Results 21 to 30 of about 79,155 (276)
Community-led, integrated, reproducible multi-omics with anvi’o [PDF]
Nature Microbiology, 2020 Big data abound in microbiology, but the workflows designed to enable researchers to interpret data can constrain the biological questions that can be asked. Five years after anvi’o was first published, this community-led multi-omics platform is maturing into an open software ecosystem that reduces constraints in ‘omics data analyses.
A. Murat Eren +33 more
openaire +6 more sources
Editorial: Multi-omic Data Integration in Oncology [PDF]
Frontiers in Oncology, 2020 Non peer ...
Finotello, Francesca +4 more
openaire +5 more sources
Multi-omics integration accurately predicts cellular state in unexplored conditions for Escherichia coli. [PDF]
, 2016 A significant obstacle in training predictive cell models is the lack of integrated data sources. We develop semi-supervised normalization pipelines and perform experimental characterization (growth, transcriptional, proteome) to create Ecomics, a ...
Kim, Minseung +3 more
core +2 more sources
Multi-omics integration reveals molecular networks and regulators of psoriasis. [PDF]
, 2019 BackgroundPsoriasis is a complex multi-factorial disease, involving both genetic susceptibilities and environmental triggers. Genome-wide association studies (GWAS) and epigenome-wide association studies (EWAS) have been carried out to identify genetic ...
Arneson, Douglas +5 more
core +3 more sources
Machine Learning and Integrative Analysis of Biomedical Big Data. [PDF]
, 2019 Recent developments in high-throughput technologies have accelerated the accumulation of massive amounts of omics data from multiple sources: genome, epigenome, transcriptome, proteome, metabolome, etc. Traditionally, data from each source (e.g., genome)
Choi, Howard +5 more
core +1 more source
, 2015 Stable, predictive biomarkers and interpretable disease signatures are seen as a signi cant step towards personalized medicine. In this per- spective, integration of multi-omic data com- ing from genomics, transcriptomics, glycomics, proteomics, metabolomics is a powerful strat- egy to reconstruct and analyse complex mul- ti-dimensional interactions ...
P Tieri, C Nardini, J Dent et al
openaire +3 more sources
MSPL: Multimodal Self-Paced Learning for Multi-Omics Feature Selection and Data Integration
IEEE Access, 2019 Rapid advances in high-throughput sequencing technology have led to the generation of a large number of multi-omics biological datasets. Integrating data from different omics provides an unprecedented opportunity to gain insight into disease mechanisms ...
Zi-Yi Yang +3 more
doaj +1 more source
Computational Models for Transplant Biomarker Discovery. [PDF]
, 2015 Translational medicine offers a rich promise for improved diagnostics and drug discovery for biomedical research in the field of transplantation, where continued unmet diagnostic and therapeutic needs persist.
Sarwal, Minnie M, Wang, Anyou
core +2 more sources
Statistical single cell multi-omics integration
Current Opinion in Systems Biology, 2018 Single cell high throughput genomic measurements are revolutionizing the fields of biology and medicine, providing a means to tackle biological problems that have thus far been inaccessible, such as the systematic discovery of new cell types, the identification of cellular heterogeneity in health and disease, or the cell-fate decisions taking place ...
Colomé-Tatché, M., Theis, F.J.
openaire +3 more sources
Multi-modal intermediate integrative methods in neuropsychiatric disorders: A review
Computational and Structural Biotechnology Journal, 2022 The etiology of neuropsychiatric disorders involves complex biological processes at different omics layers, such as genomics, transcriptomics, epigenetics, proteomics, and metabolomics.
Yanlin Wang +5 more
doaj +1 more source