoma cells to become more- or less-aggressive and identifies potential targets that could ...
The promise of long-read RNA-seq: reducing bias in analyses of allele imbalance
RNA sequencing allows researchers to measure which genes are active in a cell or tissue and how strongly they are expressed. However, determining whether different copies, or alleles, of the same gene are expressed at different levels can be ...
NextLongIso – a comprehensive Nextflow pipeline for multi-dimensional long-read RNA-seq analysis
Long-read RNA sequencing has given researchers a powerful way to examine the full range of RNA molecules produced by cells. Technologies from Pacific Biosciences, or PacBio, and Oxford Nanopore Technologies, or ONT, can sequence much longer stretches of RNA ...
Combining RNA sequencing and pathology images identifies glioblastoma subgroups linked to survival
RNA sequencing combined with digital pathology and deep learning identifies distinct glioblastoma subgroups associated with substantial differences in patient survival...
Novel AI model trained on RNA-Seq data accurately detects key gene mutations and predicts biomarkers across 32 cancer types
RNA sequencing and pathology imaging data helped train an AI model to predict TP53 mutations, gene expression, cancer type, and clinical outcomes across solid tumors...
MitoClipSplice – machine learning improves RNA sequencing analysis of mitochondrial RNA processing
RNA sequencing combined with machine learning identifies mitochondrial RNA cleavage sites from soft-clipped reads, providing a new approach for investigating mitochondrial RNA...
Transcriptomic aging clock reveals age-related molecular patterns in opioid dependence
The study was led by first author Hai Duc Nguyen from the Division of Microbiology, Tulane National Biomedical Research Center, Tulane University. The corresponding author is Woong-Ki Kim, who is affiliated with the Division of Microbiology, Tulane National Biomedical Research ...
Machine learning improves RNA sequencing annotation of active genes
Understanding which parts of the genome are active is essential for studying how cells develop, specialize, and respond to disease. RNA sequencing provides researchers with information about gene activity, but turning sequencing signals into accurate maps of genes and ...
RNA sequencing helps predict stem cell transplant benefit in pediatric AML
Pediatric acute myeloid leukemia (AML) is a severe hematological malignancy where allogeneic hematopoietic stem cell transplantation (allo-HSCT) serves as a critical, life-saving intervention. However, selecting the appropriate candidates for this intensive procedure remains a clinical challenge. Current clinical decision-making ...
RNA-Seq Products & Services
JOBS
Senior Product Manager | RNA-seq
About Plasmidsaurus Plasmidsaurus is on a mission to accelerate new cures and promote a healthier planet by unlocking a new level of productivity for scientists. Our sequencing services are used daily by thousands of innovators, including Nobel laureates, Fortune ...
INDUSTRY NEWS
Novogene Europe Expands Single-cell Sequencing Capability at Cambridge Omics Centre
Offers UK academic, biotech and biopharma researchers direct access to specialist project support, 10x Genomics Chromium Single Cell-based workflows, sequencing infrastructure and bioinformatics expertise Novogene Europe, a multiomics research services partner, today announced that it has expanded its single-cell ...
EVENTS
Upcoming RNA-Seq Webinar – Quantifying Inflammatory Resolution in Menstrual Fluid
Thursday, Juy 23rd | 10 AM PDT Longitudinal menstrual RNA-seq: a platform for studying inflammatory resolution, how it fails in disease, and enabling diagnostics. Menstruation is one of the few recurrent, non-pathological windows into inflammatory resolution in humans. Turning ...
RNA-SEQ Forum Feeds
- Bioinformatics Stackexchange
- SEQanswers - RNA Sequencing
I am considering using a hippocampal snRNA-seq atlas as the [...]
Question about snRNA Seq cell type deconvolution Hi everyone, I [...]
as it’s my first time attempting downstream analysis for single [...]
I am a biostatistician who is a newbie to bulk-RNA [...]
I have a question about multimapped reads in small RNA-seq [...]
Why can I not download this plugin: Interference is a [...]
Im currently working with 150bp paired-end sequencing for metatranscriptomics and [...]
I'm pretty new to RNAseq diff. expression analysis etc., and [...]
I have some 3' RNA seq samples (human). I want [...]
does anyone have any recommendations for studying deep learning for [...]
I have a dataset which contains samples which have either [...]
Currently working on a bulk RNA-seq project with two non-model [...]
I am trying to download and prepare RNA-seq data from [...]
Below are the RNA-sequencing results for two different mouse samples [...]
We would like to use bulk RNA-seq for characterizing cell [...]
I performed RNAseq comparing two different populations of CD8+ T [...]
The problem can be solved by simply installing Java, though [...]
I’m aligning paired-end RNA-seq (~150 bp; 461,828 reads) with STAR [...]
I have RNA-seq expression data from in vitro drug-treated samples [...]
I want to download the GSE203206 Alzheimer's dataset from the [...]
RNA-SEQ Data Analysis Tool Collections
Recent RNA-Seq Data Analysis Tools
MitoClipSplice – machine learning improves RNA sequencing analysis of mitochondrial RNA processing
Machine learning improves RNA sequencing annotation of active genes
NextLongIso – a comprehensive Nextflow pipeline for multi-dimensional long-read RNA-seq analysis
ISAtools improves full-length RNA isoform analysis from long-read RNA sequencing
Deep learning improves cell cycle prediction from single-cell RNA sequencing
MIRACLE keeps single-cell atlases up to date with continual learning
Seq-Scope-X pushes spatial transcriptomics beyond optical resolution
Spatial transcriptomics benchmark compares leading platforms
Nanopore RNA sequencing maps mitochondrial tRNA modifications in yeast
The Lomb–Scargle periodogram-based differentially expressed gene detection along pseudotime
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