Maximizing Analytical Performance in Biomolecular Discovery with LC-MS: Focus on Psychiatric Disorders.
Clicks: 124
ID: 278381
2024
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Star Article
30.0
/100
124 views
29 readers
AI Quality Assessment
Not analyzed
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
In this review, we discuss the cutting-edge developments in mass spectrometry proteomics and metabolomics that have brought improvements for the identification of new disease-based biomarkers. A special focus is placed on psychiatric disorders, for example, schizophrenia, because they are considered to be not a single disease entity but rather a spectrum of disorders with many overlapping symptoms. This review includes descriptions of various types of commonly used mass spectrometry platforms for biomarker research, as well as complementary techniques to maximize data coverage, reduce sample heterogeneity, and work around potentially confounding factors. Finally, we summarize the different statistical methods that can be used for improving data quality to aid in reliability and interpretation of proteomics findings, as well as to enhance their translatability into clinical use and generalizability to new data sets. Expected final online publication date for the , Volume 17 is May 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
| Reference Key |
smith2024maximizingannual
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Smith, Bradley J;Guest, Paul C;Martins-de-Souza, Daniel; |
| Journal | Annual review of analytical chemistry (Palo Alto, Calif.) |
| Year | 2024 |
| DOI |
10.1146/annurev-anchem-061522-041154
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.