Computational methods for molecular diagnostics of cancer
The group's aim is to develop novel diagnostic tools for cancer through the application of emerging molecular and genomic technologies. The current focus of research is on circulating tumour-specific DNA as a non-invasive modality to assess disease progression and response to therapy.
We use genomic platforms to identify somatic mutations and structural rearrangements in tumour samples, and develop assays to measure the presence of tumour-specific sequences. We apply these to monitor the levels of cell-free tumour DNA in serial blood samples collected from patients during treatment and clinical follow-up.
We integrate and innovate a variety of state-of-the-art methods including microfluidic digital PCR, paired-end next generation sequencing and targeted resequencing. We use these to collect novel types of molecular data. The proposed project involves the analysis of such novel data, in conjunction with concurrent clinical information, to develop clinically meaningful diagnostic classifications. An additional goal is to support genomics analysis that forms an integral part of ongoing projects.
A successful candidate is expected to have enthusiasm and facility for computational analysis, a solid grounding in statistical approaches and familiarity with molecular biology concepts. Experience in analysis of experimental data in the physical or life sciences is advantageous.
Projects in our laboratory are highly interdisciplinary relying on close collaboration between experimentalists, clinicians and analysts, and thus demand good interpersonal skills, cooperation, independence, and scientific maturity.
We use genomic platforms to identify somatic mutations and structural rearrangements in tumour samples, and develop assays to measure the presence of tumour-specific sequences. We apply these to monitor the levels of cell-free tumour DNA in serial blood samples collected from patients during treatment and clinical follow-up.
We integrate and innovate a variety of state-of-the-art methods including microfluidic digital PCR, paired-end next generation sequencing and targeted resequencing. We use these to collect novel types of molecular data. The proposed project involves the analysis of such novel data, in conjunction with concurrent clinical information, to develop clinically meaningful diagnostic classifications. An additional goal is to support genomics analysis that forms an integral part of ongoing projects.
A successful candidate is expected to have enthusiasm and facility for computational analysis, a solid grounding in statistical approaches and familiarity with molecular biology concepts. Experience in analysis of experimental data in the physical or life sciences is advantageous.
Projects in our laboratory are highly interdisciplinary relying on close collaboration between experimentalists, clinicians and analysts, and thus demand good interpersonal skills, cooperation, independence, and scientific maturity.
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