Using machine learning approaches for multi-omics data analysis: A review
With the development of modern high-throughput omic measurement platforms, it has
become essential for biomedical studies to undertake an integrative (combined) approach to …
become essential for biomedical studies to undertake an integrative (combined) approach to …
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 …
approach that combines multi-omics data to highlight the interrelationships of the involved …
Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities
New technologies have enabled the investigation of biology and human health at an
unprecedented scale and in multiple dimensions. These dimensions include a myriad of …
unprecedented scale and in multiple dimensions. These dimensions include a myriad of …
More is better: recent progress in multi-omics data integration methods
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 …
Considerable work has been done with the advent of high-throughput studies, which have …
Data fusion and IoT for smart ubiquitous environments: A survey
The Internet of Things (IoT) is set to become one of the key technological developments of
our times provided we are able to realize its full potential. The number of objects connected …
our times provided we are able to realize its full potential. The number of objects connected …
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 …
Multi-omics data integration considerations and study design for biological systems and disease
S Graw, K Chappell, CL Washam, A Gies, J Bird… - Molecular omics, 2021 - pubs.rsc.org
With the advancement of next-generation sequencing and mass spectrometry, there is a
growing need for the ability to merge biological features in order to study a system as a …
growing need for the ability to merge biological features in order to study a system as a …
Unsupervised multi-omics data integration methods: a comprehensive review
Through the developments of Omics technologies and dissemination of large-scale
datasets, such as those from The Cancer Genome Atlas, Alzheimer's Disease Neuroimaging …
datasets, such as those from The Cancer Genome Atlas, Alzheimer's Disease Neuroimaging …
A selective review of multi-level omics data integration using variable selection
High-throughput technologies have been used to generate a large amount of omics data. In
the past, single-level analysis has been extensively conducted where the omics …
the past, single-level analysis has been extensively conducted where the omics …
Machine learning: its challenges and opportunities in plant system biology
Sequencing technologies are evolving at a rapid pace, enabling the generation of massive
amounts of data in multiple dimensions (eg, genomics, epigenomics, transcriptomic …
amounts of data in multiple dimensions (eg, genomics, epigenomics, transcriptomic …