{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,4,8]],"date-time":"2024-04-08T21:10:19Z","timestamp":1712610619282},"reference-count":15,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2010,6,15]],"date-time":"2010-06-15T00:00:00Z","timestamp":1276560000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Comput Stat"],"published-print":{"date-parts":[[2011,6]]},"DOI":"10.1007\/s00180-010-0201-9","type":"journal-article","created":{"date-parts":[[2010,6,14]],"date-time":"2010-06-14T09:45:11Z","timestamp":1276508711000},"page":"199-218","source":"Crossref","is-referenced-by-count":8,"title":["Modelling non-stationary dynamic gene regulatory processes with the BGM model"],"prefix":"10.1007","volume":"26","author":[{"given":"Marco","family":"Grzegorczyk","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dirk","family":"Husmeier","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"J\u00f6rg","family":"Rahnenf\u00fchrer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2010,6,15]]},"reference":[{"issue":"3","key":"201_CR1","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1093\/bioinformatics\/bti014","volume":"21","author":"M Beal","year":"2005","unstructured":"Beal M, Falciani F, Ghahramani Z, Rangel C, Wild D (2005) A Bayesian approach to reconstructing genetic regulatory networks with hidden factors. Bioinformatics 21(3): 349\u2013356","journal-title":"Bioinformatics"},{"key":"201_CR2","doi-asserted-by":"crossref","first-page":"1415","DOI":"10.1126\/science.8197455","volume":"264","author":"J Darnell","year":"1994","unstructured":"Darnell J, Kerr I, Stark G (1994) Jak-STAT pathways and transcriptional activation in response to IFNs and other extracellular signaling proteins. Science 264: 1415\u20131421","journal-title":"Science"},{"key":"201_CR3","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1023\/A:1020249912095","volume":"50","author":"N Friedman","year":"2003","unstructured":"Friedman N, Koller D (2003) Being Bayesian about network structure. Mach Learn 50: 95\u2013126","journal-title":"Mach Learn"},{"key":"201_CR4","doi-asserted-by":"crossref","unstructured":"Geiger D, Heckerman D (1994) Learning Gaussian networks. Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence, pp 235\u2013243","DOI":"10.1016\/B978-1-55860-332-5.50035-3"},{"key":"201_CR5","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1214\/ss\/1177011136","volume":"7","author":"A Gelman","year":"1992","unstructured":"Gelman A, Rubin D (1992) Inference from iterative simulation using multiple sequences. Stat Sci 7: 457\u2013472","journal-title":"Stat Sci"},{"key":"201_CR6","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1093\/biomet\/82.4.711","volume":"82","author":"P Green","year":"1995","unstructured":"Green P (1995) Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika 82: 711\u2013732","journal-title":"Biometrika"},{"key":"201_CR7","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1007\/s10994-008-5057-7","volume":"71","author":"M Grzegorczyk","year":"2008","unstructured":"Grzegorczyk M, Husmeier D (2008) Improving the structure MCMC sampler for Bayesian networks by introducing a new edge reversal move. Mach Learn 71: 265\u2013305","journal-title":"Mach Learn"},{"key":"201_CR8","doi-asserted-by":"crossref","first-page":"2071","DOI":"10.1093\/bioinformatics\/btn367","volume":"24","author":"M Grzegorczyk","year":"2008","unstructured":"Grzegorczyk M, Husmeier D, Edwards K, Ghazal P, Millar A (2008) Modelling non-stationary gene regulatory processes with a non-homogeneous Bayesian network and the allocation sampler. Bioinformatics 24: 2071\u20132078","journal-title":"Bioinformatics"},{"key":"201_CR9","first-page":"301","volume-title":"Learning in graphical models, adaptive computation and machine learning","author":"D Heckerman","year":"1999","unstructured":"Heckerman D (1999) A tutorial on learning with Bayesian networks. In: Jordan MI (eds) Learning in graphical models, adaptive computation and machine learning. MIT Press, Cambridge, Massachusetts, pp 301\u2013354"},{"key":"201_CR10","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1016\/j.immuni.2006.08.009","volume":"25","author":"K Honda","year":"2006","unstructured":"Honda K, Takaoka A, Taniguchi T. (2006) Type I interferon gene induction by the Interferon regulatory factor family of transcription factors. Immunity 25: 349\u2013360","journal-title":"Immunity"},{"key":"201_CR11","doi-asserted-by":"crossref","first-page":"2271","DOI":"10.1093\/bioinformatics\/btg313","volume":"19","author":"D Husmeier","year":"2003","unstructured":"Husmeier D (2003) Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic Bayesian networks. Bioinformatics 19: 2271\u20132282","journal-title":"Bioinformatics"},{"key":"201_CR12","doi-asserted-by":"crossref","first-page":"215","DOI":"10.2307\/1403615","volume":"63","author":"D Madigan","year":"1995","unstructured":"Madigan D, York J (1995) Bayesian graphical models for discrete data. Int Stat Rev 63: 215\u2013232","journal-title":"Int Stat Rev"},{"key":"201_CR13","doi-asserted-by":"crossref","unstructured":"Raza S, Robertson K, Lacaze P, Page D, Enright A, Ghazal P, Freeman T (2008) A logic based diagram of signalling pathways central to macrophage activation. BMC Systems Biology 2:Article 36","DOI":"10.1186\/1752-0509-2-36"},{"issue":"14","key":"201_CR14","doi-asserted-by":"crossref","first-page":"3131","DOI":"10.1093\/bioinformatics\/bti487","volume":"21","author":"S Rogers","year":"2005","unstructured":"Rogers S, Girolami M (2005) A Bayesian regression approach to the inference of regulatory networks from gene expression data. Bioinformatics 21(14): 3131\u20133137","journal-title":"Bioinformatics"},{"key":"201_CR15","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1126\/science.1105809","volume":"308","author":"K Sachs","year":"2005","unstructured":"Sachs K, Perez O, Pe\u2018er DA, Lauffenburger DA, Nolan GP (2005) Protein-signaling networks derived from multiparameter single-cell data. Science 308: 523\u2013529","journal-title":"Science"}],"container-title":["Computational Statistics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00180-010-0201-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00180-010-0201-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00180-010-0201-9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,30]],"date-time":"2019-05-30T03:04:24Z","timestamp":1559185464000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00180-010-0201-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,6,15]]},"references-count":15,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2011,6]]}},"alternative-id":["201"],"URL":"https:\/\/doi.org\/10.1007\/s00180-010-0201-9","relation":{},"ISSN":["0943-4062","1613-9658"],"issn-type":[{"value":"0943-4062","type":"print"},{"value":"1613-9658","type":"electronic"}],"subject":[],"published":{"date-parts":[[2010,6,15]]}}}