Professor Mathias Uhlen has chosen the Qlucore Gene Expression Explorer to research proteomics, at the Albanova University Centre at the Royal Institute of Technology (KTH) in Sweden.
Prof Uhlen and his team are currently using the software for their work on the Human Protein Resource Project (HPR).
The HPR programme, funded by the Knut and Alice Wallenberg Foundation, will allow for a systematic exploration of the human proteome using antibody-based proteomics by combining high-throughput generation of affinity-purified (mono-specific) antibodies with protein profiling in a multitude of tissues and cells assembled in tissue microarrays.
The Qlucore Gene Expression Explorer software will enable Prof Uhlen and the researchers working on the HPR programme to analyse and explore data sets (containing more than 100 million data samples) on a regular PC.
The Qlucore software provides the user with instant feedback and takes advantage of all annotations and other links connected with the data being studied.
This is achieved while offering powerful statistical functions such as false discovery rates (FDR) and p-values.
The main objective of the HPR programme is to produce specific antibodies to human target proteins using a high-throughput production method involving the cloning and protein expression of Protein Epitope Signature Tags (PrESTs).
After purification, the antibodies study expression profiles in cells and tissues and for functional analysis of the corresponding proteins in a range of platforms.
The programme also hosts the Human Protein Atlas (HPA) portal with expression profiles of human proteins in tissues and cells.
At present, the Human Protein Atlas portal contains more than five-million high-resolution images representing 5000 human proteins.
Carl-Johan Ivarsson, chief executive officer of Qlucore, said: 'Because the software displays data sets in 3D, researchers working on this project can visualise the results in real-time, directly on the computer screen.' Qlucore's software can be used to explore many different types of data, including gene expression micro-array data, protein-array data, antibody arrays, miRNA data and RT-PCR data.
The software can also be used to analyse protein data from 2-D gels, image-analysis data and with any data set of multivariate data of sizes up to 1000 samples and 100,000 variables, or 1000 variables and 100,000 samples.
