ArticleBriefings in bioinformatics2016
Using prior knowledge from cellular pathways and molecular networks for diagnostic specimen classification.
Article in Briefings in bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Causal network analysis of omics data using prior knowledge databases.Briefings in bioinformatics · 2025Pooled it
- The PERMIT guidelines for designing and implementing all stages of personalised medicine research.Scientific reports · 2024Article
- Bioinformatics approaches for studying molecular sex differences in complex diseases.Briefings in bioinformatics · 2024Review
- Construction of a pathway-level model for preeclampsia based on gene expression data.Hypertension research : official journal of the Japanese Society of Hypertension · 2024Article
- Ten quick tips for biomarker discovery and validation analyses using machine learning.PLoS computational biology · 2022Article
- Machine-learning algorithms based on personalized pathways for a novel predictive model for the diagnosis of hepatocellular carcinoma.BMC bioinformatics · 2022Article
- Network-based cancer genomic data integration for pattern discovery.BMC genomic data · 2021Article
- Biomarker discovery studies for patient stratification using machine learning analysis of omics data: a scoping review.BMJ open · 2021Article
- Highly accurate diagnosis of papillary thyroid carcinomas based on personalized pathways coupled with machine learning.Briefings in bioinformatics · 2021Article
- Knowledge-primed neural networks enable biologically interpretable deep learning on single-cell sequencing data.Genome biology · 2020Article
- Semi-supervised identification of cancer subgroups using survival outcomes and overlapping grouping information.Statistical methods in medical research · 2019Article
- Navigating the disease landscape: knowledge representations for contextualizing molecular signatures.Briefings in bioinformatics · 2019Review
- Review
- Personalized Prediction of Acquired Resistance to EGFR-Targeted Inhibitors Using a Pathway-Based Machine Learning Approach.Cancers · 2019Article
- Network approaches to systems biology analysis of complex disease: integrative methods for multi-omics data.Briefings in bioinformatics · 2018Review
- Robust method for identification of prognostic gene signatures from gene expression profiles.Scientific reports · 2017Article
- Analytical Strategy to Prioritize Alzheimer's Disease Candidate Genes in Gene Regulatory Networks Using Public Expression Data.Journal of Alzheimer's disease : JAD · 2017Article
- Identifying Significant Features in Cancer Methylation Data Using Gene Pathway Segmentation.Cancer informatics · 2016Article
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Abstract
For many complex diseases, an earlier and more reliable diagnosis is considered a key prerequisite for developing more effective therapies to prevent or delay disease progression. Classical statistical learning approaches for specimen classification using omics data, however, often cannot provide diagnostic models with sufficient accuracy and robustness for heterogeneous diseases like cancers or neurodegenerative disorders. In recent years, new approaches for building multivariate biomarker models on omics data have been proposed, which exploit prior biological knowledge from molecular networks and cellular pathways to address these limitations. This survey provides an overview of these recent developments and compares pathway- and network-based specimen classification approaches in terms of their utility for improving model robustness, accuracy and biological interpretability. Different routes to translate omics-based multifactorial biomarker models into clinical diagnostic tests are discussed, and a previous study is presented as example.
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