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Volumn 17, Issue 2-3, 2009, Pages 163-175

The possibility of Integrative Causal Analysis: Learning from different datasets and studies

Author keywords

[No Author keywords available]

Indexed keywords

CAUSAL ANALYSIS; CAUSAL MODEL; CAUSAL RELATIONS; DATA ANALYSIS; DATA SETS; EXPERIMENTAL CONDITIONS; HUMAN BRAIN; LARGE PARTS; LARGE SCALE INTEGRATION; MACHINE-LEARNING; MULTIPLE GENES; SEMI-AUTOMATED;

EID: 77956700497     PISSN: 14728915     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Conference Paper
Times cited : (1)

References (22)
  • 2
    • 0031189914 scopus 로고    scopus 로고
    • Multitask learning: A knowledge-based source of inductive bias
    • Richard Caruana. Multitask learning: A knowledge-based source of inductive bias. Machine Learning, 28:41-75, 1997.
    • (1997) Machine Learning , vol.28 , pp. 41-75
    • Caruana, R.1
  • 3
    • 0007047929 scopus 로고    scopus 로고
    • Causal discovery from a mixture of experimental and observational data
    • Morgan Kaufmann
    • Gregory F. Cooper and Changwon Yoo. Causal discovery from a mixture of experimental and observational data. In UAI, pages 116-125. Morgan Kaufmann, 1999.
    • (1999) UAI , pp. 116-125
    • Cooper, G.F.1    Yoo, C.2
  • 6
    • 34249761849 scopus 로고    scopus 로고
    • Learning Bayesian networks: The combination of knowledge and statistical data
    • David Heckerman, Dan Geiger, and David M. Chickering. Learning Bayesian networks: The combination of knowledge and statistical data. Machine Learning, 20(3):197-243, 2005.
    • (2005) Machine Learning , vol.20 , Issue.3 , pp. 197-243
    • Heckerman, D.1    Geiger, D.2    Chickering, D.M.3
  • 7
    • 38849106351 scopus 로고    scopus 로고
    • A comparison of metaanalysis methods for detecting differentially expressed genes in microarray experiments
    • Fangxin Hong and Rainer Breitling. A comparison of metaanalysis methods for detecting differentially expressed genes in microarray experiments. Bioinformatics, 24:374-382, 2008.
    • (2008) Bioinformatics , vol.24 , pp. 374-382
    • Hong, F.1    Breitling, R.2
  • 9
    • 41649108328 scopus 로고    scopus 로고
    • An historical perspective on meta-analysis: Dealing quantitatively with varying study results
    • Keith O'Rourke. An historical perspective on meta-analysis: dealing quantitatively with varying study results. Journal of the Royal Society of Medicine, 100(12):579-582, 2007.
    • (2007) Journal of the Royal Society of Medicine , vol.100 , Issue.12 , pp. 579-582
    • O'Rourke, K.1
  • 11
    • 0003806983 scopus 로고
    • London, A. and C. Black, URL, http://www.biodiversitylibrary.org/ bibliography/5733
    • Karl Pearson. The grammar of science,. London, A. and C. Black, 1900. URL http://www.biodiversitylibrary.org/item/26639. http://www.biodiversitylibrary. org/bibliography/5733.
    • (1900) The Grammar of Science
    • Pearson, K.1
  • 12
    • 0036392228 scopus 로고    scopus 로고
    • Ancestral graph markov models
    • Thomas Richardson and Peter Spines, doi: doi: 10.1214/aos/1031689015, URL
    • Thomas Richardson and Peter Spines. Ancestral graph markov models. Annals of Statistics, 30(4):962-1030, 2002. doi: doi: 10.1214/aos/1031689015. URL http://dx.doi.org/doi:10.1214/aos/1031689015.
    • (2002) Annals of Statistics , vol.30 , Issue.4 , pp. 962-1030
  • 13
    • 17644427718 scopus 로고    scopus 로고
    • Causal protein-signaling networks derived from multiparameter single-cell data
    • Karen Sachs, Omar Perez, Dana Pe'er, Douglas A. Lauffenburger, and Garry P. Nolan. Causal protein-signaling networks derived from multiparameter single-cell data. Science, 308:523-529, 2005.
    • (2005) Science , vol.308 , pp. 523-529
    • Sachs, K.1    Perez, O.2    Pe'er, D.3    Lauffenburger, D.A.4    Nolan, G.P.5
  • 14
    • 22844446947 scopus 로고    scopus 로고
    • An integrative genomics approach to infer causal associations between gene expression and disease
    • Eric E. Schadt, John Lamb, Xia Yang, and et. al. An integrative genomics approach to infer causal associations between gene expression and disease. Nature Genetics, 37:710-717, 2005.
    • (2005) Nature Genetics , vol.37 , pp. 710-717
    • Schadt, E.E.1    Lamb, J.2    Yang, X.3
  • 18
    • 85069202966 scopus 로고    scopus 로고
    • Integrating locally learned causal structures with overlapping variables
    • R. E. Tillman, D. Danks, and C. Glymour. Integrating locally learned causal structures with overlapping variables. In NIPS, 2008.
    • (2008) NIPS
    • Tillman, R.E.1    Danks, D.2    Glymour, C.3
  • 19
    • 84862275305 scopus 로고    scopus 로고
    • Sofia Triantafillou, Master's thesis, Computer Science Department, University of Crete
    • Sofia Triantafillou. Learning causal structure from overlapping variable sets. Master's thesis, Computer Science Department, University of Crete, 2010.
    • (2010) Learning Causal Structure from Overlapping Variable Sets
  • 20
    • 33746035971 scopus 로고    scopus 로고
    • The max-min hill-climbing bayesian network structure learning algorithm
    • I. Tsamardinos, L. E. Brown, and C. F. Aliferis. The Max-Min Hill-Climbing Bayesian Network Structure Learning Algorithm. Machine Learning, 65(1):31-78, 2006.
    • (2006) Machine Learning , vol.65 , Issue.1 , pp. 31-78
    • Tsamardinos, I.1    Brown, L.E.2    Aliferis, C.F.3
  • 21
    • 57749169260 scopus 로고    scopus 로고
    • Bounding the false discovery rate in local bayesian network learning
    • Ioannis Tsamardinos and Laura E. Brown, In
    • Ioannis Tsamardinos and Laura E. Brown. Bounding the false discovery rate in local bayesian network learning. In AAAI, pages 1100-1105, 2008.
    • (2008) AAAI , pp. 1100-1105


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.