메뉴 건너뛰기




Volumn 38, Issue 4, 2014, Pages 275-280

The ENCODE project and perspectives on pathways

Author keywords

ENCODE; Evolutionary computing; Machine learning; Pathway analysis

Indexed keywords

DNA SEQUENCE; GENE LINKAGE DISEQUILIBRIUM; GENETIC ALGORITHM; GENETIC TRAIT; HUMAN; HUMAN GENOME PROJECT; MACHINE LEARNING; METABOLISM; MOLECULAR EVOLUTION; REVIEW; RNA SEQUENCE; SINGLE NUCLEOTIDE POLYMORPHISM;

EID: 84898681891     PISSN: 07410395     EISSN: 10982272     Source Type: Journal    
DOI: 10.1002/gepi.21802     Document Type: Review
Times cited : (52)

References (65)
  • 1
    • 79851468862 scopus 로고    scopus 로고
    • Synthetic associations are unlikely to account for many common disease genome-wide association signals
    • Anderson CA, Soranzo N, Zeggini E, Barrett JC. 2011. Synthetic associations are unlikely to account for many common disease genome-wide association signals. PLoS Biol 9(1):e1000580.
    • (2011) PLoS Biol , vol.9 , Issue.1
    • Anderson, C.A.1    Soranzo, N.2    Zeggini, E.3    Barrett, J.C.4
  • 3
    • 84865856641 scopus 로고    scopus 로고
    • Sequence and chromatin determinants of cell-type-specific transcription factor binding
    • Arvey A, Agius P, Noble WS, Leslie C. 2012. Sequence and chromatin determinants of cell-type-specific transcription factor binding. Genome Res 22(9):1723-1734.
    • (2012) Genome Res , vol.22 , Issue.9 , pp. 1723-1734
    • Arvey, A.1    Agius, P.2    Noble, W.S.3    Leslie, C.4
  • 6
    • 0003479517 scopus 로고    scopus 로고
    • Genetic Programming: An Introduction on the Automatic Evolution of Computer Programs and its Applications
    • San Francisco, CA: Morgan Kaufmann.
    • Banzhaf W, Nordin P, Keller RE, Francone FD. 1997. Genetic Programming: An Introduction on the Automatic Evolution of Computer Programs and its Applications. San Francisco, CA: Morgan Kaufmann.
    • (1997)
    • Banzhaf, W.1    Nordin, P.2    Keller, R.E.3    Francone, F.D.4
  • 10
    • 0028931857 scopus 로고
    • Multiple significance tests: the Bonferroni method
    • Bland JM, Altman DG. 1995. Multiple significance tests: the Bonferroni method. BMJ 310(6973):170.
    • (1995) BMJ , vol.310 , Issue.6973 , pp. 170
    • Bland, J.M.1    Altman, D.G.2
  • 13
    • 84864402194 scopus 로고    scopus 로고
    • Leveraging models of cell regulation and GWAS data in integrative network-based association studies
    • Califano A, Butte AJ, Friend S, Ideker T, Schadt E. 2012. Leveraging models of cell regulation and GWAS data in integrative network-based association studies. Nat Genet 44(8):841-847.
    • (2012) Nat Genet , vol.44 , Issue.8 , pp. 841-847
    • Califano, A.1    Butte, A.J.2    Friend, S.3    Ideker, T.4    Schadt, E.5
  • 15
    • 84865790047 scopus 로고    scopus 로고
    • An integrated encyclopedia of DNA elements in the human genome
    • ENCODE Project Consortium
    • ENCODE Project Consortium. 2012. An integrated encyclopedia of DNA elements in the human genome. Nature 489(7414):57-74.
    • (2012) Nature , vol.489 , Issue.7414 , pp. 57-74
  • 19
    • 0032594950 scopus 로고    scopus 로고
    • Support vector machines for spam categorization
    • Drucker H, Wu D, Vapnik VN. 1999. Support vector machines for spam categorization. IEEE Trans Neural Netw 10(5):1048-1054.
    • (1999) IEEE Trans Neural Netw , vol.10 , Issue.5 , pp. 1048-1054
    • Drucker, H.1    Wu, D.2    Vapnik, V.N.3
  • 22
  • 26
    • 80052406926 scopus 로고    scopus 로고
    • Building sparse support vector machines for multi-instance classification
    • European Conference on. Berlin, Germany: Springer.
