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István Kovács

Researcher at Northwestern University

Publications -  178
Citations -  5090

István Kovács is an academic researcher from Northwestern University. The author has contributed to research in topics: Automorphism & Cayley graph. The author has an hindex of 29, co-authored 157 publications receiving 3779 citations. Previous affiliations of István Kovács include Eötvös Loránd University & Harvard University.

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A reference map of the human binary protein interactome

Katja Luck, +94 more
- 08 Apr 2020 - 
TL;DR: The utility of HuRI is demonstrated in identifying the specific subcellular roles of protein–protein interactions and in identifying potential molecular mechanisms that might underlie tissue-specific phenotypes of Mendelian diseases.
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Widespread Macromolecular Interaction Perturbations in Human Genetic Disorders

TL;DR: This work functionally profile several thousand missense mutations across a spectrum of Mendelian disorders using various interaction assays, suggesting that disease-associated alleles that perturb distinct protein activities rather than grossly affecting folding and stability are relatively widespread.
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Network-based prediction of drug combinations.

TL;DR: A network-based methodology to identify efficacious drug combinations for specific diseases is proposed, and it is found that successful combinations tend to target separate neighbourhoods of the disease module in the human interactome.
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Community Landscapes: An Integrative Approach to Determine Overlapping Network Module Hierarchy, Identify Key Nodes and Predict Network Dynamics

TL;DR: The novel concept of ModuLand is introduced, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases.
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Network-based prediction of protein interactions.

TL;DR: It is shown that proteins tend to interact if one is similar to the other’s partners and that PPI prediction based on this principle is highly accurate and can offer mechanistic insights into disease mechanisms and complement future experimental efforts to complete the human interactome.