Research Fellow, Department of Oncology
- Understanding the molecular drivers of tumour development and progression through application of computational methods to integrate cancer genomics datasets.
- Novel cancer biomarker and drug target identification and characterization with focus on long non-coding RNA and the tumour microenvironment
I am actively seeking cross-disciplinary collaborations to meet the “big data” challenges presented by the above
- Execution of Next Generation Sequencing pipelines on large cancer datasets
- Interpretation of complex cancer datasets
- Multi-dimensional/platform data integration
- Novel cancer target/biomarker discovery, validation and disease positioning.
- Application of machine learning approaches to biological problems
My research interests are primarily in the area of bacterial genomics.
Current research topics include:
- Comparative genomics and phylogenetics of bacterial pathogens, particularly E. coli and Salmonella
- Use of transposon insertion sequencing methods (TraDIS/TnSeq/HITS/InSeq) to identify essential bacterial genes and genes important for survival in particular environments such as during infection of a model system
- Development of user-friendly software tools and online resources for exploring data from -omics technologies. Examples include coliBASE, Xbase and the recently-funded MicrobesNG.
Bacterial Genomics, High-throughput sequencing, Phylogenetics, Transposon Insertion Sequencing (TraDIS/TnSeq/HITS/InSeq), Genome assembly, Variant detection, RNAseq
Lead Bioinformatician, NHS Sheffield Diagnostic Genetics Service
NHS and research service provision
I have two different roles within the hub. Firstly, I am the point of contact with the Sheffield Diagnostics Genetics Service, which is part of the NHS. We offer next generation sequencing (NGS) on HiSeq, MiSeq and Ion Torrent machines, for a fee. We can also perform or assist with data analysis for an additional cost. We welcome research projects and involvement from the initial grant writing and planning stages. Secondly, I hope to be active in research. I was previously at the Sanger Institute where I was one of the main analysts on the UK10K project, which is a sequencing study of 10,000 people.
- Focusing lists of NGS-derived variants by biological relevance using tissue-specific expression and other intermediate phenotypes
- Approaches for testing combinations of NGS variants for association with disease
- Improved calling of insertions and deletions from NGS data
- Building pipelines for NGS analysis
- Quality control of NGS data
- QTL mapping with epistasis for outbred line crosses
- Statistical and mathematical modelling, complex disease genetics, evolutionary biology, clinical genomics
My research centres on identifying and addressing biology related to computational, population, and evolutionary genetics. Current research topics include:
- Identify and measure interbreeding sites between human and ancient hominins.
- Develop tools to infer the geographical origins of human population
- Develop tools to improve personalised medicine
- Develop theoretical framework, tools, and animal models to improve our understanding of complex diseases.
Molecular Evolution, Population Genetics, Genetic epidemiology, Biogeography, Genomics, Paleogenomics, and Epigenetics.
I am interested in understanding normal and and abnormal development.
- Can we find omics profiles that diagnose or predict disease progression?
- Can we integrate model organism, cell line and human cohort omics surveys to yield new understanding of normal and disease processes?
- How can we develop and exploit next generation sequencing to inform our understanding of biology?
- How to integrate models of function and disease across networks of interaction to yield targets for intervention?
Research opportunities include:
- Simplification of molecular profiles to allow integration across biological processes leading to discovery of key processes and targets involved in normal and diseased systems.
- Interpreting molecular profiling of gene high throughput genome sequencing/RNAseq analyses
- Integration and data interpretation challenges across human, model organism and cell line systems
- Building network models of specific diseases that collate and interpret integration across studies.
- Development of tools to group experiments based upon shared phenotypic and molecular attributes. Providing a sharing environment for data to share functional biological models
Reducing the gap between primary data and its interpretation. We perform computational biology using a systems approach to deliver interventions through understanding of processes underlying disease
Research Fellow in Computational Biology, Department of Computer Science
Having years of expertise in bioinformatics and systems biology, my research interests focus on developing computational tools, pipelines, workflows and systems biology models in omics research. I am currently working for AirPROM (€12m EU FP7 Project), which involves the building of individual-based models of cellular interaction, with the aim of using genomic data as the basis for the individual-based model of the cell. My main responsibilities are the analysis and interpretation of high-throughput biological data, with the aim to produce feasible and robust hypothesis for a deeper understanding of the biological systems under study.
- Quantification and inference of gene expression levels using probabilistic models;
- Inference of gene networks using regulatory data and gene expression data;
- Integrated approaches for the analysis of Next Generation Sequencing data.
- Teaching Modelling and simulation of Natural Systems
To understand and define the source of uncertainty in quantitative biology is a key aspect for improving sensitivity and accuracy in the analysis of high throughput genomic data. My research interests focus on developing computational tools, pipelines, appropriate experimental designs and protocols to assist in improving accuracy and sensitivity in the analysis of biological data.
- Propagation of uncertainty, associated to low-level data, in downstream analysis of microarray data
- Quantification and inference of gene expression levels using probabilistic models
- Inference of gene networks using regulatory data and gene expression data
- Integrated approaches for the analysis of Next Generation Sequencing data
My research is predominantly focused on different aspects of plant-microbe Interactions. Coming from a molecular biology background, I process sequencing data sets and metabolomic data to identify genes, genomic features and metabolic signatures that are involved in the molecular-genetic basis underpinning pathogen virulence and plant immunity. Examples include identifying disease-promoting effectors of Bremia lactucae by de novo assembly of RNAseq from mixed Bremia/host tissue, as well as improving the genome sequence assembly and annotation of Botrytis cinerea. My current project investigates the molecular and epigenetic basis of the onset and long-term (transgenerational) maintenance of plant immune priming.
Next Generation Sequencing data analysis, Genome assembly, Epigenetics, Plant-Microbe Interactions, non-model systems.
Lecturer in Bioinformatics, Department of Molecular Biology and Biotechnology
How do cells integrate information to make decisions about what genes should be expressed at a given time and in a given place? How do these processes malfunction to produce disease states? The correct regulation of gene expression is essential for the proper functioning of the cell, and incorrect regulation of genes is central to the mechanisms of many diseases. My interests rest in understanding how the many levels of eukaryotic gene regulation work together to perform these functions, using computational and functional genomics tools.
Examples of recent projects:
- The Polycomb Repressive Complex is targeted to CpG islands by KDM2b
- Reconfiguration of the 3D structure of the genome by a disease causing SNP
- Activation of the WNT pathway by androgen ablation therapy in prostate cancer.
- Association of RNA binding actors with coding and non-coding transcripts
Genome-wide measurement of gene expression at all stages of regulation:
- Transcription (ChIP-seq, ChIP-exo, 4/5/HiC)
- RNA processing (HITS-CLIP/iCLIP)
- RNA stability (RNA-seq, small RNA-seq)
- Translation (Ribosome Profiling)