    • Fu Z, Lu G, Ting K, Zhang D. 2011. Building sparse support vector machines for multi-instance classification. European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2011). Berlin, Germany: Springer, pp. 471-486.
    • (2011) Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2011) , pp. 471-486
    • Fu, Z.1    Lu, G.2    Ting, K.3    Zhang, D.4
  • 27
    • 2942582468 scopus 로고    scopus 로고
    • Defining transcriptional networks through integrative modeling of mRNA expression and transcription factor binding data
    • Gao F, Foat BC, Bussemaker HJ. 2004. Defining transcriptional networks through integrative modeling of mRNA expression and transcription factor binding data. BMC Bioinform 5(1):31.
    • (2004) BMC Bioinform , vol.5 , Issue.1 , pp. 31
    • Gao, F.1    Foat, B.C.2    Bussemaker, H.J.3
  • 28
    • 33749319347 scopus 로고    scopus 로고
    • Interestingness measures for data mining: a survey
    • Geng L, Hamilton HJ. 2006. Interestingness measures for data mining: a survey. ACM Comput Surv (CSUR) 38(3):9.
    • (2006) ACM Comput Surv (CSUR) , vol.38 , Issue.3 , pp. 9
    • Geng, L.1    Hamilton, H.J.2
  • 29
    • 80052213499 scopus 로고    scopus 로고
    • Multiple kernel learning algorithms
    • Gönen M, Alpaydin E. 2011. Multiple kernel learning algorithms. J Mach Learn Res 12:2211-2268.
    • (2011) J Mach Learn Res , vol.12 , pp. 2211-2268
    • Gönen, M.1    Alpaydin, E.2
  • 30
    • 18144425478 scopus 로고    scopus 로고
    • A genome-wide scalable SNP genotyping assay using microarray technology
    • Gunderson KL, Steemers FJ, Lee G, Mendoza LG, Chee MS. 2005. A genome-wide scalable SNP genotyping assay using microarray technology. Nat Genet 37(5):549-554.
    • (2005) Nat Genet , vol.37 , Issue.5 , pp. 549-554
    • Gunderson, K.L.1    Steemers, F.J.2    Lee, G.3    Mendoza, L.G.4    Chee, M.S.5
  • 31
    • 84857646961 scopus 로고    scopus 로고
    • Weighted kernel Fisher discriminant (wKFD) analysis for integrating heterogeneous data
    • Hamid JS, Greenwood CMT, Beyene J. 2011. Weighted kernel Fisher discriminant (wKFD) analysis for integrating heterogeneous data. Comput Stat Data Anal 56:2031-2040.
    • (2011) Comput Stat Data Anal , vol.56 , pp. 2031-2040
    • Hamid, J.S.1    Greenwood, C.M.T.2    Beyene, J.3
  • 33
    • 0032415865 scopus 로고    scopus 로고
    • How to interpret an anonymous bacterial genome: machine learning approach to gene identification
    • Hayes WS, Borodovsky M. 1998. How to interpret an anonymous bacterial genome: machine learning approach to gene identification. Genome Res 8(11):1154-1171.
    • (1998) Genome Res , vol.8 , Issue.11 , pp. 1154-1171
    • Hayes, W.S.1    Borodovsky, M.2
  • 35
    • 0000107975 scopus 로고
    • Relations between two sets of variates
    • Hotelling H. 1936. Relations between two sets of variates. Biometrika 28(3/4):321-377.
    • (1936) Biometrika , vol.28 , Issue.3-4 , pp. 321-377
    • Hotelling, H.1
  • 37
    • 47049111900 scopus 로고    scopus 로고
    • Learning Context-Specific Gene Regulatory Networks via In-Silico Conditioning. In Genomic Signal Processing and Statistics, 2007 (GENSIPS 2007). IEEE International Workshop on. IEEE.
    • Kim S, Roy I, Raghavan S, Dougherty ER, Bittner M. 2007. Learning Context-Specific Gene Regulatory Networks via In-Silico Conditioning. In Genomic Signal Processing and Statistics, 2007 (GENSIPS 2007). IEEE International Workshop on (pp. 1-4). IEEE.
    • (2007) , pp. 1-4
    • Kim, S.1    Roy, I.2    Raghavan, S.3    Dougherty, E.R.4    Bittner, M.5
  • 38
    • 33745727034 scopus 로고    scopus 로고
    • Multi-objective optimization using genetic algorithms: a tutorial
    • Konak A, Coit DW, Smith AE. 2006. Multi-objective optimization using genetic algorithms: a tutorial. Reliab Eng Syst Safe 91(9):992-1007.
