LC-MS in Proteomics and Biomarker Discovery

Liquid chromatography-mass spectrometry (LC-MS) has emerged as a powerful analytical tool in the field of proteomics and biomarker discovery. LC-MS combines the high separation efficiency of liquid chromatography (LC) with the sensitive and specific detection capabilities of mass spectrometry (MS), enabling the identification and quantification of complex protein mixtures in biological samples. In proteomics, LC-MS facilitates the characterization of post-translational modifications, protein-protein interactions, and differential protein expression in health and disease states. The technique's high sensitivity and resolution enable the detection of low-abundance proteins, which are often critical for understanding disease mechanisms and identifying potential biomarkers. In biomarker discovery, LC-MS allows for the accurate profiling of disease-associated proteins, leading to the identification of novel diagnostic, prognostic, and therapeutic targets. Advances in LC-MS, such as tandem mass spectrometry (MS/MS), data-independent acquisition (DIA), and label-free quantification, have further enhanced the depth and accuracy of proteomic analysis. The integration of bioinformatics tools and machine learning approaches with LC-MS data has also improved biomarker validation and discovery. Overall, LC-MS continues to play a crucial role in advancing precision medicine by providing deeper insights into disease pathophysiology and facilitating the development of targeted therapeutic strategies.

Authors

Publication Details

Journal
International Journal of Science and Research Archive
Published
2025-03-20
DOI
https://doi.org/10.30574/ijsra.2025.14.3.0753
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

LC-MS in Proteomics and Biomarker Discovery

T Reshma, CM Bindu, T. Farmaan
1 links
International Journal of Science and Research Archive
Advanced Proteomics Techniques and Applications
article

LC-MS in Proteomics and Biomarker Discovery

T Reshma, CM Bindu, T. Farmaan
article en

Abstract

Liquid chromatography-mass spectrometry (LC-MS) has emerged as a powerful analytical tool in the field of proteomics and biomarker discovery. LC-MS combines the high separation efficiency of liquid chromatography (LC) with the sensitive and specific detection capabilities of mass spectrometry (MS), enabling the identification and quantification of complex protein mixtures in biological samples. In proteomics, LC-MS facilitates the characterization of post-translational modifications, protein-protein interactions, and differential protein expression in health and disease states. The technique's high sensitivity and resolution enable the detection of low-abundance proteins, which are often critical for understanding disease mechanisms and identifying potential biomarkers. In biomarker discovery, LC-MS allows for the accurate profiling of disease-associated proteins, leading to the identification of novel diagnostic, prognostic, and therapeutic targets. Advances in LC-MS, such as tandem mass spectrometry (MS/MS), data-independent acquisition (DIA), and label-free quantification, have further enhanced the depth and accuracy of proteomic analysis. The integration of bioinformatics tools and machine learning approaches with LC-MS data has also improved biomarker validation and discovery. Overall, LC-MS continues to play a crucial role in advancing precision medicine by providing deeper insights into disease pathophysiology and facilitating the development of targeted therapeutic strategies.

International Journal of Science and Research ArchiveVol. 14(3)
Openalex Percentile: Top 95%
Advanced Proteomics Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.