Personal Information

Name: Péter Antal

Phone: +36-1-463-4394

Office: 1117 Budapest, XI. Magyar tudósok körútja 2. IE423

CV

Courses

Artificial Intelligence (BMEVIMM4025)

 

Bayesian machine learning (BMEVIMM9052)

 

Bioinformatics (BMEVIMM9179)

 

Biomedical informatics (BMEVIMM9179)

 

Artificial Intelligence (CCE spec. 2/1)

 

Decision support systems

 

Intelligent Data Analysis/Advanced Machine Learning

 

 

Publications

Journal papers

P. Antal, G. Fannes, D. Timmerman, Y. Moreau, B. De Moor: Bayesian Applications of Belief Networks and Multilayer Perceptrons for Ovarian Tumor Classification with Rejection, Artificial Intelligence in Medicine, vol. 29, pp 39-60, 2003

P. Antal, G. Fannes, Y. Moreau, D. Timmerman, B. De Moor: Using Literature and Data to Learn Bayesian Networks as Clinical Models of Ovarian Tumors, Artificial Intelligence in Medicine, 2004, vol 30, pp 257-281

Y. Moreau, P. Antal, G. Fannes, B. De Moor: Probabilistic graphical models for computational biomedicine, Methods of Information in Medicine, 2003; 42(2) pp. 161-8.

P. Antal, G. Fannes, Y. Moreau, B. De Moor, J Vandewalle, D. Timmerman: Extended Bayesian regression models: a symbiotic application of Belief Networks and Multilayer Perceptrons for the Classification of Ovarian Tumors, in: AIME 2001. Lecture Notes in Artificial Intelligence 2001, Springer-Verlag, Berlin, 2001, pp 177-187

P. Antal, A. Millinghoffer, G. Hullám: Statisztikai adat- és szövegelemzés Bayes-hálókkal: a valószínűségektől a függetlenségi és oksági viszonyokig, Híradástechnika, 2005, vol. 60, pp 40-49

P. Antal, A. Millinghoffer: Learning Causal Bayesian Networks from Literature Data, Periodica Polytechnica, 2006, vol. 40, no. 3-4, pp 201-221

T. G Szabó, R. Palotai, P. Antal, I. Tokatly, L. Tóthfalusi, O. Lund, Gy. Nagy, A. Falus, E. I. Buzás: Critical role of glycosylation in determining the length and structure of T cell epitopes- As suggested by a combined in silico systems biology approach, Immunome Research, (accepted), IF: 5.33

Semsei A.F, Antal P, Szalai Cs.: Strengths and weaknesses of gene association studies in childhood acute lymphoblastic leukemia, Leuk Res., 2009, in press, doi:10.1016/j.leukres.2009.07.036, IF: 2.39

Sanjeev Srivastava, Péter Antal, Mercédesz Mazán, Mária Pásztói, Ilona Újfalussy, Bernadett Rojkovich, Judit Kelemen, Ildikó Ungvári, Csaba Szalai, Tamás Gáti, Gábor Hullám, György Nagy, András Falus, Edit I Buzás: Combined analysis of two single nucleotide polymorphisms of the glucuronidase gene shows strong association with rheumatoid arthritis, The Journal of Rheumatology (submitted)

S. Srivastava, P. Antal, J. Gál, G. Hullám, A.F. Semsei, G. Nagy, A. Falus, E. I. Buzás: Lack of evidence for association of two functional SNPs of CHI3L1 gene(HC-gp39) with rheumatoid arthritis, Rheumatology International (Clinical and Experimental Investigations), 2010

G. Hullám, P. Antal, Cs. Szalai, A. Falus: Evaluation of a Bayesian model-based approach in GA studies, JMLR Workshop and Conference Proceedings, 2010

 

 

Book chapters

P. Antal, A. Millinghoffer, G. Hullám, G. Hajós, Cs. Szalai, A. Falus: A bioinformatic platform for a Bayesian, multiphased, multilevel analysis in immunogenomics, in Bioinformatics for Immunomics, Ed.: M.N.Davies, S.Ranganathan, D.R.Flower, Springer, 2009

 

Posters

P. Antal, A. Millinghoffer, G. Hullám, Cs. Szalai, A. Falus: BysCyc: A Bayesian Logic for the Integrative Analysis of Knowledge and Data in Genetic Association Studies, The Second International Workshop on Machine Learning in Systems Biology (MLSB08)

