Jamie is currently a Post-doctoral Research Associate in the SCALE Lab at Imperial College London. SCALE Lab's focus is on the management and processing of data in general and HPC data analytics, data visualisation, spatial data, indexing, new hardware for data processing and novel storage technology. At SCALE lab I work on game-changing DNA storage technology (storing digital data within DNA) and investigating viral insertions into the 100,000 Genomes project and developing high-parallel bioinformatics pipelines to run on HPC (High-Performance Computing) platforms. Prior to that he worked as a Scientific Programmer (Research Software Engineer) at the Institute of Cancer Research, London.

Jamie undertook and completed his Doctorate at Royal Holloway University of London where he conducted research in the Centre for Systems and Synthetic Biology (CSSB) and department of Computer Science.

A list of Jamie's research publications can be found under the papers section.

http://orcid.org/0000-0001-8164-4753

After completing his Ph.D. Jamie worked at the ICR (Institute of Cancer Research) where he provided consulting to support researchers in software engineering, High-performance computing (HPC) and Workflow languages.

Doctoral Thesis


Jamie's doctoral thesis (Ph.D supervised by Dr. Hugh Shanahan) explored the analysis of high-throughput biological datasets using distributed computing, particularly sequencing data produced by high-throughput technologies, which is increasing at an unprecedented scale. As a result of these technological advancements, large, complex data sets are routinely deposited in public archives such as the SRA (Sequence Read Archive) - as of January 2017 the SRA alone contains over a Petabyte of data. Jamie conducted a detailed literature review into biochemical protocol steps applied in preparing nucleic acid samples for sequencing. His thesis describes, in detail, bias that can be introduced at the molecular level of sequencing workflow steps. This work was published in a GigaScience paper: Investigation into the annotation of protocol sequencing steps in the sequence read archive

In this work Jamie also explored sequencing metadata by applying advanced data-mining techniques and SQL (Structured Query Language). This quantified the level of annotation in 29,958 experiments deposited in the SRA by searching for keywords in meta-data annotation of key protocol steps. He found that only 7.10%, 5.84% and 7.57% of all records (fragmentation, ligation and enrichment, respectively) had at least one keyword corresponding to one of the three protocol steps. Only 5.58% of all top-level SRA experiment records had annotation for all three steps.

Jamie's thesis also focused on applying distributed computing to tackle the processing of such large datasets. His thesis reviewed various types of distributed and high-performance computing, namely batch-scheduled computing, Hadoop MapReduce, Spark and MPI (Message-Passing Interface). This was published in Oxford University Press - Briefings in Bioinformatics paper: The application of Hadoop in Structural Bioinformatics. PDB-Hadoop was developed with MapReduce, allowing for user-defined operations (the thesis explored structural analysis and molecular docking jobs) to be carried out, in a high-throughput parallel fashion, on the entirety of the PDB (Protein Data-Bank). PDB-Hadoop was presented at the ISCB 3DSig Structural Bioinformatics and Computational Biophysics conference 2015 in Dublin, Ireland.

Hadoop MapReduce was demonstrated in benchmarking to be competitive against batch-scheduled computing, and at the time the development of Spark enabled 2-3 orders of magnitude gains in through-put through optimisations such as in-memory caching and lazy-executions. Jamie decided to apply MapReduce on Spark to the processing of typically large short-read RNA-Seq datasets. Given the poor lack of annotation observed in the SRA, Jamie developed the above-mentioned analysis system named Hercules to quantify sequence-specific deviations in the distribution of mapped RNA-Seq reads. The distributed method uses intra-exon motif correlations, and is explained in a Journal of Integrative Bioinformatics paper: A novel method to detect bias in Short Read NGS RNA-seq data, and in more depth for the computer-science employed, in a International Journal for the Foundations of Computer Science paper: Transcriptomics: Quantifying non-uniform read distribution using MapReduce..

Drug Design, Chemical, Pharmacological research

After completing his masters, Jamie assisted research efforts at the Biomedical Sciences department of St. Georges Hospital Medical School working with Prof. Brian Austen (chair of the Alzheimer's association) on developing neuroprotective drug molecules for neurodegenerative disorders. The current drugs under development are Peptide based PDZ binding ligands Jamie-3-Asn and Jamie-3-Glu based on the work of Pizerchio and Spaller et al and Austen et al.

(Top) Jamie using a Carl Zeiss Fluorescent microscope (Bottom) Jamie-3-Asn drug stained neuronal cells using three fluorophores

Masters Thesis Jamie's masters thesis was: "Characterisation of Neuroprotective PDZ binding ligands". The objective was to design a drug molecule to slow the progression of neurodegenerative disorders by targeting the PDZ1 domain of a GCPR protein (G-protein coupled receptor) called PSD-95 in neuronal cells of the brain. Repeated triggering of this receptor by excesses in glutamate, occurring during tissue damage, results in excito-toxicity (via toxic calcium intrusion into cells) that is a key mechanism implicated in neuro-degenerative diseases such as Alzheimer's, epilepsy, and stroke, which currently have no cure. Jamie utilised computational Chemistry and molecular modeling to select a group of potential drug molecules to synthesise for targeting neuronal cells. He then used chemical synthesis (SPPS - Solid Phase Peptide Synthesis) and analytical chemistry techniques (Mass spectrometry, HPLC) to characterise these molecules prior to testing them on cultured neuronal cells from the SHSY-5Y neuroblastoma cell line. - As a byproduct of this work Jamie also developed the Zeus molecular visualisation software in order to assist his work. This was subsequently used to  generate molecular imagery for a Poster presentation and has been listed at the World Index of BioMolecular Visualization Resources

Continuation of this work involves using immunohistochemistry to label and visualise the peptide drugs within the cells (The gallery hosts some images from this process). Various cellular components and a location on the Jamie-3 drug molecule are labelled with antibodies and fluorescent dyes which fluoresce (glow) on application of laser light at a particular wavelength. This allows us to visualise the penetration and the co-localisation of the drug with the other stained cellular components by virtue of the fluorophores responding to different wavelengths of light, thereby producing different colours.

This work has been published in an American Journals of Chemistry paper: Cyclisation of Cell-Penetrating PDZ-Binding Peptides Directed to PSD95. It was also presented as a poster at the RSC (The Royal Society of Chemistry) Protein and Peptide Science Group Early Stage Researcher Meeting in November 2011 and subsequently at  St. Georges Research Day November 2011