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John Archer

John Archer

Principal Researcher

Principal Researcher
Member type
CIBIO-InBIO, Universidade do Porto, Campus de Vairão, Rua Padre Armando Quintas. 4485-661 Vairão, Portugal

I graduated from the University of Liverpool in 1998 with a BSc in Microbiology. The following year I completed an MSc in Applied Parasitology and Medical Entomology. In 2000 I took a diploma in software technology at the University of Liverpool and in 2001 I graduated with an MSc in Software Engineering (with Distinction). From 2001 to 2005 I worked as a software developer in a Liverpool based IT company. In 2005 I combined my two areas of interest by starting a PhD in the department of bioinformatics at the University of Manchester under the supervision of Prof. David Robertson. This was funded by the BBSRC. The project involved looking at the evolutionary dynamics of HIV-1 but progressed into developing software for data analysis, specifically in relation to next generation sequence data. My main areas of interest were in characterizing the diversity found with the HIV-1, detecting recombinant breakpoints within HIV-1 genomes and tracking low frequency resistance mutations using next generation sequence (NGS) data. I completed my PhD in 2009.

Following my PhD I remained in Manchester for six years as a postdoc working on projects related to viral evolution and software development. During this time one of my projects, funded by Pfizer R&D (Cambridge, UK), involved the development of software to tracking low frequency resistance variants to the drug maraviroc while another, funded by Case Western Reserve University Hospital (Cleveland, US), involved the development of software for the genotyping of Next Generation Sequence (NGS) data obtained from viral populations. During this time, however, main area of interest was the development of a framework for distinguishing low frequency genomic variation from NGS error. This continues to be a challenge for the study of viruses. Data correction ranges from the empirical to the probabilistic, but none incorporate variation in nucleotide frequencies over a prolonged period of time. Such information, in conjunction with error rates, can aid in the differentiation between biological variants and error below frequencies at which such a distinction was previously impossible. Based on this I developed a probabilistic approach for the identification of variants that are maintained through time.

From 2013 to 2015 I spent two years at the Liverpool School of Tropical medicine where I developed software, called VTBuilder, that can be used to reconstruct transcriptomes from read data. Many of the bioinformatics techniques I learned during my earlier post doc and PhD were employed during this project in order to allow for the reconstruction of non-chimeric transcripts that reflect the isoform variation present within complex transcriptomes.

I joined CIBIO-InBIO in 2015 in order to take part in the development of a new computational biology research group. Project areas will include human genomics, domestication and de-novo sequencing projects for non-model species as well as software development.

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