Multi-omics data integration, interpretation, and its application

I Subramanian, S Verma, S Kumar… - … and biology insights, 2020 - journals.sagepub.com
To study complex biological processes holistically, it is imperative to take an integrative
approach that combines multi-omics data to highlight the interrelationships of the involved …

[HTML][HTML] Multi-omics approaches in cancer research with applications in tumor subtyping, prognosis, and diagnosis

O Menyhárt, B Győrffy - Computational and structural biotechnology journal, 2021 - Elsevier
While cost-effective high-throughput technologies provide an increasing amount of data, the
analyses of single layers of data seldom provide causal relations. Multi-omics data …

Onco‐multi‐OMICS approach: a new frontier in cancer research

S Chakraborty, MI Hosen, M Ahmed… - BioMed research …, 2018 - Wiley Online Library
The acquisition of cancer hallmarks requires molecular alterations at multiple levels
including genome, epigenome, transcriptome, proteome, and metabolome. In the past …

Comprehensive metabolic profiling of Parkinson's disease by liquid chromatography-mass spectrometry

Y Shao, T Li, Z Liu, X Wang, X Xu, S Li, G Xu… - Molecular …, 2021 - Springer
Background Parkinson's disease (PD) is a prevalent neurological disease in the elderly with
increasing morbidity and mortality. Despite enormous efforts, rapid and accurate diagnosis …

Challenges and emergent solutions for LC‐MS/MS based untargeted metabolomics in diseases

L Cui, H Lu, YH Lee - Mass spectrometry reviews, 2018 - Wiley Online Library
In the past decade, advances in liquid chromatography‐mass spectrometry (LC‐MS) have
revolutionized untargeted metabolomics analyses. By mining metabolomes more deeply …

Analytical and biochemical perspectives of protein O-GlcNAcylation

J Ma, C Wu, GW Hart - Chemical Reviews, 2021 - ACS Publications
Protein O-linked β-N-acetylglucosamine (O-GlcNAc) modification (O-GlcNAcylation) is a
unique monosaccharide modification discovered in the early 1980s. With the technological …

Metabolomic machine learning predictor for diagnosis and prognosis of gastric cancer

Y Chen, B Wang, Y Zhao, X Shao, M Wang… - Nature …, 2024 - nature.com
Gastric cancer (GC) represents a significant burden of cancer-related mortality worldwide,
underscoring an urgent need for the development of early detection strategies and precise …

Defining disease-related modules based on weighted miRNA synergistic network

C Li, P Dou, T Wang, X Lu, G Xu, X Lin - Computers in Biology and …, 2023 - Elsevier
MicroRNAs (miRNAs) play an important role in the biological process. Their expression and
functional changes have been observed in most cancers. Meanwhile, there exists …

Spatial differentiation of metabolism in prostate cancer tissue by MALDI-TOF MSI

MK Andersen, TS Høiem, BSR Claes, B Balluff… - Cancer & …, 2021 - Springer
Background Prostate cancer tissues are inherently heterogeneous, which presents a
challenge for metabolic profiling using traditional bulk analysis methods that produce an …

Metabolomics and multi-omics integration: a survey of computational methods and resources

T Eicher, G Kinnebrew, A Patt, K Spencer, K Ying, Q Ma… - Metabolites, 2020 - mdpi.com
As researchers are increasingly able to collect data on a large scale from multiple clinical
and omics modalities, multi-omics integration is becoming a critical component of …