Monday, April 25, 2011

Published Study Validates New Protein Enrichment Approach For Low-Abundance Biomarker Detection

Hercules, CA — April 20, 2011 — University of Minnesota researchers found that Bio-Rad Laboratories' ProteoMiner protein enrichment kit enhanced identification of changes to low-abundance proteins and detection of post-translationally modified (PTM) proteins in human saliva. These findings offer promise for improving differential proteomic analyses and biomarker studies aimed at identifying disease-specific proteins and their PTM variants in various types of biological samples and fluids. The study was published in the Dec. 13, 2010, issue of the Journal of Proteome Research.
ven when highly sensitive mass spectrometers are used to analyze complex biological samples and bodily fluids, high-abundance proteins obscure the detection of lower-abundance proteins and their post-translational modifications," said Sri Bandhakavi, who led the study at the University of Minnesota in 2010. (Bandhakavi is now a senior scientist at Bio-Rad.) "These lower-abundance proteins and PTMs are often of most interest to researchers, given their association with specific disease or physiological states."

Friday, April 22, 2011

UC Berkeley Starts Synthetic Biology Institute

"Agilent will serve as a founding industry partner for the new Synthetic Biology Institute, which will involve Lawrence Berkeley National Laboratory and will focus on synthetic bio and bioengineering."

U of Minnesota Spends $3.6M NIH Grant on Supercomputer for Biological and Medical Research

The University of Minnesota Supercomputing Institute for Advanced Computational Research has installed a new high-performance computing system from SGI, christened Koronis, that it will use for multi-scale modeling, chemical dynamics, bioinformatics, computational biology, and biomedical imaging.
The university purchased the 1,152-core system with a $3.6 million grant from the National Institutes of Health's National Center for Research Resources. It will support NIH-funded research projects at the university.
Jeff McDonald, assistant director of high-performance computing operations at MSI, told BioInform that the latest purchase is the largest system at MSI and that it was selected because its shared memory capabilities best fit the researchers' needs.
In the grant abstract, the researchers wrote that the new system will help 33 research groups supported by 91 NIH grants "tackle ... the acquisition, analysis and visualization of petascale data from high-performance computing and high-throughput technologies."

Friday, April 15, 2011

MSblender: a probabilistic approach for integrating peptide identifications from multiple database search engines

"Shotgun proteomics using mass spectrometry is a powerful method for protein identification but suffers limited sensitivity in complex samples. Integrating peptide identifications from multiple database search engines is a promising strategy to increase the number of peptide identifications and reduce the volume of unassigned tandem mass spectra. Existing methods pool statistical significance scores such as p-values or posterior probabilities of peptide-spectrum matches (PSMs) from multiple search engines after high scoring peptides have been assigned to spectra, but these methods lack reliable control of identification error rates as data are integrated from different search engines. We developed a statistically coherent method for integrative analysis, termed MSblender. MSblender converts raw search scores from search engines into a probability score for all possible PSMs and properly accounts for the correlation between search scores. The method reliably estimates false discovery rates and identifies more PSMs than any single search engine at the same false discovery rate. Increased identifications increment spectral counts for all detected proteins and allow quantification of proteins that would not have been quantified by individual search engines. We also demonstrate that enhanced quantification contributes to improve sensitivity in differential expression analyses."
full article

However, a bunch of similar works have been published before. I am not convinced the method is much better than its counterparts.

Thursday, April 7, 2011

SIMA: Simultaneous Multiple Alignment of LC/MS Peak Lists

Motivation: Alignment of multiple liquid chromatography/mass spectrometry (LC/MS) experiments is a necessity today, which arises from the need for biological and technical repeats. Due to limits in sampling frequency and poor reproducibility of retention times, current LC systems suffer from missing observations and non-linear distortions of the retention times across runs. Existing approaches for peak correspondence estimation focus almost exclusively on solving the pairwise alignment problem, yielding straightforward but suboptimal results formultiple alignment problems.
Results: We propose SIMA, a novel automated procedure for alignment of peak lists from multiple LC/MS runs. SIMA combines hierarchical pairwise correspondence estimation withsimultaneous alignment and global retention time correction. It employs a tailored multidimensional kernel function and a procedure based on maximum likelihood estimation to find the retention time distortion function that best fits the observed data. SIMA does not require a dedicated reference spectrum, is robust with regard to outliers, needs only two intuitive parameters and naturally incorporates incomplete correspondence information. In a comparison with seven alternative methods on four different datasets, we show that SIMA yields competitive and superior performance on real-world data.

Wednesday, April 6, 2011

Global Market for Bioinformatics to touch $2.4 billion in 2011

"According to the new market research report from Industry Experts ‘Bioinformatics – A Global Market Overview’, global market for bioinformatics is estimated at about $2.4 billion in 2011 and further projected to reach $7.6 billion by 2017 registering a CAGR of 18.3% during the period 2007-2017.
At the beginning of the “genomic revolution”, Bioinformatics was applied in creating and maintaining a database that stored biological information, such as nucleotide and amino acid sequences. Development of this type of database involved not only design issues but also the development of complex interfaces, whereby researchers could access existing data, in addition to submitting new or revised data.
Market for Bioinformatics product categories analyzed in this study includes Bioinformatics Content, Bioinformatics Analysis Software & Services and Bioinformatics IT Infrastructure & Other Services. The report also includes the market analysis for end-use application analysis of Bioinformatics – Biopharma & Diagnostics, Genomics, Agriculture, Chemicals and Environmental & Other."