G. Hajós, P. Antal, Y. Moreau, Cs. Szalai, A. Falus: Model-based SNP set selection in study design using a multilevel, sequential, Bayesian analysis of earlier data sets, The Second International Workshop on Machine Learning in Systems Biology (MLSB08)

P. Antal, A. Millinghoffer, Cs. Szalai, A. Falus: On the Bayesian applicability of graphical models in genome-wide association studies, (MLSB09)

G. Hajós, P. Antal, Y. Moreau, Cs. Szalai, A. Falus: Variable Pruning in Bayesian Sequential Study Design, (MLSB09)

P. Antal, P. Sárközy, Z.Balázs, P. Kiszel, A. Semsei, Cs. Szalai, A. Falus: Averaging over measurement and haplotype uncertainty using probabilistic genotype data, (MLSB09)

Petra Sz. Kiszel, Ágnes F. Semsei, Ildikó Ungvári, Adrienne Nagy, Márta Széll, Béla Melegh, Péter Kisfali, Péter Antal, Gábor Hullám, András Falus, Csaba Szalai:  Screening for susceptibility genes of asthma on chromosome 11 and 14, Allergy & Asthma Symposium: Bridging Innate and Adaptive Immunity, May 28-29, 2009 Bruges, Belgium

 

Lectures

P.Antal, G. Hajós, G.Hullám, A.Millinghoffer Cs.Szalai and A. Falus: A bioinformatic platform for a model-based, knowledge-rich study design and Bayesian analysis of partial genome screening studies, Magyar Biokémiai Egyesület 2008. évi Vándorgyűlése (Szeged, 2008. augusztus 31-szeptember 03.)

Csaba Szalai, Ágnes F. Semsei, Ildikó Ungvári, Petra Kiszel, Péter Antal, András Falus: Investigation of the genomic background of obesity using single nucleotide polymorphism analysis in candidate genes, 2nd Central European Congress on Obesity, October 1-3, 2009, Budapest, Hungary

P.Antal, G. Hajós, G.Hullám, A.Millinghoffer Cs.Szalai and A. Falus: Adaptive Sequential Partial Genome Screening Studies: a Case Study in Asthma, Human Genome Variation Society, Human Variome Project, Towards Establishing Standards, 22nd May 2009, Vienna, Austria

 

Conference papers

 

P. Antal: Applicability of Prior Domain Knowledge Formalised as Bayesian Network in the Process of Construction of a Classifier, IEEE IECON’98, 1998, Aachen, pp. 2527-2531

P. Antal, H. Verrelst, D. Timmerman, S. Van Huffel, B. De Moor, I. Vergote, Y. Moreau: Bayesian networks in ovarian cancer diagnosis: potentials and limitations, 13th IEEE Symposium on Computer-Based Medical Systems, June 23-24, 2000, Texas Medical Center, Houston, Texas, pp. 103-108

P. Antal, H. Verrelst, D. Timmerman, S. Van Huffel, B. De Moor, I. Vergote: How might we combine the information we know about a mass better? The use of mathematical models to handle medical data, 1st Montecarlo Conference on updates in Gynaecology, March 8-11, 2000, Monaco

P. Antal, G. Fannes, H. Verrelst, B. De Moor, J Vandewalle: Incorporation of prior knowledge in black-box models: Comparison of Transformation Methods from Bayesian Network to Multilayer Perceptrons, in Working notes of the Fusion of Domain Knowledge with Data for Decision Support workshop, The Sixteenth Conference on Uncertainty in Artificial Intelligence (UAI-2000), June 30, 2000, Stanford University, pp. 11-16

P. Antal, G. Fannes, S. Van Huffel, B. De Moor, J Vandewalle: Bayesian predictive models for Ovarian Cancer Classification: evaluation of Logistic Regression, Multi Layer Perceptron and Belief Network models in the Bayesian Context, Proc. Of the 10th Belgian-Dutch Conf. On Machine Learning,   BENELEARN2000, December 13, 2000, Tilburg University, pp. 125-132

P. Antal, G. Fannes, De Smet F., B. De Moor: Ovarian cancer classification with rejection by Bayesian Belief Networks, in Working Notes of the Bayesian Models in Medicine workshop, the European Conference on Artificial Intelligence in Medicine (AIME'01), 8th European Conference on Artificial Intelligence in Medicine, AIME'01, July 1-4, 2001, Cascais, Portugal,  pp 23-27

