A roadmap for multi-omics data integration using deep learning

M Kang, E Ko, TB Mersha - Briefings in Bioinformatics, 2022 - academic.oup.com
High-throughput next-generation sequencing now makes it possible to generate a vast
amount of multi-omics data for various applications. These data have revolutionized …

Integration of multi-omics data for integrative gene regulatory network inference

N Zarayeneh, E Ko, JH Oh, S Suh… - … journal of data …, 2017 - inderscienceonline.com
Gene regulatory networks provide comprehensive insights and in-depth understanding of
complex biological processes. The molecular interactions of gene regulatory networks are …

Gene-and pathway-based deep neural network for multi-omics data integration to predict cancer survival outcomes

J Hao, M Masum, JH Oh, M Kang - … ISBRA 2019, Barcelona, Spain, June 3 …, 2019 - Springer
Data integration of multi-platform based omics data from biospecimen holds promise of
improving survival prediction and personalized therapies in cancer. Multi-omics data provide …

Integrative gene regulatory network inference using multi-omics data

N Zarayeneh, JH Oh, D Kim, C Liu… - 2016 IEEE …, 2016 - ieeexplore.ieee.org
Biological network inference is of importance to understand underlying biological
mechanisms. Gene regulatory networks describe molecular interactions of complex …

[PDF][PDF] Multifactorial Disease Detection Using Regressive Multi-Array Deep Neural Classifier.

D Venugopal, T Jayasankar… - … Automation & Soft …, 2021 - pdfs.semanticscholar.org
Comprehensive evaluation of common complex diseases associated with common gene
mutations is currently a hot area of human genome research into causative new …

Biologically interpretable, integrative deep learning for cancer survival analysis

J Hao - 2019 - digitalcommons.kennesaw.edu
Identifying complex biological processes associated to patients' survival time at the cellular
and molecular level is critical not only for develo** new treatments for patients but also for …

Integration of multi-omics data for expression quantitative trait loci (eQTL) analysis and eQTL epistasis

M Kang, J Gao - eQTL Analysis: Methods and Protocols, 2020 - Springer
Expression quantitative trait loci (eQTL) map** studies identify genetic loci that regulate
gene expression. eQTL map** studies can capture gene regulatory interactions and …

Gene-and Pathway-Based Deep Neural Network for Multi-omics Data Integration

J Hao¹, M Masum¹, JH Oh - … 2019, Barcelona, Spain, June 3–6 …, 2019 - books.google.com
Data integration of multi-platform based omics data from biospecimen holds promise of
improving survival prediction and personalized therapies in cancer. Multi-omics data provide …