Article (Scientific journals)
Using prior knowledge from cellular pathways and molecular networks for diagnostic specimen classification
Glaab, Enrico
2015In Briefings in Bioinformatics, p. 1-13
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Keywords :
biomarker; pathway analysis; network analysis; machine learning; omics; cross-study analysis; prediction; supervised learning; dagnostics; biostatistics; classification; prognosis
Abstract :
[en] 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.
Research center :
Luxembourg Centre for Systems Biomedicine (LCSB): Biomedical Data Science (Enrico Glaab)
- Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group)
Disciplines :
Life sciences: Multidisciplinary, general & others
Human health sciences: Multidisciplinary, general & others
Physical, chemical, mathematical & earth Sciences: Multidisciplinary, general & others
Author, co-author :
Glaab, Enrico  ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
External co-authors :
Language :
Title :
Using prior knowledge from cellular pathways and molecular networks for diagnostic specimen classification
Publication date :
02 July 2015
Journal title :
Briefings in Bioinformatics
Publisher :
Oxford University Press
Pages :
Peer reviewed :
Peer Reviewed verified by ORBi
FnR Project :
FNR5782168 - Exploring Parkinson'S Disease Inhibitor Efficacy On A Non-dopaminergic Target, 2013 (01/12/2013-31/05/2016) - Enrico Glaab
Funders :
FNR - Fonds National de la Recherche [LU]
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