AI Article Synopsis
- Label-free quantitative LC-MS profiling has gained significance in biomarker discovery and understanding biological processes over the last decade.
- Accurate data processing and statistical analysis are crucial due to variations in mass spectrometers, settings, and sample preparations, impacting life science research and disease mechanisms.
- The review highlights key aspects of data processing workflows, quality control methods, and trends in high-throughput analysis, especially for users lacking bioinformatics expertise.
Article Abstract
Label-free quantitative LC-MS profiling of complex body fluids has become an important analytical tool for biomarker and biological knowledge discovery in the past decade. Accurate processing, statistical analysis and validation of acquired data diversified by the different types of mass spectrometers, mass spectrometer parameter settings and applied sample preparation steps are essential to answer complex life science research questions and understand the molecular mechanism of disease onset and developments. This review provides insight into the main modules of label-free data processing pipelines with statistical analysis and validation and discusses recent developments. Special emphasis is devoted to quality control methods, performance assessment of complete workflows and algorithms of individual modules. Finally, the review discusses the current state and trends in high throughput data processing and analysis solutions for users with little bioinformatics knowledge.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.talanta.2010.10.029 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!