    • (2006) Reliab Eng Syst Safe , vol.91 , Issue.9 , pp. 992-1007
    • Konak, A.1    Coit, D.W.2    Smith, A.E.3
  • 40
    • 43449088832 scopus 로고    scopus 로고
    • A modular approach for integrative analysis of large-scale gene-expression and drug-response data
    • Kutalik Z, Beckmann JS, Bergmann S. 2008. A modular approach for integrative analysis of large-scale gene-expression and drug-response data. Nat Biotech 26(5):531-539.
    • (2008) Nat Biotech , vol.26 , Issue.5 , pp. 531-539
    • Kutalik, Z.1    Beckmann, J.S.2    Bergmann, S.3
  • 42
    • 84867283138 scopus 로고    scopus 로고
    • Identifying multi-layer gene regulatory modules from multi-dimensional genomic data
    • Li W, Zhang S, Liu C-C, Zhou XJ. 2012. Identifying multi-layer gene regulatory modules from multi-dimensional genomic data. Bioinformatics 28(19):2458-2466.
    • (2012) Bioinformatics , vol.28 , Issue.19 , pp. 2458-2466
    • Li, W.1    Zhang, S.2    Liu, C.-C.3    Zhou, X.J.4
  • 43
    • 79956373394 scopus 로고    scopus 로고
    • Systems Biology for Identifying Liver Toxicity Pathways
    • London, UK: BioMed Central Ltd.
    • Li Z, Chan C. 2009. Systems Biology for Identifying Liver Toxicity Pathways. In BMC Proceedings (Vol. 3, No. Suppl 2, p. S2). London, UK: BioMed Central Ltd.
    • (2009) BMC Proceedings , vol.3 , Issue.SUPPL 2
    • Li, Z.1    Chan, C.2
  • 44
    • 80455125871 scopus 로고    scopus 로고
    • Time to recurrence and survival in serous ovarian tumors predicted from integrated genomic profiles
    • Mankoo PK, Shen R, Schultz N, Levine DA, Sander C. 2011. Time to recurrence and survival in serous ovarian tumors predicted from integrated genomic profiles. PLoS ONE 6(11):e24709.
    • (2011) PLoS ONE , vol.6 , Issue.11
    • Mankoo, P.K.1    Shen, R.2    Schultz, N.3    Levine, D.A.4    Sander, C.5
  • 45
    • 72749098014 scopus 로고    scopus 로고
    • Does complexity matter? Artificial evolution, computational evolution and the genetic analysis of epistasis in common human diseases
    • Berlin, Germany: Springer
    • Moore JH, Greene CS, Andrews PC, White BC. 2009. Does complexity matter? Artificial evolution, computational evolution and the genetic analysis of epistasis in common human diseases. Genetic Programming Theory and Practice VI. Berlin, Germany: Springer, pp. 1-19.
    • (2009) Genetic Programming Theory and Practice VI , pp. 1-19
    • Moore, J.H.1    Greene, C.S.2    Andrews, P.C.3    White, B.C.4
  • 46
    • 77949497074 scopus 로고    scopus 로고
    • Bioinformatics challenges for genome-wide association studies
    • Moore JH, Asselbergs FW, Williams SM. 2010. Bioinformatics challenges for genome-wide association studies. Bioinformatics 26(4):445-455.
    • (2010) Bioinformatics , vol.26 , Issue.4 , pp. 445-455
    • Moore, J.H.1    Asselbergs, F.W.2    Williams, S.M.3
  • 47
    • 84898683617 scopus 로고    scopus 로고
    • Genetic analysis of prostate cancer using computational evolution, Pareto-optimization and post-processing
    • Berlin, Germany: Springer
    • Moore JH, Hill DP, Sulovari A. 2013. Genetic analysis of prostate cancer using computational evolution, Pareto-optimization and post-processing. Genetic Programming Theory and Practice X. Berlin, Germany: Springer, pp. 87-101.
    • (2013) Genetic Programming Theory and Practice X , pp. 87-101
    • Moore, J.H.1    Hill, D.P.2    Sulovari, A.3
  • 49
    • 0029492588 scopus 로고
    • Evolutionary Computation, 1995, IEEE International Conference on. IEEE.
    • Murata T, Ishibuchi H. 1995. MOGA: Multi-Objective Genetic Algorithms. Evolutionary Computation, 1995, IEEE International Conference on (Vol. 1, p. 289). IEEE.
