ResearchThe Portfolio showcases and details Jamie's research and software projects. A list of his research publications can be found under the publications section.
Computer Science Research![]()
Jamie spent two years as a Post-doctoral Research Associate in
![]() Prior to Imperial Jamie worked as a Scientific Programmer (Research Software Engineer) at the ![]()
Before joining the ICR, 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.
Doctoral Thesis![]() Jamie's doctoral thesis (Ph.D supervised by Prof. 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: ![]() 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: ![]() ![]() 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: ![]() ![]() Drug Design, Chemical and Pharmacological Research![]()
After completing his masters, Jamie assisted research efforts at the Biomedical Sciences department of
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. |
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