- Sanjeev KumarAffiliated withBioCOS Life Sciences Private Limited Email author
- , Shipra AgrawalAffiliated withBioCOS Life Sciences Pvt. Limited, Institute of Bioinformatics and Applied Biotechnology
The complex phenotypes observed during the development of a disease are rarely due to single proteins. Hence, recently, it has been shown that protein networks are a source for identifying powerful biomarkers. These biomarker networks in many cases are more useful in predictions rather than the any individual gene.
Transcriptional modules rich in biomarkers can be generated by measuring coordinately expressed gene expression profiles in biofluids. These “biomarker modules” can further be used to predict new biomarker networks in an iterative manner. Such biomarkers based on networks could also be abstracted from the integrative network models of the cellular networks, which are constructed from high throughput proteomics and genomics datasets.
Stratification of disease progression from one stage to another: For example, the protein networks obtained from expression profile and/or interaction data fr ...
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- Network-based Biomarkers
- Reference Work Title
- Encyclopedia of Systems Biology
- pp 1524-1525
- Print ISBN
- Online ISBN
- Springer New York
- Copyright Holder
- Springer Science+Business Media, LLC
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- Editor Affiliations
- 1. Biomedical Sciences Research Institute, University of Ulster
- 2. Department of Computer Science, University of Rostock
- 3. Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST)
- 4. Department of Biomedical Engineering, Rensselaer Polytechnic Institute
- Author Affiliations
- 02051. BioCOS Life Sciences Private Limited, Bangalore Biotech Park (IBAB Campus), 560100, Bangalore, Karnataka, India
- 02052. BioCOS Life Sciences Pvt. Limited, Institute of Bioinformatics and Applied Biotechnology, Bangalore, Karnataka, India
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