    • (1995) MOGA: Multi-Objective Genetic Algorithms , vol.1 , pp. 289
    • Murata, T.1    Ishibuchi, H.2
  • 50
    • 84898676928 scopus 로고    scopus 로고
    • Sensible initialization of a computational evolution system using expert knowledge for epistasis analysis in human genetics
    • Berlin, Germany: Springer.
    • Payne JL, Greene CS, Hill DP, Moore JH. 2010. Sensible initialization of a computational evolution system using expert knowledge for epistasis analysis in human genetics. Exploitation of Linkage Learning in Evolutionary Algorithms. Berlin, Germany: Springer, pp. 215-226.
    • (2010) Exploitation of Linkage Learning in Evolutionary Algorithms , pp. 215-226
    • Payne, J.L.1    Greene, C.S.2    Hill, D.P.3    Moore, J.H.4
  • 51
    • 84859914496 scopus 로고    scopus 로고
    • The genetics of coronary artery disease
    • Roberts R, Stewart AF. 2012. The genetics of coronary artery disease. Curr Opin Cardiol 27(3):221-227.
    • (2012) Curr Opin Cardiol , vol.27 , Issue.3 , pp. 221-227
    • Roberts, R.1    Stewart, A.F.2
  • 53
    • 84865777825 scopus 로고    scopus 로고
    • Linking disease associations with regulatory information in the human genome
    • Schaub MA, Boyle AP, Kundaje A, Batzoglou S, Snyder M. 2012. Linking disease associations with regulatory information in the human genome. Genome Res 22(9):1748-1759.
    • (2012) Genome Res , vol.22 , Issue.9 , pp. 1748-1759
    • Schaub, M.A.1    Boyle, A.P.2    Kundaje, A.3    Batzoglou, S.4    Snyder, M.5
  • 57
    • 84866731350 scopus 로고    scopus 로고
    • Integration of biological networks and pathways with genetic association studies
    • Sun YV. 2012. Integration of biological networks and pathways with genetic association studies. Hum Genet 131(10):1677-1686.
    • (2012) Hum Genet , vol.131 , Issue.10 , pp. 1677-1686
    • Sun, Y.V.1
  • 61
    • 0030085393 scopus 로고    scopus 로고
    • Multicriteria optimization using a genetic algorithm for determining a Pareto set
    • Vlennet R, Fonteix C, Marc I. 1996. Multicriteria optimization using a genetic algorithm for determining a Pareto set. Int J Syst Sci 27(2):255-260.
    • (1996) Int J Syst Sci , vol.27 , Issue.2 , pp. 255-260
    • Vlennet, R.1    Fonteix, C.2    Marc, I.3
  • 62
    • 68249115586 scopus 로고    scopus 로고
    • Extensions of sparse canonical correlation analysis with applications to genomic data
    • Witten DM, Tibshirani RJ. 2009. Extensions of sparse canonical correlation analysis with applications to genomic data. Stat Appl Genet Mol Biol 8(1):1-27.
    • (2009) Stat Appl Genet Mol Biol , vol.8 , Issue.1 , pp. 1-27
    • Witten, D.M.1    Tibshirani, R.J.2
  • 63
    • 62549137441 scopus 로고    scopus 로고
    • CNV discovery using SNP genotyping arrays
    • Yau C, Holmes C. 2008. CNV discovery using SNP genotyping arrays. Cytogenet Genome Res 123(1-4):307-312.
    • (2008) Cytogenet Genome Res , vol.123 , Issue.1-4 , pp. 307-312
    • Yau, C.1    Holmes, C.2
  • 64
    • 84865754452 scopus 로고    scopus 로고
    • Classification of human genomic regions based on experimentally determined binding sites of more than 100 transcription-related factors
    • Yip K, Cheng C, Bhardwaj N, Brown J, Leng J, Kundaje A, Rozowsky J, Birney E, Bickel P, Snyder M and others. 2012. Classification of human genomic regions based on experimentally determined binding sites of more than 100 transcription-related factors. Genome Biol 13(9):R48.
    • (2012) Genome Biol , vol.13 , Issue.9
    • Yip, K.1    Cheng, C.2    Bhardwaj, N.3    Brown, J.4    Leng, J.5    Kundaje, A.6    Rozowsky, J.7    Birney, E.8    Bickel, P.9    Snyder, M.10


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.