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P. Sykacek, R. Clarkson, C. Print, R. Furlong and G. Micklem.
Bayesian Modeling of Shared Gene Function. In Bioinformatics,
2007; doi: 10.1093/bioinformatics/btm280, pp 1936--1944. An
abstract and a
pdf preprint are available from Bioinformatics online,
a local draft version is draft available in
gzipped postscript and
pdf.
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L. Anderson, R. M. Burnstein, X. He, R. Luce, R. Furlong, T. Foltynie, P. Sykacek, D. K.
Menon and Maeve A. Caldwell.
Gene expression changes in long term expanded human neural progenitor cells passaged by
chopping leads to loss of neurogenic potential in vivo. In Experimental Neurology,
Volume 204, Issue 2, April 2007, Pages 512-524; doi:10.1016/j.expneurol.2006.12.025.
online version.
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P. Sykacek, R. Furlong and G. Micklem. A Friendly Statistics Package
for Microarray Analysis, In Bioinformatics, 21(21). 4096-4070, 2005.
Drafts available in pdf and as
gzipped postscript. An abstract and a
pdf file are available from Bioinformatics online access.
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P. Sykacek, S. J. Roberts and M. Stokes. Adaptive BCI based
on variational Bayesian Kalman filtering: an empirical evaluation.
In IEEE Trans. Biomedical Engineering, 51(5):719--727, 2004.
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S.N. Mukherjee, P. Sykacek, S.J. Roberts and S.J. Gurr.
Gene Ranking Using Bootstrapped P-values. In
ACM SIGKDD Explorations, Volume 5, Issue 2,
Special Issue on Microarray Data Mining, 2004.
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E. Curran, P. Sykacek, M. Stokes, S. J. Roberts, W. Penny,
I. Johnsrude and A. M. Owen. Cognitive tasks for driving a Brain
Compute Interfacing System. In IEEE Trans. Neural Systems and
Rehabilitation Engineering, 12 (1): 48-57, 2004.
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P. Sykacek, S. J. Roberts, M. Stokes, E. Curran, M. Gibbs
and L. Pickup. Probabilistic methods in BCI research.
In IEEE Trans. Neural Systems and Rehabilitation Engineering,
pp. 192--195, 2003.
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P. Sykacek, G. Dorffner, P. Rappelsberger and J. Zeitlhofer.
Improving biosignal processing through modelling uncertainty: Bayes
vs. non-Bayes in sleep staging. Applied Artificial Intelligence,
16(5):395-421,2002.
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A. Flexer, G. Dorffner, P. Sykacek, I. Rezek.
An automatic, continuous and probabilistic sleep stager
based on a hidden Markov model.
Applied Artificial Intelligence, 16(3):199-207,2002.
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Rappelsberger P., Trenker E., Rothman C., Gruber G., Sykacek P., Roberts S.,
Klösch G., Zeitlhofer J., Anderer P., Saletu B., Schlögl A., Värri A., Kemp B.,
Penzel T., Herrmann WM., Hasan J., Barbanoj MJ., Kunz D., Dorffner G.
Das Projekt SIESTA. in Klinische Neurophysiologie,32(2):
pages 76-88, 2001. (in German).
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I. Rezek, P. Sykacek and S. Roberts.
Learning interaction dynamics with coupled hidden Markov models.
in IEE special issue proceedings science measurement and
technology, Vol. 147(5), pages 345-350, 2000.
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P. Sykacek, I. Rezek and S. J. Roberts. Bayes Consistent
Classification of EEG Data by Approximate Marginalisation.
In D. Husmeier and R. Dybowski and S. J. Roberts editors. Probabilistic
Modeling in Bioinformatics and Medical Informatics,
pages 391--416, Springer Verlag, London, 2004.
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P. Sykacek and S. J. Roberts.
Adaptive classification by variational Kalman filtering.
In S.Thrun, S. Becker and K. Obermayer, editors, Advances
in Neural Information Processing Systems 15, pp 737-744,
MIT press, 2003. draft available in
pdf or
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I. Rezek, S. J. Roberts and P. Sykacek,(2003).
Ensemble Coupled Hidden Markov Models for Joint
Characterisation of Dynamic Signals. Ninth International
Workshop on Artificial Intelligence and Statistics 2003.
draft available in
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P. Sykacek and S. J. Roberts. Bayesian time series classification.
In T. G. Dietterich, S. Becker and Z. Ghahramani, editors,
Advances in Neural Information Processing Systems 14, pages
937-944, MIT press, 2002. draft available in
pdf or
gzipped postscript.
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P. Sykacek, S. J. Roberts, I. Rezek, A. Flexer and G. Dorffner.
A probabilistic approach to high resolution sleep analysis.
In G. Dorffner, K. Hornik and H. Bischof, editors,
Proceedings of the International Conference on Neural
Networks (ICANN), pages 617-624, Springer Verlag, 2001.
draft available in
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G. Dorffner, P. Sykacek and C. Schittenkopf. Modelling Uncertainty
in Biomedical Applications of Neural Networks. in Proceedings of
Artificial Neural Networks in Medicine and Biology 1, Göteborg,
Sweden, pages 18-26, Springer Verlag, 2000.
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A. Flexer, P. Sykacek, I. Rezek and G. Dorffner.
Using hidden Markov models to build an automatic,
continuous and probabilistic stager, in S. I. Amari et al.,
Proceedings of the IEEE-INNS-ENNS International Joint
Conference on Neural Networks, IJCNN 2000, Como Italy,
IEEE Computer Society, Vol. III, 627-631, 2000.
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I. Rezek, P. Sykacek and S. Roberts.
Coupled hidden Markov models for biosignal interaction modelling.
in Proceedings of Medsip-2000, International Conference on
Advances in Medical Signal and Information Processing,
pages 672-679, 2000.
