2023
Scalable and Privacy-Preserving Federated Principal Component Analysis
Froelicher D, Cho H, Edupalli M, Sousa J, Bossuat J, Pyrgelis A, Troncoso-Pastoriza J, Berger B, Hubaux J. Scalable and Privacy-Preserving Federated Principal Component Analysis. 2016 IEEE Symposium On Security And Privacy (SP) 2023, 00: 1908-1925. PMID: 38665901, PMCID: PMC11044025, DOI: 10.1109/sp46215.2023.10179350.Peer-Reviewed Original ResearchHomomorphic encryptionData providersMultiparty homomorphic encryptionPrivacy-preserving alternativeMultiple data providersSecure multiparty computationPassive adversary modelData science domainCleartext dataData confidentialityPrivate dataMultiparty computationSecure systemsInteractive protocolDataset dimensionsEssential algorithmsCentralized solutionData distributionScience domainLocal analysis resultsDimensionality reductionIntermediate resultsEncryptionPrincipal component analysisOriginal data
2016
Compact Integration of Multi-Network Topology for Functional Analysis of Genes
Cho H, Berger B, Peng J. Compact Integration of Multi-Network Topology for Functional Analysis of Genes. Cell Systems 2016, 3: 540-548.e5. PMID: 27889536, PMCID: PMC5225290, DOI: 10.1016/j.cels.2016.10.017.Peer-Reviewed Original ResearchMultiple heterogeneous networksBiological network dataLow-dimensional vectorsProtein function predictionMashup frameworkShelf machineArt performanceHeterogeneous networksNetwork dataScience domainMashupsIndividual networksInference tasksTopological landscapeNetwork integrationInteraction predictionNetworkFunction predictionUnsolved challengeMore accurate inferencesPresent toolsAccurate inferenceFunctional interaction networkTopological contextTopological patterns