Knowledge-Based Analysis of Protein Interaction Networks in Neurodegenerative Diseases
- PMID: 21882442
- Bookshelf ID: NBK56010
Knowledge-Based Analysis of Protein Interaction Networks in Neurodegenerative Diseases
Excerpt
The large-scale datasets generated by gene sequencing, proteomics, and other high-throughput experimental technologies are the bases for understanding life as a molecular system and for developing medical, industrial, and other practical applications. In order to facilitate bioinformatics analysis of such large-scale datasets, it is essential to organize our knowledge on higher levels of systemic functions in a computable form, so that it can be used as a reference for inferring molecular systems from the information contained in the building blocks. Thus, we have been developing the KEGG (Kyoto Encyclopedia of Genes and Genomes) database (
As part of the KEGG PATHWAY database, we organize disease pathway maps representing our knowledge of causative genes and molecular networks related to them for human diseases, including cancers, immune disorders, neurodegenerative diseases, metabolic disorders, and infectious diseases. Here we focus on neurodegenerative diseases, which were among the first to be made available on the KEGG PATHWAY database. A diverse range of neurodegenerative diseases is commonly characterized by the accumulation of abnormal protein aggregates. Causative genes, including those that produce abnormal proteins, have been identified in various neurodegenerative diseases. The current information is not sufficient to find common molecular mechanisms of the diseases. In this chapter we first present an overview of KEGG, including the KEGG DISEASE and KEGG DRUG databases, and describe the KEGG PATHWAY maps for six neurodegenerative diseases: Alzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), Huntington’s disease (HD), dentatorubropallidoluysian atrophy (DRPLA), and prion diseases (PRION). We then present bioinformatics analysis to combine and expand these pathway maps toward identification of common proteins and common interactions, which may lead to a better understanding of common molecular pathogenic mechanisms (2).
Copyright © 2010 by Taylor and Francis Group, LLC.
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