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- P. Sykacek. On input selection with reversible jump Markov chain
Monte Carlo sampling. in S. A. Solla and T. K. Leen and K. R. Müller
editors, Advances in Neural Information Processing Systems 12,
pages 638-644, MIT press, 2000. draft available in
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gzipped postscript.
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P. Sykacek. Outliers and Bayesian Inference.
in M. Heiss editor, Proceedings of NC 98 Vienna,
pages 973-978, 1998.
wins best presentation award.
draft available in
pdf or
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N. Cristianini, J. Shawe-Taylor and P. Sykacek.
Bayesian Classifiers are Large Margin Hyperplanes in a Hilbert Space.
in Proceedings of the ICML 98, pages 109-117, 1998.
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P. Sykacek, G. Dorffner, P. Rappelsberger and J. Zeitlhofer.
Experiences with Bayesian learning in a real world application.
in M. I. Jordan and M.J. Kearns and S. Solla editors,
Advances in Neural Information Processing Systems 10,
pages 964-970, 1998.
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P. Sykacek. Equivalent error bars for neural network classifiers
trained by Bayesian inference. in Proceedings of the European
Symposium on Artificial Neural Networks (Bruges, 1997), pages
121-126, 1997.
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P. Sykacek, R. Clarkson, C. Print, R. Furlong and G. Micklem.
Bayesian Modeling of Shared Gene Function. Technical report,
Dept. of Biotechnology, BOKU University, Vienna, 2007. available in
pdf and
gzipped postscript.
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P. Sykacek and G. Micklem. Hierarchical Bayesian Modelling
Identifies Shared Gene Function. (biologists version)
presented at the Annual Research at Genetics Meeting,
December 2005, Cambridge UK, talk available in
pdf.
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P. Sykacek and G. Micklem. Hierarchical Bayesian Modelling
Identifies Shared Gene Function. (technical version)
presented at Birbeck College's Bioinformatics Seminar,
November 2005, London UK, talk available in
pdf.
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P. Sykacek. A short FSPMA tutorial. available in
pdf and as
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P. Sykacek. Probabilistic Methods in BCI Research.
presented at Birmingham Universities Computer Science Seminar,
November 2004, Birmingham UK, talk available in
pdf.
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P. Sykacek and R. Clarkson. Probabilistic Modeling for Multi Systems Microarray Experiments.
presented at the BBSRC's Exploiting Genomics Initiative Grant Holder Meeting,
October 2004, Windsor UK, technical part available in
pdf.
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P. Sykacek. Biomedical Applications and the Probabilistic Framework,
presented at David MacKay's Inference Group Seminar, Feb. 2004, Cambridge UK,
available in pdf.
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P. Sykacek. Brain Computer Interfacing: State of the Art, Probabilistic Advances and
Future Perspectives. Technical Report, available in
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P. Sykacek. Towards Adaptive BCI. Presentation
at the NCAF meeting on human computer interaction,
3-4 September 2003, Cambridge, UK.
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P. Sykacek, S. J. Roberts and M. Stokes. Adaptive BCI based
on variational Bayes: an empirical evaluation.
Poster presented and
awarded in the "best engineering" category at the BCI
workshop 2002 in Albany, NY, June 12-17.
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G. Dorffner, P. Sykacek, S. Roberts, A. Schlögl, A. Värri,
P. Rappelsberger, P. Anderer, G. Klösch, B. Saletu, MJ. Barbanoj,
W. Herrmann, S.-L. Himanen, B. Kemp, T. Penzel, J. Röschke.
Continuous sleep processes and subjective sleep quality - first
results from the SIESTA project. in J. Sleep Res Supplement 1.,
page 55, 2000.
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signal processing, PhD. thesis at the Technical University Vienna,
June 2000. available in
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Bayesian wrappers versus conventional filters:
Feature subset selection in the Siesta project.
in Proceedings of the European Medical & Biomedical
Engineering Conference, pages 1652-1653, 1999.
draft available in
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- P. Sykacek, S. J. Roberts, I. Rezek, A. Flexer and G. Dorffner.
Reliability in preprocessing: Bayes rules Siesta.
in Proceedings of the European Medical & Biomedical
Engineering Conference, pages 1656--1657, 1999.
draft available in
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- P. Sykacek, S. J. Roberts, I. Rezek, A. Flexer and G. Dorffner.
Classification in the sampling paradigm: A predictive
approach towards a Siesta sleep analyzer
in Proceedings of the European Medical & Biomedical
Engineering Conference, pages 1660-1661, 1999.
draft available in
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- P. Sykacek., Metalevel learning - is more than model selection necessary?
In Proceedings of the ICML 99 Workshop on Recent Advances in
Meta-Learning and Future Work, pages 66-73, 1999.
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Kemp B, Penzel T, Värri A. O., Sykacek P., Roberts S. J. and Nielsen K. D.
EDF: a simple format for graphical analysis results from polygraphic
SIESTA recordings. in J. Sleep Research 7, suppl. 2, page 132, 1998.
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P. Sykacek, G. Dorffner, O. Filz, P. Rappelsberger and J. Zeitlhofer.
Classification of REM sleep periods with artificial neural networks.
in Proc. of Measurement '97, (Smolenice, 1997), pages 327-333,
1997.
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- P. Sykacek and R. Weissgärber. Parameteroptimierung für Fuzzy Controller.
Konferenzbeitrag Mikroelektronik 1995, ÖVE Schriftenreihe Nr.8,
September 1995. (in German).
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P. Sykacek. Parameteroptimierung für Fuzzy Controller. Diploma Thesis,
ICT TU-Vienna, 1995. (in German).