Protein networks in disease.

By Trey Ideker, Roded Sharan. Genome Research, 2008

837 citations recorded by the source corpus.

During a decade of proof-of-principle analysis in model organisms, protein networks have been used to further the study of molecular evolution, to gain insight into the robustness of cells to perturbation, and for assignment of new protein functions. Following these analyses, and with the recent rise of protein interaction measurements in mammals, protein networks are increasingly serving as tools to unravel the molecular basis of disease. We review promising applications of protein networks to disease in four major areas: identifying new disease genes; the study of their network properties; identifying disease-related subnetworks; and network-based disease classification. Applications in infectious disease, personalized medicine, and pharmacology are also forthcoming as the available protein network information improves in quality and coverage.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/961759e91b5a804edd85b8baf63c9e7649e886af

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Citations in the corpus

The challenge of modeling protein assemblies: the CASP12‐CAPRI experiment (2018, background): “Their dysregulation or disruption often leads to disease.(2,3) Characterizing these interactions and understanding the principles that governs them is therefore more than ever at the center”
Network propagation: a universal amplifier of genetic associations (2017, background): “A network module, the member genes of which are associated with a particular disease. applications, including gene function prediction 6,21 , module discovery 22 , disease characterization 23,24 and drug target prediction 25 .”
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Global Functional Atlas of Escherichia coli Encompassing Previously Uncharacterized Proteins (2009, background): “Since the biological role of a protein is not necessarily reflected in its primary sequence, the elucidation of molecular interaction networks can provide an alternate perspective even in the absence of detailed phenotypic data [16,71].”
Network Medicine: A Network-based Approach to Human Disease (2011, background): “The human interactome Although much of our understanding of cellular networks is derived from model organisms, the past decade has seen an exceptional growth in human-specific molecular interaction dat”
Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment (2021, background): “Their disruption or dysregulation often causes disease.(1,2) Characterizing the threedimensional (3D) structure and function of these interactions, at both the molecular and cellular levels, and elucidating the underlying physical principles remains an important goal of biology and medicine.”
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Automated Network Analysis Identifies Core Pathways in Glioblastoma (2010, methodology): “Human interaction and pathway data remain sparse and fragmented, and we must assume that the Human Interaction Network (HIN) used here represents a small portion of the full human interactome [47].”
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