An Adaptive Alignment Algorithm for Quality-Controlled Label-Free LC-MS
News Jan 30, 2013
Label-free quantification using precursor-based intensities is a versatile workflow for large-scale proteomics studies. The method requires extensive computational analysis and is therefore in need of robust quality control during the data mining stage. We present a new label-free data analysis workflow integrated into a multi-user software platform. A novel adaptive alignment algorithm has been developed to minimize the possible systematic bias introduced into the analysis. Parameters are estimated on the fly from the data at hand, producing a user-friendly analysis suite. Quality metrics are output in every step of the analysis as well as actively incorporated into the parameter estimation. We furthermore show the improvement of this system by comprehensive comparison to classical label-free analysis methodology as well as current state-of-the-art software.
The article is published online in Molecular & Cellular Proteomics and is free to access.
Sysmex Partners with Laboratories to Deliver Improved QC ManagementNews
Sysmex America has announced its latest innovation: a way to make quality assurance easier and more risk free than manual quality control processes.READ MORE
New Algorithms Help Extract 3-D Biological Structure from Limited DataNews
CAMERA researchers capitalize on their Multi-Tiered Iterative Phasing approach to determine molecular structure of proteins and viruses from X-ray free electron laser data.READ MORE
Comments | 0 ADD COMMENT
EMBO Workshop: Integrating Systems Biology: From Networks to Mechanisms to Models
Apr 15 - Apr 17, 2018
EMBL Course: Introduction to Next Generation Sequencing
Apr 09 - Apr 12, 2018
EMBL Course: Introduction to Metabolomics Analysis
Mar 20 - Mar 23, 2018
EMBL Course: RNA Sequencing Library Preparation - How Low Can You Go?
Mar 19 - Mar 23, 2018