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Circular RNA: Liquid biopsy biomarker for human diseases

A recent review, published in Protein & Cell, has explored the potential use of blood circular RNA as a liquid […]

Pheno-RNA: a method to associate genes with phenotypes

In a recent article, published in PNAS, researchers have described a new method – Pheno-RNA – to identify candidate genes […]

New International Consortium for Blood Genetics

A new international consortium of blood genetics has been created by a team at the University of Montreal. Unlike previous […]

Novel circRNA identified as a potential biomarker for pancreatic cancer

A recent study, published in the Journal of Human Genetics, has analysed and identified a novel circRNA in pancreatic cancer […]

scREAD: single-cell RNA-Seq database for Alzheimer’s Disease

Researchers at The Ohio State University have developed an integrated database known as scREAD – single-cell RNA-Seq database for Alzheimer’s […]

Biologically-validated AI is how scientists are realising the full potential of single-cell RNA sequencing

The promise of single-cell gene expression data Genomic data are an excellent source of novel disease biomarkers and targets. In […]

Opinion: We should address genetic data governance as we fight to find a COVID-19 vaccine

As the world rushes to develop a vaccine against COVID-19, geneticists are looking at our genes to understand the variation […]

MicroRNAs: The cast-off genetic material with the potential to fight diseases

This is a summary of an article written by Alice Godden originally published on TheConversation. Of the nearly 3 billion […]

How to: Choose the best RNA sequencing method for quantitative miRNA profiling

This article has been based upon this blog post, written by Dr Karolina Szczesna. RNA sequencing (RNA-seq) uses next generation […]

International Women’s Day 2020

Here at Front Line Genomics, we love to celebrate the contributions made to the field at our annual Festival of Genomics every January.

This year, we had over 120+ speakers and of which, 50% were women!