Vertaisarvioitu katsausartikkeli tieteellisessä aikakauslehdessä (A2)

Interpreting the lipidome: bioinformatic approaches to embrace the complexity

Julkaisun tekijät: Kyle Jennifer E, Aimo Lucila, Bridge Alan J, Clair Geremy, Fedorova Maria, Helms J Bernd, Molenaar Martijn R, Ni Zhixu, Oresic Matej, Slenter Denise, Willighagen Egon, Webb-Robertson Bobbie-Jo M

Kustantaja: SPRINGER

Julkaisuvuosi: 2021

Journal: Metabolomics

Tietokannassa oleva lehden nimi: METABOLOMICS

Lehden akronyymi: METABOLOMICS

Volyymi: 17

Sivujen määrä: 10

ISSN: 1573-3882

eISSN: 1573-3890




Improvements in mass spectrometry (MS) technologies coupled with bioinformatics developments have allowed considerable advancement in the measurement and interpretation of lipidomics data in recent years. Since research areas employing lipidomics are rapidly increasing, there is a great need for bioinformatic tools that capture and utilize the complexity of the data. Currently, the diversity and complexity within the lipidome is often concealed by summing over or averaging individual lipids up to (sub)class-based descriptors, losing valuable information about biological function and interactions with other distinct lipids molecules, proteins and/or metabolites.

Aim of review
To address this gap in knowledge, novel bioinformatics methods are needed to improve identification, quantification, integration and interpretation of lipidomics data. The purpose of this mini-review is to summarize exemplary methods to explore the complexity of the lipidome.

Key scientific concepts of review
Here we describe six approaches that capture three core focus areas for lipidomics: (1) lipidome annotation including a resolvable database identifier, (2) interpretation via pathway- and enrichment-based methods, and (3) understanding complex interactions to emphasize specific steps in the analytical process and highlight challenges in analyses associated with the complexity of lipidome data.

Last updated on 2022-01-03 at 13:43