Multi-omic and multi-view clustering algorithms: review and cancer benchmark

N Rappoport, R Shamir - Nucleic acids research, 2018‏ - academic.oup.com
Recent high throughput experimental methods have been used to collect large biomedical
omics datasets. Clustering of single omic datasets has proven invaluable for biological and …

More is better: recent progress in multi-omics data integration methods

S Huang, K Chaudhary, LX Garmire - Frontiers in genetics, 2017‏ - frontiersin.org
Multi-omics data integration is one of the major challenges in the era of precision medicine.
Considerable work has been done with the advent of high-throughput studies, which have …

Defining inflammatory cell states in rheumatoid arthritis joint synovial tissues by integrating single-cell transcriptomics and mass cytometry

F Zhang, K Wei, K Slowikowski, CY Fonseka… - Nature …, 2019‏ - nature.com
To define the cell populations that drive joint inflammation in rheumatoid arthritis (RA), we
applied single-cell RNA sequencing (scRNA-seq), mass cytometry, bulk RNA sequencing …

Integrated omics: tools, advances and future approaches

BB Misra, C Langefeld, M Olivier… - Journal of molecular …, 2019‏ - jme.bioscientifica.com
With the rapid adoption of high-throughput omic approaches to analyze biological samples
such as genomics, transcriptomics, proteomics, and metabolomics, each analysis can …

Correlation and association analyses in microbiome study integrating multiomics in health and disease

Y **
R Duan, L Gao, Y Gao, Y Hu, H Xu… - PLoS computational …, 2021‏ - journals.plos.org
Computational integrative analysis has become a significant approach in the data-driven
exploration of biological problems. Many integration methods for cancer subty** have …