European Bioinformatics Institute - Articles and news items

Progress by the Proteomics Standards Initiative

Issue 1 2009, Past issues / 7 February 2009 /

There are compelling reasons for regularising the capture and description of proteomics data. Adhering to community-consensus specifications for the annotation of data sets can increase confidence in results and the conclusions drawn upon them, and supports data re-use; working with standard formats and vocabularies can raise efficiency and facilitates sophisticated approaches to data handling and analysis. The Human Proteome Organisation’s Proteomics Standards Initiative (HUPO PSI) is a standards generating body comprising diverse members of the proteomics community and related trades. It develops reporting guidelines, data formats and vocabulary terms with which to describe the components of a proteomics experiment. This article briefly explores the benefits accruing to the use of reporting standards, for academics and for those in a commercial setting; describes HUPO PSI, its products and the status quo with respect to compatible tools and databases; and closes by pulling back to consider multi-domain investigations in the life sciences.

Detecting microRNA targets or siRNA off-targets using expression data

Issue 6 2008, Past issues / 3 December 2008 /

Recently, small RNAs such as microRNAs (miRNAs) have been demonstrated to be important regulators in both plants and animals. In animals miRNAs act as translational repressors of target genes through a combination of inhibition of translation and mRNA destabilisation. These molecules have been implicated in a multitude of diseases, including cancer and represent promising candidates for both diagnostics and therapeutics. While substantial progress has been made in the detection, sequencing and profiling of miRNAs, accurately delineating their targets remains difficult. Purely computational approaches hold much promise, yet they still suffer from over-prediction. In this article we will describe alternative approaches that utilise computational analysis combined with gene expression data to better detect miRNA effects and their targets. In particular we will describe Sylamer1 a new tool for the detection of miRNA targets and siRNA off-target effects from expression data.


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