Taking the ‘noise’ out of protein data

Share via AddThis
Posted May 10, 2013

Mass spectrometry technologies offer the promise to comprehensively identify all of the proteins present in complexes, cells and tissues. A typical analysis generates large numbers of peptide (bits of protein) spectra. A search engine then compares the experimental peptide data to theoretical peptide sequences in a protein database and identifies each peptide in the sample. But the search engine often falsely identifies the peptides.

To combat search engine error, Andrew Link, Ph.D., associate professor of Pathology, Microbiology and Immunology, and colleagues have now designed and implemented a novel algorithm called De-Noise. They optimized De-Noise using data sets generated from various control and biological samples and run on different mass spectrometers.

They report in the Journal of Proteome Research that De-Noise improves peptide identification by SEQUEST, one of the most widely used search engines. They demonstrated that De-Noise performs better than other methods used to validate SEQUEST peptide matches. The De-Noise software is available upon request and can be easily implemented with other search engines.

Source: Vanderbilt University



55,484 science & technology articles

Categories

Our Articles (see all)

General News

Follow us

Facebook   Twitter   Pinterest   StumbleUpon   Plurk
Google+   Tumblr   Delicious   RSS   Newsletter via Email

Featured Video (see all)


New study unlocks potential for ultra-lightweight and flexible 3D-printed metallic materials
Lawrence Livermore National Laboratory (LLNL) engineers have achieved unprecedented scalability in 3D-printed architectures of arbitrary geometry, opening the…

Featured Image (see all)


Researchers invent “smart” thread that collects diagnostic data when sutured into tissue
For the first time, researchers led by Tufts University engineers have integrated nano-scale sensors, electronics and microfluidics into…