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University of Edinburgh



Stem Cells In-Depth Focus 2015

20 April 2015 | By

In this free-to-view Stem Cells In-Depth Focus, you can find out how computational ('in silico') methods can help to rationally choose bioactive small molecules to improve stem cell differentiation. The differentiation of pluripotent stem cells to hepatocyte-like cells is the focus of a second interesting article...


Label-free quantitative proteomics: Why has it taken so long to become a mainstream approach?

13 June 2013 | By Thierry Le Bihan, SynthSys and Institute of Structural and Molecular Biology, University of Edinburgh

In recent years, mass spectrometry (MS) based proteomics has moved from being a qualitative tool (used to mainly identify proteins) to a more reliable analysis tool, allowing relative quantitation as well as absolute quantitation of a large number of proteins. However, the developed quantitative methods are either specific for certain…


microRNA manipulation as a host-targeted antiviral therapeutic strategy

13 December 2011 | By Nouf N. Laqtom, University of Edinburgh & King Abdulaziz University and Amy H. Buck, University of Edinburgh

microRNAs (miRNA) are a class of non-coding RNA that regulate the precise amounts of proteins expressed in a cell at a given time. These molecules were discovered in worms in 1993 and only known to exist in humans in the last decade. Despite the youth of the miRNA field, miRNA…


Applying statistical inference in genomics with evidence based pathways: Towards elucidating new functional correlations of biomarkers

22 February 2010 | By Peter Ghazal, Professor of Molecular Genetics and Biomedicine, University of Edinburgh and Head of Division of Pathway Medicine and Associate Director of Centre for Systems Biology, Edinburgh, Al Ivens, Head of Data Analysis, Fios Genomics Ltd and Thorsten Forster, Statistical Bioinformatician, Division of Pathway Medicine, University of Edinburgh

In conventional pharmacogenomic studies, genetic polymorphisms (including single nucleotide and copy number variations) are elucidated from case-control distribution of individuals usually representing ethnicity, severity of disease, and positive or negative response to treatment. However, the interpretation of a single genetic marker in this context is complicated, as the same marker…