This paper aims to find a practical way of quantitatively representing the privacy of network data. A method of quantifying the privacy of network data anonymization based on similarity distance and entropy in the sce...This paper aims to find a practical way of quantitatively representing the privacy of network data. A method of quantifying the privacy of network data anonymization based on similarity distance and entropy in the scenario involving multiparty network data sharing with Trusted Third Party (TTP) is proposed. Simulations are then conducted using network data from different sources, and show that the measurement indicators defined in this paper can adequately quantify the privacy of the network. In particular, it can indicate the effect of the auxiliary information of the adversary on privacy.展开更多
Gao, Volny and Wang （2010） gave a simple criterion for signature-based algorithms to compute GrSbner bases. It gives a unified frame work for computing GrSbner bases for both ideals and syzygies, the latter is very ...Gao, Volny and Wang （2010） gave a simple criterion for signature-based algorithms to compute GrSbner bases. It gives a unified frame work for computing GrSbner bases for both ideals and syzygies, the latter is very important in free resolutions in homological algebra. Sun and Wang （2011） later generalized the GVW criterion to a more general situation （to include the F5 Algorithm）. Signature-based algorithms have become increasingly popular for computing GrSbner bases. The current paper introduces a concept of factor pairs that can be used to detect more useless J-pairs than the generalized GVW criterion, thus improving signature-based algorithms.展开更多
Microarray and deep sequencing technologies have provided unprecedented opportunities for mapping genome mutations,RNA transcripts,transcription factor binding,and histone modifications at high resolution at the genom...Microarray and deep sequencing technologies have provided unprecedented opportunities for mapping genome mutations,RNA transcripts,transcription factor binding,and histone modifications at high resolution at the genome-wide level.This has revolutionized the way in which transcriptomes,regulatory networks and epigenetic regulations have been studied and large amounts of heterogeneous data have been generated.Although efforts are being made to integrate these datasets unbiasedly and efficiently,how best to do this still remains a challenge.Here we review major impacts of high-throughput genome-wide data generation,their relevance to human diseases,and various bioinformatics approaches for data integration.Finally,we provide a case study on inflammatory diseases.展开更多
基金supported by the National Key Basic Research Program of China (973 Program) under Grant No. 2009CB320505the Fundamental Research Funds for the Central Universities under Grant No. 2011RC0508+2 种基金the National Natural Science Foundation of China under Grant No. 61003282China Next Generation Internet Project "Research and Trial on Evolving Next Generation Network Intelligence Capability Enhancement"the National Science and Technology Major Project "Research about Architecture of Mobile Internet" under Grant No. 2011ZX03002-001-01
文摘This paper aims to find a practical way of quantitatively representing the privacy of network data. A method of quantifying the privacy of network data anonymization based on similarity distance and entropy in the scenario involving multiparty network data sharing with Trusted Third Party (TTP) is proposed. Simulations are then conducted using network data from different sources, and show that the measurement indicators defined in this paper can adequately quantify the privacy of the network. In particular, it can indicate the effect of the auxiliary information of the adversary on privacy.
基金supported by the National Natural Science Foundation of China under Grant Nos.11471108,11426101Hunan Provincial Natural Science Foundation of China under Grant Nos.14JJ6027,2015JJ2051Fundamental Research Funds for the Central Universities of Central South University under Grant No.2013zzts008
文摘Gao, Volny and Wang （2010） gave a simple criterion for signature-based algorithms to compute GrSbner bases. It gives a unified frame work for computing GrSbner bases for both ideals and syzygies, the latter is very important in free resolutions in homological algebra. Sun and Wang （2011） later generalized the GVW criterion to a more general situation （to include the F5 Algorithm）. Signature-based algorithms have become increasingly popular for computing GrSbner bases. The current paper introduces a concept of factor pairs that can be used to detect more useless J-pairs than the generalized GVW criterion, thus improving signature-based algorithms.
文摘Microarray and deep sequencing technologies have provided unprecedented opportunities for mapping genome mutations,RNA transcripts,transcription factor binding,and histone modifications at high resolution at the genome-wide level.This has revolutionized the way in which transcriptomes,regulatory networks and epigenetic regulations have been studied and large amounts of heterogeneous data have been generated.Although efforts are being made to integrate these datasets unbiasedly and efficiently,how best to do this still remains a challenge.Here we review major impacts of high-throughput genome-wide data generation,their relevance to human diseases,and various bioinformatics approaches for data integration.Finally,we provide a case study on inflammatory diseases.
