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ORCIDJirí Kléma
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2020 – today
- 2024
[c22]Petr Rysavý
, Jirí Kléma, Michaela Dostálová Merkerová:
GPACDA - circRNA-Disease Association Prediction with Generating Polynomials. IWBBIO (1) 2024: 33-48- [i1]Vladimír Kunc, Jirí Kléma:
Three Decades of Activations: A Comprehensive Survey of 400 Activation Functions for Neural Networks. CoRR abs/2402.09092 (2024) - 2022
- [j9]Petr Rysavý, Jirí Kléma, Michaela Dostálová Merkerová:
circGPA: circRNA functional annotation based on probability-generating functions. BMC Bioinform. 23(1): 392 (2022) - [c21]Vladimír Kunc, Jirí Kléma:
On functional annotation with gene co-expression networks. BIBM 2022: 3055-3062 - 2020
- [j8]Frantisek Malinka, Filip Zelezný, Jirí Kléma:
Finding semantic patterns in omics data using concept rule learning with an ontology-based refinement operator. BioData Min. 13(1): 13 (2020)
2010 – 2019
- 2019
- [c20]Eliska Dvoráková, Sajal Kumar, Jirí Kléma, Filip Zelezný, Karel Drbal, Mingzhou Song:
Evaluating Model-free Directional Dependency Methods on Single-cell RNA Sequencing Data with Severe Dropout. ICBRA 2019: 55-62 - 2015
- [j7]Peggy Cellier, Thierry Charnois, Marc Plantevit, Christophe Rigotti, Bruno Crémilleux, Olivier Gandrillon, Jirí Kléma, Jean-Luc Manguin:
Sequential pattern mining for discovering gene interactions and their contextual information from biomedical texts. J. Biomed. Semant. 6: 27 (2015) - [c19]Michael Andel, Filip Masri, Jirí Kléma, Zdenek Krejcík, Monika Belickova:
Sparse omics-network regularization to increase interpretability and performance of linear classification models. BIBM 2015: 615-620 - 2014
- [c18]Michael Andel, Jirí Kléma, Zdenek Krejcík:
Network-constrained forest for regularized omics data classification. BIBM 2014: 410-417 - [c17]Jirí Kléma, Jan Zahálka, Michael Andel, Zdenek Krejcík:
Knowledge-based Subtractive Integration of mRNA and miRNA Expression Profiles to Differentiate Myelodysplastic Syndrome. BIOINFORMATICS 2014: 31-39 - [c16]Jirí Kléma, Jan Zahálka, Michael Andel, Zdenek Krejcík:
Interaction-Based Aggregation of mRNA and miRNA Expression Profiles to Differentiate Myelodysplastic Syndrome. BIOSTEC (Selected Papers) 2014: 165-180 - [c15]Matej Holec, Valentin Gologuzov, Jirí Kléma:
miXGENE Tool for Learning from Heterogeneous Gene Expression Data Using Prior Knowledge. CBMS 2014: 247-250 - 2012
- [j6]Matej Holec, Jirí Kléma, Filip Zelezný, Jakub Tolar:
Comparative evaluation of set-level techniques in predictive classification of gene expression samples. BMC Bioinform. 13(S-10): S15 (2012) - [j5]Milos Krejnik, Jirí Kléma:
Empirical Evidence of the Applicability of Functional Clustering through Gene Expression Classification. IEEE ACM Trans. Comput. Biol. Bioinform. 9(3): 788-798 (2012) - [c14]Jirí Kléma:
Machine learning applications in bioinformatics. ITAT 2012: 1-2 - 2011
- [c13]Jirí Kléma, Matej Holec, Filip Zelezný, Jakub Tolar:
Comparative Evaluation of Set-Level Techniques in Microarray Classification. ISBRA 2011: 274-285 - [c12]Jan Hrdlicka, Jirí Kléma:
Schizophrenia Prediction with the Adaboost Algorithm. MIE 2011: 574-578
2000 – 2009
- 2009
- [j4]Marc Plantevit, Thierry Charnois, Jirí Kléma, Christophe Rigotti, Bruno Crémilleux:
Combining sequence and itemset mining to discover named entities in biomedical texts: a new type of pattern. Int. J. Data Min. Model. Manag. 1(2): 119-148 (2009) - [c11]Matej Holec, Filip Zelezný, Jirí Kléma, Jakub Tolar:
Integrating Multiple-Platform Expression Data through Gene Set Features. ISBRA 2009: 5-17 - 2008
- [j3]Jirí Kléma, Sylvain Blachon, Arnaud Soulet, Bruno Crémilleux, Olivier Gandrillon:
Constraint-Based Knowledge Discovery from SAGE Data. Silico Biol. 8(2): 157-175 (2008) - [j2]Jirí Kléma, Lenka Nováková, Filip Karel, Olga Stepánková, Filip Zelezný:
Sequential Data Mining: A Comparative Case Study in Development of Atherosclerosis Risk Factors. IEEE Trans. Syst. Man Cybern. Part C 38(1): 3-15 (2008) - [c10]Pavel Smrz, Jana Silhavá, Jirí Kléma, Filip Zelezný:
Gene expression data mining guided by genomic background knowledge. SOFSEM (2) 2008: 101-111 - 2006
- [c9]Jirí Kléma, Arnaud Soulet, Bruno Crémilleux, Sylvain Blachon, Olivier Gandrillon:
Mining Plausible Patterns from Genomic Data. CBMS 2006: 183-190 - [c8]Arnaud Soulet, Jirí Kléma, Bruno Crémilleux:
Efficient Mining Under Rich Constraints Derived from Various Datasets. KDID 2006: 223-239 - 2005
- [j1]Jirí Kléma, Jirí Kubalík, Lenka Lhotská:
Optimized model tuning in medical systems. Comput. Methods Programs Biomed. 80(Supplement-1): S17-S28 (2005) - 2004
- [c7]Jirí Kubalík, Jirí Kléma, Miroslav Kulich:
Application of Soft Computing Techniques to Rescue Operation Planning. ICAISC 2004: 897-902 - [c6]Jirí Kléma, Ondrej Flek, Jan Kout, Lenka Nováková:
Intelligent Diagnosis and Learning in Centrifugal Pumps. BASYS 2004: 513-522 - 2002
- [c5]Jirí Kléma, Jirí Kubalík, Jiri Palous:
Optimized Model Tuning in Medical Systems. CBMS 2002: 59-64 - [c4]Olga Stepánková, Jirí Kléma, Stepán Lauryn, Petr Miksovský, Lenka Nováková:
Data Mining and Resource Allocation: A Case Study. BASYS 2002: 477-484 - 2001
- [c3]Matej Sprogar, Peter Kokol, Milan Zorman, Vili Podgorelec, Lenka Lhotská, Jirí Kléma:
Evolving Groups of Basic Decision Trees. CBMS 2001: 183-188 - [c2]Matej Sprogar, Peter Kokol, Milan Zorman, Vili Podgorelec, Lenka Lhotská, Jirí Kléma:
Notes on Medical Decision Model Creation. ISMDA 2001: 270-275
1990 – 1999
- 1998
- [c1]Lenka Lhotská, Jirí Kléma, Olga Stepánková:
Problems of learning in multi-agent systems. BASYS 1998: 615-624
Coauthor Index
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