Simon Tomlinson Research Group
Stem cell bioinformatics
The stem cell bioinformatics group uses computational methods to explore the molecular mechanisms underpinning stem cells. To accomplish this we develop and apply advanced analysis techniques that make it possible to dissect complex collections of data from a wide range of technologies and sources.
Aims and areas of interest
The fields of stem cell biology and regenerative medicine research are fundamentally about understanding dynamic cellular processes such as development, reprogramming, repair, differentiation and the loss, acquisition or maintenance of pluripotency. In order to precisely decipher these processes at a molecular level, it is critical to identify and study key regulatory genes and transcriptional circuits.
Modern high-throughput molecular profiling technologies provide a powerful approach to addressing these questions as they allow the profiling of tens of thousands of gene products in a single experiment. A central focus of our work is to use bioinformatics to interpret the information produced by such technologies. We work extensively with data from public repositories and collaborations over a wide variety of platforms such as microarrays, RNA-seq and ChIP-seq, using the latest methods to integrate studies and explore biological function.
Current research interests
In general we are interested to understand how the functional properties of stem cells are encoded in their genome and expressed through the transcriptome. We take a purely bioinformatics approach to this work, capitalising on the wealth of genomic and functional data now available. We work mainly in the mouse embryonic stem cell system but occasionally in related areas. We take an integrative approach to data analysis, typically working with large data compendia and combining well established methods (analysis of gene expression scRNA-seq, RNA-seq etc) with advanced emerging methods from data science. To aid our work we make extensive use of R, custom databases, large scale storage and cluster computing. We build software systems using Java and even occasionally use Python.
Kay Kong - PhD student (Joint first supervisor with Prof Kamil Kranc)
Ludi Ling - MSc Bioinformatics student
Meishan Liu - MSc Bioinformatics student
Yuqing Wang - MSc Bioinformatics student
Xinyu Yi - MSc Bioinformatics student
Busra Senin - Undergraduate summer internship student
- Prof Ian Chambers
- Prof Keisuke Kaji
- Prof Clare Blackburn
- Prof Alexander Medvinsky