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 …
Methods of integrating data to uncover genotype–phenotype interactions
MD Ritchie, ER Holzinger, R Li… - Nature Reviews …, 2015 - nature.com
Recent technological advances have expanded the breadth of available omic data, from
whole-genome sequencing data, to extensive transcriptomic, methylomic and metabolomic …
whole-genome sequencing data, to extensive transcriptomic, methylomic and metabolomic …
A review of approaches to identifying patient phenotype cohorts using electronic health records
C Shivade, P Raghavan… - Journal of the …, 2014 - academic.oup.com
Objective To summarize literature describing approaches aimed at automatically identifying
patients with a common phenotype. Materials and methods We performed a review of …
patients with a common phenotype. Materials and methods We performed a review of …
Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy
MS Ghaemi, DB DiGiulio, K Contrepois… - …, 2019 - academic.oup.com
Motivation Multiple biological clocks govern a healthy pregnancy. These biological
mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic …
mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic …
Combining multidimensional genomic measurements for predicting cancer prognosis: observations from TCGA
With accumulating research on the interconnections among different types of genomic
regulations, researchers have found that multidimensional genomic studies outperform one …
regulations, researchers have found that multidimensional genomic studies outperform one …
Unsupervised multiple kernel learning for heterogeneous data integration
J Mariette, N Villa-Vialaneix - Bioinformatics, 2018 - academic.oup.com
Motivation Recent high-throughput sequencing advances have expanded the breadth of
available omics datasets and the integrated analysis of multiple datasets obtained on the …
available omics datasets and the integrated analysis of multiple datasets obtained on the …
Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction
Objective Cancer can involve gene dysregulation via multiple mechanisms, so no single
level of genomic data fully elucidates tumor behavior due to the presence of numerous …
level of genomic data fully elucidates tumor behavior due to the presence of numerous …
Text Mining for Precision Medicine: Bringing Structure to EHRs and Biomedical Literature to Understand Genes and Health
The key question of precision medicine is whether it is possible to find clinically actionable
granularity in diagnosing disease and classifying patient risk. The advent of next-generation …
granularity in diagnosing disease and classifying patient risk. The advent of next-generation …
Machine learning-based analysis of multi-omics data on the cloud for investigating gene regulations
Gene expressions are subtly regulated by quantifiable measures of genetic molecules such
as interaction with other genes, methylation, mutations, transcription factor and histone …
as interaction with other genes, methylation, mutations, transcription factor and histone …
Identification of epigenetic interactions between miRNA and DNA methylation associated with gene expression as potential prognostic markers in bladder cancer
Background One of the fundamental challenges in cancer is to detect the regulators of gene
expression changes during cancer progression. Through transcriptional silencing of critical …
expression changes during cancer progression. Through transcriptional silencing of critical …