Computational Biology Group Members
Sergii Ivakhno (CV)
Oncology
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Telephone:
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+44 1223 40 4293
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Fax:
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+44 1223 40 4199
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email:
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sergii.ivakhno@cancer.org.uk
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Office Location:
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Office 130H, CRUK
Cambridge Research Institute, Li Ka Shing
Centre, Robinson Way,
Cambridge CB2
0RE
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Background
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Sergii received MSc in Computer Science (Major
Bioinformatics) at the School of
Informatics, University of
Edinburgh, UK.
His thesis research was conducted under supervision of Dr Douglas
Armstrong from The Edinburgh
Centre for Bioinformatics and Institute for
Adaptive and Neural Computation. During this time Sergii also was an Erasmus Mundus
fellow and I held Erasmus Mundus fellowship from the European Commission.
During MSc studies, Sergii was also a visiting
student at the Massachusetts Institute of Technology,
Department of Bioengineering
and MIT Computational and Systems Biology
institute, where I worked with Prof Douglas Lauffenburger
on nonlinear dimensionality reduction and probabilistic graphical
modelling of signalling networks. He also completed a summer internship
at the Wellcome Trust Sanger Institute,
Computational Functional Genomics Group working on integrative data
analysis of cancer transcriptome with Dr Anton Enright. Before coming to Edinburgh,
Sergii graduated from the Faculty of Biology, Taras Shevchenko
Kyiv National University (Kyiv State
University), where he
was awarded Bachelor and Master degree in Biology and Biochemistry, both
with distinctions.
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Research
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Sergii main area of research includes
development of methods for finding frequent copy number changes in
cancers using high-density SNP microarray
technologies. Sergii is also interested in
integrative statistical analysis of high-throughput genomic data for finding
distinct subtypes of genetic and functional alterations in cancers. In addition
to methodological developments, Sergii actively
collaborates with David Tuveson
Laboratory at the Cancer Research UK Cambridge Research
Institute (CRI) and Christine
Iacobuzio-Donahue at the Johns Hopkins Medical
School to study chromosome
aberrations in human pancreatic cancer and mouse models with SNP microarray technology.
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