Missing data in multi-omics integration: Recent advances through artificial intelligence
JE Flores, DM Claborne, ZD Weller… - Frontiers in artificial …, 2023 - frontiersin.org
Biological systems function through complex interactions between various 'omics
(biomolecules), and a more complete understanding of these systems is only possible …
(biomolecules), and a more complete understanding of these systems is only possible …
[HTML][HTML] Multi-omics approaches in cancer research with applications in tumor subty**, prognosis, and diagnosis
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 …
analyses of single layers of data seldom provide causal relations. Multi-omics data …
Integrated multi-omics analyses in oncology: a review of machine learning methods and tools
In recent years, high-throughput sequencing technologies provide unprecedented
opportunity to depict cancer samples at multiple molecular levels. The integration and …
opportunity to depict cancer samples at multiple molecular levels. The integration and …
[HTML][HTML] Integrative multi-omics approaches in cancer research: from biological networks to clinical subtypes
YJ Heo, C Hwa, GH Lee, JM Park, JY An - Molecules and cells, 2021 - Elsevier
Multi-omics approaches are novel frameworks that integrate multiple omics datasets
generated from the same patients to better understand the molecular and clinical features of …
generated from the same patients to better understand the molecular and clinical features of …
Graph machine learning for integrated multi-omics analysis
Multi-omics experiments at bulk or single-cell resolution facilitate the discovery of hypothesis-
generating biomarkers for predicting response to therapy, as well as aid in uncovering …
generating biomarkers for predicting response to therapy, as well as aid in uncovering …
Recent advances in systems and synthetic biology approaches for develo** novel cell-factories in non-conventional yeasts
Microbial bioproduction of chemicals, proteins, and primary metabolites from cheap carbon
sources is currently an advancing area in industrial research. The model yeast …
sources is currently an advancing area in industrial research. The model yeast …
[HTML][HTML] Approaches to integrating metabolomics and multi-omics data: a primer
T Jendoubi - Metabolites, 2021 - mdpi.com
Metabolomics deals with multiple and complex chemical reactions within living organisms
and how these are influenced by external or internal perturbations. It lies at the heart of …
and how these are influenced by external or internal perturbations. It lies at the heart of …
Computational approaches for network-based integrative multi-omics analysis
Advances in omics technologies allow for holistic studies into biological systems. These
studies rely on integrative data analysis techniques to obtain a comprehensive view of the …
studies rely on integrative data analysis techniques to obtain a comprehensive view of the …
MOMA: a multi-task attention learning algorithm for multi-omics data interpretation and classification
Motivation Accurate diagnostic classification and biological interpretation are important in
biology and medicine, which are data-rich sciences. Thus, integration of different data types …
biology and medicine, which are data-rich sciences. Thus, integration of different data types …
Mergeomics 2.0: a web server for multi-omics data integration to elucidate disease networks and predict therapeutics
The Mergeomics web server is a flexible online tool for multi-omics data integration to derive
biological pathways, networks, and key drivers important to disease pathogenesis and is …
biological pathways, networks, and key drivers important to disease pathogenesis and is …