Harnessing multimodal data integration to advance precision oncology
Advances in quantitative biomarker development have accelerated new forms of data-driven
insights for patients with cancer. However, most approaches are limited to a single mode of …
insights for patients with cancer. However, most approaches are limited to a single mode of …
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 …
The emerging role of mass spectrometry-based proteomics in drug discovery
Proteins are the main targets of most drugs; however, system-wide methods to monitor
protein activity and function are still underused in drug discovery. Novel biochemical …
protein activity and function are still underused in drug discovery. Novel biochemical …
mRNAs, proteins and the emerging principles of gene expression control
C Buccitelli, M Selbach - Nature Reviews Genetics, 2020 - nature.com
Gene expression involves transcription, translation and the turnover of mRNAs and proteins.
The degree to which protein abundances scale with mRNA levels and the implications in …
The degree to which protein abundances scale with mRNA levels and the implications in …
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 …
[HTML][HTML] Multivariable association discovery in population-scale meta-omics studies
It is challenging to associate features such as human health outcomes, diet, environmental
conditions, or other metadata to microbial community measurements, due in part to their …
conditions, or other metadata to microbial community measurements, due in part to their …
[HTML][HTML] Integration strategies of multi-omics data for machine learning analysis
Increased availability of high-throughput technologies has generated an ever-growing
number of omics data that seek to portray many different but complementary biological …
number of omics data that seek to portray many different but complementary biological …
[HTML][HTML] Artificial intelligence in cancer target identification and drug discovery
Artificial intelligence is an advanced method to identify novel anticancer targets and discover
novel drugs from biology networks because the networks can effectively preserve and …
novel drugs from biology networks because the networks can effectively preserve and …
Strategic vision for improving human health at The Forefront of Genomics
ED Green, C Gunter, LG Biesecker, V Di Francesco… - Nature, 2020 - nature.com
Starting with the launch of the Human Genome Project three decades ago, and continuing
after its completion in 2003, genomics has progressively come to have a central and …
after its completion in 2003, genomics has progressively come to have a central and …
DNA methylation-based predictors of health: applications and statistical considerations
DNA methylation data have become a valuable source of information for biomarker
development, because, unlike static genetic risk estimates, DNA methylation varies …
development, because, unlike static genetic risk estimates, DNA methylation varies …