Back to search

Article

Interpreting and integrating big data in the life sciences

2019-06-07

Abstract excerpt

Recent advances in omics technologies have led to the broad applicability of computational techniques across various domains of life science and medical research. These technologies provide an unprecedented opportunity to collect omics data from hundreds of thousands of individuals and to study gene-disease association without the aid of prior assumptions about the trait biology. Despite the many advantages of mod...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
a2d1d624-29ff-5329-a9e4-d78ea27b4795
DOI
10.7287/peerj.preprints.27603v2
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Interpreting and integrating big data in the life sciencesDOI 10.7287/peerj.preprints.27603v2
Big Data Analysis in Biology: A Detailed ReviewSemantic proximity
Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases.Semantic proximity
Vertical and horizontal integration of multi-omics data with miodinSemantic proximity
Severe testing with high-dimensional omics data for enhancing biomedical scientific discovery.Semantic proximity
Multi-omics approaches to disease.Semantic proximity
Analyzing associations and higher-order effects in multi-omics data with double machine learningSemantic proximity
A multi-omics data simulator for complex disease studies and its application to evaluate multi-omics data analysis methods for disease classificationSemantic proximity
A multi-omics data simulator for complex disease studies and its application to evaluate multi-omics data analysis methods for disease classificationSemantic proximity
The future is now? Clinical and translational aspects of “Omics” technologiesSemantic proximity
Multi-Omics factor analysis - a framework for unsupervised integration of multi-omic data setsSemantic proximity
Molecular pathological epidemiology: new developing frontiers of big data science to study etiologies and pathogenesisSemantic proximity
playOmics: A multi-omics pipeline for interpretable predictions and biomarker discoverySemantic proximity
Select a neighboring publication to make it the new centre.