Nerlov Group: Single Cell Biology and Machine Learning in Blood Development, Cancer and Ageing

Supervisor: Claus Nerlov

About the Research 

The Nerlov laboratory studies the fundamental processes by which blood (or hematopoietic) stem cells sustain blood cell production throughout life and how ageing and haematological malignancies perturb this process, in order to develop molecularly informed strategies to counteract adverse blood phenotypes.

We use single cell genomic technologies (ATAC-seq and RNA-seq) and advanced genetics to study hematopoietic stem– and progenitor cells in normal development, during ageing and when blood cancers develop. We use computational biology and machine learning to identify the gene regulatory networks that control normal blood formation and the perturbations that occur when adverse phenotypes develop, and employ this knowledge to generate molecularly informed therapeutic strategies for conditions where cell types are dysfunctional (age-associated immune decline), under- or overproduced (anaemia, hypereosinophilia, mastocytosis), premalignant (clonal hematopoiesis (CH)) or malignant (acute myeloid leukaemia (AML), myeloproliferative disorders (MPD). 

Modelling and targeting of gene regulatory networks that control normal and dysfunctional hematopoiesis. Blood cells are specified from multipotent hematopoietic stem cells via a series of increasingly lineage-restricted progenitors. To identify the gene regulatory networks that control these successive lineage bifurcations, we will combine RNAseq and ATACseq to identify candidate regulators, which will be validated using in vivo CRISPR-Cas9-based gene manipulation and physiological and oncogenic perturbations. We will use computational and statistical modelling together with advanced deep learning approaches (algebraic, geometric and topological deep learning) to model the entire blood lineage specification process using multilayer/higher order neural networks to generate a predictive model, which will form the basis for identification and targeting of the regulatory elements that control age- and malignancy-associated phenotypes.

Training Opportunities 

Training is available in the areas of HSC and progenitor biology, single cell functional genomics (RNAseq, ATACseq), advanced flow cytometry, advanced mouse genetics, CRISPR/Cas9-based genome editing and library screening technologies, advanced bioinformatics, mathematical/statistical modelling and advanced deep learning.

Students will be enrolled on the MRC Weatherall Institute of Molecular Medicine DPhil Course, which takes place in the autumn of their first year. Running over several days, this course helps students to develop basic research and presentation skills, as well as introducing them to a wide range of scientific techniques and principles, ensuring that students have the opportunity to build a broad-based understanding of differing research methodologies.

Generic skills training is offered through the Medical Sciences Division's Skills Training Programme. This programme offers a comprehensive range of courses covering many important areas of researcher development: knowledge and intellectual abilities, personal effectiveness, research governance and organisation, and engagement, influence, and impact. Students are actively encouraged to take advantage of the training opportunities available to them.

As well as the specific training detailed above, students will have access to a wide range of seminars and training opportunities through the many research institutes and centres based in Oxford.

The Department has a successful mentoring scheme, open to graduate students, which provides an additional possible channel for personal and professional development outside the regular supervisory framework. We hold an Athena SWAN Silver Award in recognition of our efforts to build a happy and rewarding environment where all staff and students are supported to achieve their full potential.

Additional Supervisors 

1. Bethan Psaila 

2. Pietro Lio 

Publications