Search results for "protein interaction network"

showing 10 items of 18 documents

Identifying Early Warning Signals for the Sudden Transition from Mild to Severe Tobacco Etch Disease by Dynamical Network Biomarkers

2019

This article belongs to the Special Issue The Complexity of the Potyviral Interaction Network.

0106 biological sciences0301 basic medicineComplex systemsSystems biologyPotyvirusDiseaseBiologytobacco etch virusSeverity of Illness Index01 natural sciencesArticlePlant VirusesTranscriptomeViral Proteins03 medical and health sciencesPlant-virus interactionpotyvirusGene Expression Regulation PlantVirologyProtein Interaction MappingTobaccoGene Regulatory NetworksProtein Interaction Mapscomplex systemsGenePlant DiseasesGeneticsTransition (genetics)Tobacco etch virusGene Expression Profilingsystems biologyDNBBiotic stressresponse to infectionbiology.organism_classificationplant-virus interactionTobacco etch virusphase transitionsprotein-protein interaction networks030104 developmental biologyInfectious DiseasesPhase transitionsHost-Pathogen InteractionsMutationBiomarker (medicine)BiomarkersSignal Transduction010606 plant biology & botanyViruses
researchProduct

Gaining Insight into Exclusive and Common Transcriptomic Features Linked with Biotic Stress Responses in Malus

2017

Identifying key information in transcriptomic data is very important, especially when the “omic” study deals with plant responses to stresses in field conditions where a high number of variables and disturbing factors may affect the analysis. In this meta-analysis we collected 12 transcriptomic works in Malus in order to identify which key genes, proteins, gene categories are involved in general plant pathological conditions and those features linked with exclusive biotic stress responses. Those genes that are only related with molecular responses to pathogen attacks and those linked with other plant physiological processes were identified. A pipeline composed by pathway and gene set enrich…

0106 biological sciences0301 basic medicineMalusPlant ScienceComputational biologylcsh:Plant cultureErwinia01 natural sciencesTranscriptometranscriptomics03 medical and health sciencesSettore AGR/07 - Genetica AgrariaHeat shock proteinBotanylcsh:SB1-1110GeneTranscription factorOriginal Researchbiologybiotic stresses; Malus; meta-analysis; protein-protein interaction network; transcriptomicsfood and beveragesBiotic stressbiotic stressesbiology.organism_classificationmeta-analysisCrosstalk (biology)030104 developmental biologyMalusbiotic stresses Malus meta-analysis protein-protein interaction network transcriptomicsprotein-protein interaction network010606 plant biology & botanyFrontiers in Plant Science
researchProduct

HIPPIE v2.0: Enhancing meaningfulness and reliability of protein-protein interaction networks

2016

The increasing number of experimentally detected interactions between proteins makes it difficult for researchers to extract the interactions relevant for specific biological processes or diseases. This makes it necessary to accompany the large-scale detection of protein-protein interactions (PPIs) with strategies and tools to generate meaningful PPI subnetworks. To this end, we generated the Human Integrated Protein-Protein Interaction rEference or HIPPIE (http://cbdm.uni-mainz.de/hippie/). HIPPIE is a one-stop resource for the generation and interpretation of PPI networks relevant to a specific research question. We provide means to generate highly reliable, context-specific PPI networks …

0301 basic medicineHippieReliability (computer networking)BiologyWeb BrowserBioinformaticsProtein protein interaction networkComputational biology03 medical and health sciences0302 clinical medicineResource (project management)GeneticsHumansDatabase IssueGraph algorithmsProtein Interaction MapsDatabases ProteinResearch questionGraphical user interfacebusiness.industryReproducibility of ResultsData science030104 developmental biologyComputingMethodologies_PATTERNRECOGNITIONProtein interaction mappingbusiness030217 neurology & neurosurgeryProtein Interaction MapSoftware
researchProduct

Identifying Host Molecular Features Strongly Linked With Responses to Huanglongbing Disease in Citrus Leaves

