Open AccessJournal Article
Interactome networks and human disease
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TL;DR: Why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease are detailed.
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Abstract: Complex biological systems and cellular networks may underlie most genotype to phenotype relationships. Here, we review basic concepts in network biology, discussing different types of interactome networks and the insights that can come from analyzing them. We elaborate on why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease.
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References
Understanding Cancer Progression Using Protein Interaction Networks
Emre Guney,Rebeca Sanz-Pamplona,Angels Sierra,Baldo Oliva +3 more
- 01 Jan 2012
TL;DR: This chapter describes the characteristics of genes involved in cancer and the relationships between them in the context of the protein-protein interaction network and explains several methods to predict novel candidates that are potentially involved incancer and its progression using topological information encoded in theprotein- protein interaction network.
3
•Dissertation
Systems Biology Approaches to Evaluate Disease Modularity
Reyes Palomares,Armando Adolfo +1 more
- 01 Jan 2014
TL;DR: The hypothesis is enunciated, mathematical modelling based on kinetic law formalism for studying the functional modularity of the metabolism and the development of a workflow to integrate metabolic and kinetic data from different databases for metabolic modelling are declared.
3
Integrating large, disparate biomedical ontologies to boost organ development network connectivity
Chimezie Ogbuji,Rong Xu +1 more
- 28 Jun 2012
TL;DR: This paper presents a method for integrating the GO's anatomical development process hierarchies with anatomical concepts in the FMA that correspond to the organs participating in the development processes, and provides an evaluation of the impact of this integration on the number of paths from diseases and disease genes to theFMA concepts that participate in theDevelopment processes that annotate the genes.
3
Review Article Pathways to neurodegeneration: mechanistic insights from GWAS in Alzheimer's disease, Parkinson's disease, and related disorders
Vijay K. Ramanan,Andrew J. Saykin +1 more
- 01 Jan 2013
TL;DR: A pathway- and network-driven model highlights several potential shared mechanisms in AD and PD that will inform future studies of these and other neurodegenerative disorders and suggests that biomarker and treatment strategies may require simultaneous targeting of multiple components, including some specific to disease stage, in order to assess and modulate Neurodegeneration.
3