James Eales, PhD

Dr, Dr

  • Room 5.015 AV Hill Building, Upper Brook Street

    M13 9PT Manchester

Accepting PhD Students

Personal profile

Further information

Overview

I am a Lecturer in Cardiovascular Computational Biology interested in studying the biological impact of genetic, transcriptomic and epigenetic variation on human health using high-throughput sequencing technologies. I apply experimental approaches from the fields of multi-omics, artificial intelligence and data-science to answer research questions directly relevant to our understanding of biological disease mechanisms. I have a special interest in translational research in cardiovascular medicine (hypertension, coronary artery disease) and nephrology (chronic kidney disease and renal histopathology) informed by genomics and transcriptomics.

Current projects in my lab focus on the following:

  • The application of artificial neural networks to explain the disease mechanisms of regulatory DNA sequences
  • The biomedical diagnostic applications of non-invasive transcriptomics
  • Quantification of alternative splicing in single cell transcriptomics data
  • Cell-type deconvolution from solid tissue and liquid biosamples by artificial neural networks applied to RNA-sequencing data

I have been creating and performing computational experiments for the large-scale analysis of genomics, transcriptomics, and epigenomics data for the last 10 years and have a particular interest in techniques for summarisation, visualisation and communication of high-dimensionality data for identifying causal disease genes. 

The work in my lab is funded by the British Heart Foundation, Translation Manchester and Health Innovation Manchester.

I have over 25 peer-reviewed publications, many in high-impact journals including Nature Genetics, the European Heart Journal, Nature Communications, Arteriosclerosis, Thrombosis and Vascular Biology and Journal of the American Society of Nephrology. I am also a recent reviewer for the European Heart Journal, Cardiovascular Research, Journal of Hypertension, Physiological Genomics, Journal of Human Hypertension and Scientific Reports. My work has over 2,000 citations and an H-index of 23.

 

My group

PhD Students

Steph Brown - PhD Student - Sequence-based deep learning models for prioritisation of disease-associated non-coding variants in cardiovascular disease

Qi Wang - PhD student - A deep learning model of tissue-specific alternative splicing in cardiovascular disease genes

Yong Sun - PhD Student - Insights into mechanisms of chronic kidney disease from human tissue multi-omics - co-supervised with Prof Maciej Tomaszewski

Kate Campbell - PhD Student - Drosophila based screening to replace mammalian systems to identify the functional role of candidate genes in controlling muscle dyadic architecture - co-supervised with Prof Andrew Trafford, Dr Kat Dibb, Prof Andreas Prokop.

Collaborators

I also collaborate with the research groups of Prof Maciej Tomaszewski and Prof Bernard Keavney.

 

 

 

Opportunities

PhD opportunities

None available at this time.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Areas of expertise

  • QH301 Biology
  • QH426 Genetics

Research Beacons, Institutes and Platforms

  • Digital Futures

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