P. Antal, T. Meszaros, B. De Moor, T. Dobrowiecki: Annotated Bayesian networks: a tool to integrate textual and probabilistic medical knowledge, Fourteenth IEEE Symposium on Computer-Based Medical Systems (CBMS 2001), July 26-27, Bethesda, MD, pp. 177-182

P. Antal, T. Meszaros, D. Timmerman, B. De Moor, T. Dobrowiecki: Domain knowledge based information retrieval langugae: an application of annotated  Bayesian networks, Fifteenth IEEE Symposium on Computer-Based Medical Systems (CBMS 2002), June 3-7, Maribor, Slovenia, pp 213-218

S. Aerts, P. Antal, B. De Moor, Y. Moreau: Web-based data collection for ovarian cancer: a case study, Fifteenth IEEE Symposium on Computer-Based Medical Systems (CBMS 2002), June 3-7, Maribor, Slovenia, pp 282-287

P. Antal, P. Glenisson, G. Fannes, Y. Moreau, B. De Moor: On the potential of domain literature for clustering and Bayesian network learning, The Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM SIGKDD), 2002, Edmonton, pp 405-414

P. Antal, G. Fannes, Y. Moreau, B. De Moor: Using Domain Literature and Data to Annotate and Learn Bayesian Networks, 14th Belgian-Dutch Conference on Artificial Intelligence (BNAIC'02), Leuven, 2002, pp 3-10

P. Antal, P. Glenisson, T. Boonefaes, P. Rottiers, Y. Moreau  Towards an integrated usage of expression data and domain literature in gene clustering: representations and methods,  Internal report 01-69, 2001

P. Glenisson, P. Antal, J. Mathys, Y. Moreau and B. De Moor: Evaluation of the vector space representation in text-based gene clustering, Pacific Symposium on Biocomputing (PSB03), Hawaii, 2003, pp 391-402

P.Antal, A.Millinghoffer: Learning causal bayesian networks from literature data, Proceedings of the 3rd International Conference on Global Research and Education, Inter-Academia'04, Budapest, 2004, pages 149--160,

P.Antal,  A.Millinghoffer: A probabilistic knowledge base using annotated bayesian network features.  In Proceedings of the 6th International Symposium of Hungarian Researchers on Computational Intelligence, Budapest, 2005, pages 1--12.

P. Antal, A. Millinghoffer: Literature mining using Bayesian networks. In Proc. of Third European Workshop on Probabilistic Graphical Models, Prague, 2006. pp 17-24

P. Antal, A. Millinghoffer: Learning complex Bayesian network features for classification. In Proc. of Third European Workshop on Probabilistic Graphical Models, Prague, 2006. pp 9-16

A. Millinghoffer, G. Hullám, P. Antal: On inferring the most probable sentences in Bayesian logic, in Working Notes of the Workshop on Intelligent Data Analysis in bioMedicine And Pharmacology (IDAMAP07), the European Conference on Artificial Intelligence in Medicine (AIME'07), 11th European Conference on Artificial Intelligence in Medicine, AIME'07, July 7, 2007, Amsterdam, pp 13-18

A. Millinghoffer, G. Hullám, P. Antal: A probabilistic logic incorporating posteriors of hierarchic graphical models, in Working Notes of The Third Workshop on Combining Probability and Logic (progic07),  Sept. 5-7, 2007, Kent,  pp –

P. Antal, A. Millinghoffer, G. Hullám, Cs. Szalai, A. Falus: A Bayesian View of Challenges in Feature Selection: Feature Aggregation, Multiple Targets, Redundancy and Interaction, ECML/PKDD, Workshop on New challenges for feature selection in data mining and knowledge discovery 2008 (FSDM08),  Antwerp, JMLR: Workshop and Conference Proceedings 4, 74-89

P Antal, G Hajós, P Sárközy: Bayesian network based analysis in sequential partial genome screening studies, MODGRAPH, June 8., 2009, Nantes, France

G. Hullám, P. Antal, Cs. Szalai, A. Falus: Evaluation of methods in GA studies: yet another case for Bayesian network, Machine Learning in System Biology 2009 (MLSB09), Sept 5-6, Ljubljana, Slovenia, Proc. of the Third International Workshop, 35-44

 

Thesis

 

P. Antal: Integrative Analysis of Data, Literature, and Expert Knowledge, Ph.D. dissertation, K.U.Leuven, ESAT, D/2007/7515/99, ISBN 978-90-5682-865-3

 

Magyarul

 

Department of Measurement and Information Systems

 

Budapest University of Technology and Economics