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University of Cambridge > Department of Oncology > Computational Biology Group > People > Dr. Shamith Samarajiwa

Computational Biology Group Members

Shamith Samarajiwa

Oncology

Telephone:+44 1223 40 4295
Fax:+44 1223 40 4199
email: shamith.samarajiwa at cancer.org.uk
Office Location:Room 130G, CRUK Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE

CV/Publications

Selected publications of ours in this area
  • Samarajiwa SA, Forster S, Auchettl K, and Herzog PJ. INTERFEROME: the database of interferon regulated genes. Nucleic Acids Res 2009 Jan;37(Database issue):D852-7. Epub 2008 Nov 7 [pubmed]
Software / Web tools
INTERFEROME

ReMOAT









Background

Shamith Samarajiwa trained in software engineering then studied Biomedical Science at the Monash University. Shamith then completed a Bachelor of Biomedical Science Honours degree with first class honours, specializing in Biochemistry/Structural Biology in Prof. Rod Devenish's Laboratory at Monash University (Melbourne, Australia). In 2006 Shamith completed a PhD. in Molecular Biology & Genomics working on innate immunity, inflammation and the interferon system with Prof. Paul Hertzog at The Monash Institute of Medical Research (MIMR) (Melbourne, Australia). From 2006 to 2008 he was the Foundation Bioinformatics Postdoctoral Fellow at the MIMR and also worked as a bioinformatician for the CRC for chronic inflammatory diseases. He is currently a Post Doctoral Research Associate in Prof. Simon Tavaré's Computational Biology group at the Department of Oncology.

Research

  • Use of Web 2.0 and Database technologies for Data Integration, Data Mining and Visualization : Designing computational and statistical methods, building software systems and use of these systems in performing downstream integrative analyses of large cancer-associated datasets, as well as developing schemas and relational databases for storing and searching such datasets. These will enable novel supervised and unsupervised interrogation, visualization and extraction of complex biological relationships underlying these high-throughput genomic datasets.

  • Regulatory and Comparative Genomics: Analysis of regulatory and evolutionary relationships in high-throughput (Microarray, ChipSeq, miRNA) biological data sets

  • Pathway Bioinformatics and Network Biology: Designing tools and methods for extracting and analysing pathway information and computational modeling of biological networks using genomic datasets.

  • Developing integrative computational approaches to understand the of biology of Innate Immunity, Inflammation and Cancer at the Systems level.

  • Interferon Systems Biology:tools and methods to integrate, data-mine and understand the impact of IFNs in cancer.



Collaborations

Narita Lab, Caldas Lab, METABRIC project at the Cambridge Research Institute


Teaching




© 2009 Computational Biology Group, Department of Oncology, University of Cambridge