Stephen Taylor

The aim of my group is to develop state-of-the-art computational methods to break down barriers to aid the integration, visualisation, and analytics of biological datasets. We develop software tools and methodologies to interrogate a wide variety of modalities including spatial biology, imaging, genomics, transcriptomics, proteomics and epigenetics. This allows us to gain insight into the disease context and progression at a molecular and tissue level. Our work will enable opportunities for exploring cellular pathologies, discovering new biomarkers, and reclassifying disease taxonomies.

EXAMPLE PROJECTS

Multi-Dimensional Viewer (MDV)

Multi-Dimensional Viewer (MDV) allows user friendly analysis and visualisation of large multi-omic data sets https://github.com/Taylor-CCB-Group/MDV

Analysis of COVID-19 lung samples to identify cell phenotypes and cellular networks using MDV

SpOOx (Spatial Omics Oxford Pipeline)

This pipeline was developed in close collaboration with clinicians, computational biologists, laboratory scientists and mathematicians to comprehensively analyse spatial proteomics data. SpOOx automates the processing of data generated by the Hyperion Imaging System and we are developing it for other platforms. https://github.com/Taylor-CCB-Group/SpOOx/

LanceOtron : Deep learning for analysing epigenetic signals

LanceOtron, combines deep learning for recognizing peak shape with multifaceted enrichment calculations for assessing significance. In benchmarking ATAC-seq, ChIP-seq and DNase-seq, LanceOtron outperforms long-standing, gold-standard peak callers such as MACS2 through its improved selectivity and near-perfect sensitivity. https://github.com/LHentges/LanceOtron

Applications of Virtual, Mixed and Augmented Reality in Biomedicine

Previously seen as mainly for gaming, commercial and research institutions are investigating VR, MR and AR (XR) solutions to solve real world problems. In Biomedicine these include researching: training, simulation, mental health, data analysis, and studying disease progression. XR offers the promise of allowing new ways to interact with data and also accelerate patient therapy. https://medicalxr.molbiol.ox.ac.uk/