Jiří Kléma

E-mail: klema::fel:cvut:cz

Web: http://ida.felk.cvut.cz/klema/

Phone: + 420-224 357 608

Address: Karlovo náměstí 13, 121 35 Prague

Office: KN:E-432

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Current position: Associate Professor at the Department of Computer Science, Faculty of Electrical Engineering, Czech Technical University, Prague.
 Deputy head of the Department of Computer Science with responsibility for teaching.
  Member of the Intelligent Data Analysis Research Group.
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Teaching: XP36VPD, Selected Parts of Data Mining, PhD course
  B4M36SAN, Statistical Data Analysis, master course
  B4M36SMU, Symbolic Machine Learning, master course
  A6M33BIN, Bioinformatics, master course
  A4B33ZUI, Foundations of Artificial Intelligence, bachelor course
  Open Informatics, a computer science program, member of the board.
  Students, past teaching
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Research: machine learning, data mining and decision support, bioinformatics
  Other research topics
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Selected publications: Klema, J., Malinka, F., Zelezny, F.: Semantic biclustering for finding local, interpretable and predictive expression patterns. BMC Genomics, Volume 18, 2017. (accepted).
  Andel, M., Klema, J., Krejcik, Z.: Network-Constrained Forest for Regularized Classification of Omics Data. Methods, Vol. 83, pp. 88–97, 15 July 2015. (preprint pdf, online).
  Libalova, H., Uhlirova, K., Klema, J., Machala, M., Sram, R., Ciganek, M. and Topinka, J.: Global Gene Expression Changes in Human Embryonic Lung Fibroblasts Induced by Organic Extracts from Respirable Air Particles. Particle and Fibre Toxicology, 9:1, 2012. (online).
  Krejnik, M., Klema J.: Empirical Evidence of the Applicability of Functional Clustering through Gene Expression Classification. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9:3, pp. 788-798, 2012. (online), (pdf).
  Holec M., Klema J., Zelezny F., Tolar J.: Comparative Evaluation of Set-Level Techniques in Predictive Classification of Gene Expression Samples. BMC Bioinformatics, 13, Suppl. 10, S15, 2012. (online).
  Plantevit, M., Charnois, T., Klema, J., Rigotti, C., Cremilleux, B.: Combining Sequence and Itemset Mining to Discover Named Entities in Biomedical Texts: A New Type of Pattern. International Journal of Data Mining, Modelling and Management, Vol. 1, No. 2, pp. 119-148, 2009.
  Klema, J., Novakova, L., Karel, F., Stepankova, O., Zelezny, F.: Sequential Data Mining: A Comparative Case Study in Development of Atherosclerosis Risk Factors. IEEE Transactions on Systems, Man, and Cybernetics: Part C: Applications and Reviews, Vol. 38, no. 1, pp. 3-15, 2008. (IEEE Trans. Sys Man Cyb C), (pdf).
  All publications, VVVS, DBLP, Google Scholar
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Personal links: Full CV
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