2018

© 2018 Balan, Ibáñez, Dandekar, Caruso and Martinelli. A bioinformatic analysis of previously published RNA-Seq studies on Huanglongbing (HLB) response and tolerance in leaf tissues was performed. The aim was to identify genes commonly modulated between studies and genes, pathways and gene set categories strongly associated with this devastating Citrus disease. Bioinformatic analysis of expression data of four datasets present in NCBI provided 46–68 million reads with an alignment percentage of 72.95–86.76%. Only 16 HLB-regulated genes were commonly identified between the three leaf datasets. Among them were key genes encoding proteins involved in cell wall modification such as CESA8, pecti…

0301 basic medicineHuanglongbing HLB citrus protein–protein interaction network transcriptomics RNA-SeqPlant BiologyHuanglongbingRNA-SeqPlant Sciencelcsh:Plant cultureBiologycitrusTranscriptometranscriptomics03 medical and health sciencesExpansinSettore AGR/07 - Genetica AgrariaHeat shock proteinGenetics2.1 Biological and endogenous factorslcsh:SB1-1110RNA-SeqAetiologyGeneTranscription factorOriginal Research2. Zero hungerGeneticsHuanglongbing; HLB; citrus; protein–protein interaction network; transcriptomics; RNA-SeqPectinesteraseSettore AGR/03 - Arboricoltura Generale E Coltivazioni ArboreeHLB030104 developmental biologyPectate lyaseprotein–protein interaction networkprotein-protein interaction networkBiotechnologyFrontiers in Plant Science
researchProduct

Neuronal Cytoskeleton in Intellectual Disability: From Systems Biology and Modeling to Therapeutic Opportunities

2021

Intellectual disability (ID) is a pathological condition characterized by limited intellectual functioning and adaptive behaviors. It affects 1–3% of the worldwide population, and no pharmacological therapies are currently available. More than 1000 genes have been found mutated in ID patients pointing out that, despite the common phenotype, the genetic bases are highly heterogeneous and apparently unrelated. Bibliomic analysis reveals that ID genes converge onto a few biological modules, including cytoskeleton dynamics, whose regulation depends on Rho GTPases transduction. Genetic variants exert their effects at different levels in a hierarchical arrangement, starting from the molecular lev…

0301 basic medicineactin cytoskeletonReview0302 clinical medicineBorderline intellectual functioningIntellectual disabilityDisabilità Intellettiva GTPasi CitoscheletroBiology (General)CytoskeletonSpectroscopyNeuronseducation.field_of_studysystems biologyCognitionGeneral MedicinePhenotypeComputer Science ApplicationsChemistryPhenotypeintellectual disabilitySignal TransductionBoolean modelingQH301-705.5NeurogenesisIn silicoSystems biologyPopulationBiologyCatalysismicrotubulesInorganic Chemistry03 medical and health sciencesmedicineAnimalsHumansPhysical and Theoretical ChemistryeducationQD1-999Molecular BiologyGTPase signalingsmall Rho GTPasesOrganic Chemistrypharmacological modulationprotein:protein interaction networkActin cytoskeletonmedicine.disease030104 developmental biologySynapsesneuronal networksNeuroscience030217 neurology & neurosurgery
researchProduct

PINCoC: a Co-Clustering based Method to Analyze Protein-Protein Interaction Networks

2007

Anovel technique to search for functionalmodules in a protein-protein interaction network is presented. The network is represented by the adjacency matrix associated with the undirected graph modelling it. The algorithm introduces the concept of quality of a sub-matrix of the adjacency matrix, and applies a greedy search technique for finding local optimal solutions made of dense submatrices containing the maximum number of ones. An initial random solution, constituted by a single protein, is evolved to search for a locally optimal solution by adding/removing connected proteins that best contribute to improve the quality function. Experimental evaluations carried out on Saccaromyces Cerevis…

BiclusteringMathematical optimizationBioinformatics network analysisCompact spaceInteraction networkBlock matrixFunction (mathematics)Adjacency matrixGreedy algorithmAlgorithmProtein protein interaction networkMathematics
researchProduct

