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Interaction network

About: Interaction network is a research topic. Over the lifetime, 2700 publications have been published within this topic receiving 113372 citations.


Papers
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Journal ArticleDOI
23 Jan 2014-PLOS ONE
TL;DR: This paper proposes to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors and achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods.
Abstract: One of the fundamental tasks in biology is to identify the functions of all proteins to reveal the primary machinery of a cell. Knowledge of the subcellular locations of proteins will provide key hints to reveal their functions and to understand the intricate pathways that regulate biological processes at the cellular level. Protein subcellular location prediction has been extensively studied in the past two decades. A lot of methods have been developed based on protein primary sequences as well as protein-protein interaction network. In this paper, we propose to use the protein-protein interaction network as an infrastructure to integrate existing sequence based predictors. When predicting the subcellular locations of a given protein, not only the protein itself, but also all its interacting partners were considered. Unlike existing methods, our method requires neither the comprehensive knowledge of the protein-protein interaction network nor the experimentally annotated subcellular locations of most proteins in the protein-protein interaction network. Besides, our method can be used as a framework to integrate multiple predictors. Our method achieved 56% on human proteome in absolute-true rate, which is higher than the state-of-the-art methods.

24 citations

BookDOI
01 Jan 2014
TL;DR: A global view of the Chaperone Network and systems-wide analysis of Protein Ubiquitylation: The authors Finally Have the Tiger by the Tail.
Abstract: Part I: Global View of the Chaperone Network.- Analysis of Chaperone Network Throughput.- Part II: Chaperones at the Ribosome.- Functions of Ribosome-associated Chaperones and Their Interaction Network.- Part III: The Hsp 70 and Hsp40 Chaperone Networks.- Yeast Hsp70 and J-protein Chaperones: Function and Interaction Network.- The Chaperone Networks: An Hsp70 Perspective.- Part IV: The Hsp90 Chaperone Network.- The Interaction Network of the Hsp90 Molecular Chaperone.- A Global View of the Proteome Perturbations by Hsp90 Inhibitors.- Designing Drugs Against Hsp90 for Cancer Therapy.- The Candida albicans Hsp90 Chaperone Network is Environmentally Flexible and Evolutionarily Divergent.- Part V: The p23 Chaperone Network.- Emergence and Characterization of the p23 Molecular Chaperone.- Part VI: Chaperones in the ER: Function and Interaction Network.- Chaperones of the ERAD Pathway.- Chaperones and Proteases of Mitochondria: From Protein Folding and Degradation to Mitophagy.- Part VII: The Ubiquitin-Proteasome System Network.- The Biogenesis of the Eukaryotic Proteasome.- Systems-wide Analysis of Protein Ubiquitylation: We Finally Have the Tiger by the Tail.- Part VIII: The Chaperone and Protease Networks in Model Bacteria and Parasites.- The Interaction Networks of E. coli Chaperones.- Chaperone-Proteases of Mycobacteria.- The Interaction Networks of Hsp70 and Hsp90 in the Plasmodium and Leishmania Parasites.- Index.

24 citations

Journal ArticleDOI
TL;DR: The app presented here makes the PathLinker functionality available to Cytoscape users and presents an example where the method was used to compute and analyze the network of interactions connecting proteins that are perturbed by the drug lovastatin.
Abstract: PathLinker is a graph-theoretic algorithm for reconstructing the interactions in a signaling pathway of interest. It efficiently computes multiple short paths within a background protein interaction network from the receptors to transcription factors (TFs) in a pathway. We originally developed PathLinker to complement manual curation of signaling pathways, which is slow and painstaking. The method can be used in general to connect any set of sources to any set of targets in an interaction network. The app presented here makes the PathLinker functionality available to Cytoscape users. We present an example where we used PathLinker to compute and analyze the network of interactions connecting proteins that are perturbed by the drug lovastatin.

24 citations

Journal ArticleDOI
20 Jul 2011-PLOS ONE
TL;DR: The functional organization of the human interactome reflects several integrative levels of functions with housekeeping and regulatory tissue-specific functions at the center and physiological tissue- specifics at the periphery, and it is proposed that gradients may represent a general principle of protein-protein interaction network organization.
Abstract: Interactome networks represent sets of possible physical interactions between proteins. They lack spatio-temporal information by construction. However, the specialized functions of the differentiated cell types which are assembled into tissues or organs depend on the combinatorial arrangements of proteins and their physical interactions. Is tissue-specificity, therefore, encoded within the interactome? In order to address this question, we combined protein-protein interactions, expression data, functional annotations and interactome topology. We first identified a subnetwork formed exclusively of proteins whose interactions were observed in all tested tissues. These are mainly involved in housekeeping functions and are located at the topological center of the interactome. This ‘Largest Common Interactome Network’ represents a ‘functional interactome core’. Interestingly, two types of tissue-specific interactions are distinguished when considering function and network topology: tissue-specific interactions involved in regulatory and developmental functions are central whereas tissue-specific interactions involved in organ physiological functions are peripheral. Overall, the functional organization of the human interactome reflects several integrative levels of functions with housekeeping and regulatory tissue-specific functions at the center and physiological tissue-specific functions at the periphery. This gradient of functions recapitulates the organization of organs, from cells to organs. Given that several gradients have already been identified across interactomes, we propose that gradients may represent a general principle of protein-protein interaction network organization.

23 citations

Patent
19 Dec 2008
TL;DR: In this article, a processor is configured to execute the method by designating a plurality of building performance variables for estimating the building performance, identifying an interaction network correlating a model building performance representative of the building's performance with the designated plurality of variables, selecting a known performance of at least one model structure as a proxy for the building performances, determining learned values for a pluralityof initially unknown parameter values from the interaction network and utilizing the learned values in the interaction networks to estimate building performance.
Abstract: There is provided a system of estimating a building performance, the system comprising a memory configured to store instructions comprising a method of estimating the building performance and a processor interactively linked to the memory. The processor is configured to execute the method by designating a plurality of building performance variables for estimating the building performance, identifying an interaction network correlating a model building performance representative of the building performance with the designated plurality of building performance variables, selecting a known performance of at least one model structure as a proxy for the building performance, determining learned values for a plurality of initially unknown parameter values from the interaction network and the at least one model structure having the known performance, and utilizing the learned values in the interaction network to estimate the building performance.

23 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202337
202290
2021183
2020221
2019201
2018163