Browsing by Author "Jurgelenaite, R."

Now showing items 1-16 of 16

FACIL: Fast and Accurate Genetic Code Inference and Logo
Dutilh, B.E. ; Jurgelenaite, R. ; Szklarczyk, R.J. ; Hijum, S.A.F.T. van ; Harhangi, H.R.; Schmid, M.; Wild, B. de; Francoijs, K.J. ; Stunnenberg, H.G. ; Strous, M. ; Jetten, M.S.M. ; Camp, H.J.M. op den ; Huynen, M.A. et al. sine al.
2011, Article / Letter to editor (Bioinformatics, vol. 27, iss. 14, (2011), pp. 1929-1933)
Genome-wide profiling of p63 DNA-binding sites identifies an element that regulates gene expression during limb development in the 7q21 SHFM1 locus.
Kouwenhoven, E.N. ; Heeringen, S.J. van; Tena, J.J.; Oti, M.O. ; Dutilh, B.E. ; Alonso, M.E.; Calle-Mustienes, E. de la; Smeenk, L.; Rinne, T.K. ; Parsaulian, L.; Bolat, E. ; Jurgelenaite, R. ; Huynen, M.A. ; Hoischen, A. ; Veltman, J.A. ; Brunner, H.G. ; Roscioli, T. ; Oates, E.; Wilson, M.; Manzanares, M.; Gomez-Skarmeta, J.L.; Stunnenberg, H.G. ; Lohrum, M.A.E. ; Bokhoven, J.H.L.M. van ; Zhou, Huiqing et al. sine al.
2010, Article / Letter to editor (Plos Genetics, vol. 6, iss. 8, (2010), pp. e1001065)
Gene regulation in the intraerythrocytic cycle of Plasmodium falciparum
Jurgelenaite, R. ; Dijkstra, T.M.H. ; Kocken, C.H.M. ; Heskes, T.M.
2009, Article / Letter to editor (Bioinformatics, vol. 25, iss. 12, (2009), pp. 1484-1491)
Gene regulation in the intraerythrocytic cycle of Plasmodium falciparum.
Jurgelenaite, R. ; Dijkstra, T.M.H. ; Kocken, C.H.M. ; Heskes, T.M.
2009, Article / Letter to editor (Bioinformatics, vol. 25, iss. 12, (2009), pp. 1484-1491)
Symmetric causal independence models
Jurgelenaite, R.
2009, Dissertation
Learning symmetric causal independence models
Jurgelenaite, R. ; Heskes, T.M.
2008, Article / Letter to editor (Machine Learning, vol. 71, iss. 2-3, (2008), pp. 133-153)
Using symmetric causal independence models to predict gene expression from sequence data
Jurgelenaite, R. ; Heskes, T.M. ; Dijkstra, T.
2007, Article in monograph or in proceedings (ECML--PKDD Workshop Data Mining in Functional Genomics and Proteomics: Current Trends and Future Directions, pp. 67-78)
Predicting carcinoid heart disease with the noisy--threshold classifier
Gerven, M.A.J. van ; Jurgelenaite, R. ; Taal, B.G.; Heskes, T.M. ; Lucas, P.J.F.
2007, Article / Letter to editor (Artificial Intelligence in Medicine, vol. 40, iss. 1, (2007), pp. 45-55)
Symmetric Causal Independence Models for Classification
Jurgelenaite, R. ; Heskes, T.M.
2006, Article in monograph or in proceedings (Proceedings of the Third European Workshop on Probabilistic Graphical Models, pp. 163-170)
EM Algorithm for Symmetric Causal Independence Models
Jurgelenaite, R. ; Heskes, T.M.
2006, Article in monograph or in proceedings (Proceedings of the Nineteenth European Conference on Machine Learning, pp. 234-245)
Noisy Threshold Functions for Modelling Causal Independence in Bayesian Networks
Jurgelenaite, R. ; Heskes, T.M. ; Lucas, P.J.F.
2006, External research report
Use of the noisy threshold function in building Bayesian networks
Jurgelenaite, R. ; Lucas, P. ; Heskes, T.
2005, Article in monograph or in proceedings (Verbeeck, K. (ed.), BNAIC 2005: 17th Belgian-Dutch Conference on Artificial Intelligence, Brussels, Belgium, October 17-18, 2005, pp. 158-165)
Exploiting Causal Independence in Large Bayesian Networks
Jurgelenaite, R. ; Lucas, P.J.F.
2005, Article / Letter to editor (Knowledge-Based Systems, vol. 18, iss. 4-5, (2005), pp. 153-162)
Exploring the Noisy Threshold Function in Designing Bayesian Networks
Jurgelenaite, R. ; Lucas, P.J.F. ; Heskes, T.M.
2005, Article in monograph or in proceedings (AI--2005 the Twenty--fifth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, pp. 133-146)
Parameter Estimation in Large Causal Models
Jurgelenaite, R. ; Lucas, P.J.F.
2004, Article in monograph or in proceedings (Proceedings of the 16th ECAI 2004, pp. 1037-1038)
Exploiting Causal Independence in Large Bayesian Networks
Jurgelenaite, R. ; Lucas, P.J.F.
2004, Article in monograph or in proceedings (Bramer, M.A. (ed.), Research and Developments in Intelligent Systems XXI: Proceedings of AI-2004, the twenty-fourth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, pp. 157-170)

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