Protein Interaction Networks and Disease: Highlights of the 3rd Challenges in Computational Biology Meeting

2017

Cellular functions are managed by a complex network of protein interactions, the malfunction of which may derive in disease phenotypes. In spite of the incompleteness and noise present in our current protein interaction maps, computational biologists are making strenuous efforts to extract knowledge from these intricate networks and, through their integration with other types of biological data, expedite the development of novel and more effective treatments against human disorders. The 3rd Challenges in Computational Biology meeting revolved around the Protein Interaction Networks and Disease subject, bringing expert network biologists to the city of Mainz, Germany to debate the current st…

Biological dataComputingMethodologies_PATTERNRECOGNITIONWorkflowComputer sciencebusiness.industryProtein Interaction NetworksBig dataCellular functionsGenomicsComputational biologyDiseaseComplex networkbusinessGenomics and Computational Biology
researchProduct

A Coclustering Approach for Mining Large Protein-Protein Interaction Networks

2012

Several approaches have been presented in the literature to cluster Protein-Protein Interaction (PPI) networks. They can be grouped in two main categories: those allowing a protein to participate in different clusters and those generating only nonoverlapping clusters. In both cases, a challenging task is to find a suitable compromise between the biological relevance of the results and a comprehensive coverage of the analyzed networks. Indeed, methods returning high accurate results are often able to cover only small parts of the input PPI network, especially when low-characterized networks are considered. We present a coclustering-based technique able to generate both overlapping and nonove…

Biologycomputer.software_genreBioinformatics network analysis co-clusteringTask (project management)Set (abstract data type)Protein Interaction MappingGeneticsCluster (physics)Cluster AnalysisHumansRelevance (information retrieval)Protein Interaction MapsCluster analysisStructure (mathematical logic)Applied MathematicsProteinsprotein-protein interaction networksbiological networksComputingMethodologies_PATTERNRECOGNITIONCover (topology)Co-clusteringData miningcomputerAlgorithmsBiological networkBiotechnologyIEEE/ACM Transactions on Computational Biology and Bioinformatics
researchProduct

Study of the role of the CDC48 chaperone protein in plant immunity

2018

The chaperone protein CDC48 (Cell division cycle 48) is a major regulator of the quality control of proteins and is involved in various cellular processes in animals and yeast. In contrast, the role of CDC48 in plants is poorly known. In the present work, we investigated the function of CDC48 in plant immunity thanks to the cryptogein/tobacco biological model, cryptogein being produced by the oomycete phytophthora cryptogea.Three strategies were carried out. First, the dynamic of accumulation CDC48 together with intracellular events inherent to the immune response were analyzed in both wild-type and CDC48 overexpressing tobacco cells (CDC48-TAP line). Second, a list if CDC48 partners was es…

Cdc48Protein-Protein interaction networkImmunité des plantes[SDV.SA] Life Sciences [q-bio]/Agricultural sciencesPlant immunityRéseau d'interaction protéine-ProtéineBiochimieBiochemistryCapx
researchProduct

Etude du rôle de la protéine CDC48 dans l'immunité des plantes

2018

The chaperone protein CDC48 (Cell division cycle 48) is a major regulator of the quality control of proteins and is involved in various cellular processes in animals and yeast. In contrast, the role of CDC48 in plants is poorly known. In the present work, we investigated the function of CDC48 in plant immunity thanks to the cryptogein/tobacco biological model, cryptogein being produced by the oomycete phytophthora cryptogea.Three strategies were carried out. First, the dynamic of accumulation CDC48 together with intracellular events inherent to the immune response were analyzed in both wild-type and CDC48 overexpressing tobacco cells (CDC48-TAP line). Second, a list if CDC48 partners was es…

Cdc48[SDV.SA]Life Sciences [q-bio]/Agricultural sciencesProtein-Protein interaction networkImmunité des plantesPlant immunityRéseau d'interaction protéine-ProtéineBiochimieBiochemistryCapx
researchProduct