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Department: Any ÅAU / Department of Information Technologies UTU / Department of Information Technology UTU / Department of Mathematics and Statistics UTU / Turku School of Economics, Institute of Information Systems Sciences

Research Unit: Any Algorithmics and Computational Intelligence Group (ACI) Biomathematics Research Unit (BIOMATH) Communication Systems (ComSys) Computational Biomodeling Laboratory (Combio Lab) Data Mining and Knowledge Management Laboratory Distributed Systems Laboratory (DS Lab) Embedded Computer and Electronic Systems (ECES) Embedded Systems Laboratory (ESLAB) FUNDIM, Fundamentals of Computing and Discrete Mathematics Institute for Advanced Management Systems Research (IAMSR) Learning and Reasoning Lab Software Construction Laboratorium Software Development Laboratory (SwDev) Software Engineering Laboratory (SE Lab) Turku BioNLP Group Turku Optimization Group (TOpGroup) UTU Information Systems Science (ISS)

Publication type: Any Monographs Edited books Edited special issues of journals Edited proceedings Articles in journals Articles in proceedings Chapters in edited books Ph.D. thesis Lic. thesis Technical reports

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Articles in journals (4):

• Asta Laiho, Noora Kotaja, Attila Gyenesei, Anu Sironen, Transcriptome Profiling of the Murine Testis During the First Wave of Spermatogenesis. Plos One , e61558, 2013.
• Attila Gyenesei, Jonathan Moody, Asta Laiho, Colin Semple, Chris Haley, Wenhua Wei, BiForce Toolbox: Powerful High-Throughput Computational Analysis of Gene-Gene Interactions in Genome-Wide Association Studies. Nucleic Acids Research , W628–32, 2012.
• Attila Gyenesei, Jukka Teuhola, Multidimensional Fuzzy Partitioning of Attribute Ranges for Mining Quantitative Data. International Journal of Intelligent Systems 19(11), 1111–1126, 2004.
• Attila Gyenesei, A Fuzzy Approach for Mining Quantitative Association Rules. Acta Cybernetica 15, 305–320, 2001.

Articles in proceedings (9):

• Asta Laiho, Andras Kiraly, Janosh Abonyi, Attila Gyenesei, Biclustering of High-Throughput Gene Expression Data with BiclusterMiner. In: Jilles Vreeken, Charles Ling, Mohammed J. Zaki, Arno Siebes, Jeffrey Xu Yu, Bart Goethals, Geoff Webb, Xindong Wu (Eds.), IEEE 12th International Conference on Data Mining Workshops, 131–138, IEEE, 2012.
• Asta Laiho, Andras Kiraly, Attila Gyenesei, GeneFuncster: A Web Tool for Gene Functional Enrichment Analysis and Visualisation. In: D. Gilbert, M. Heiner (Eds.), CMSB 2012, LNCS 7605, 382–385, Springer-Verlag Berlin Heidelberg , 2012.
• Attila Gyenesei, Jukka Teuhola, Probabilistic Iterative Expansion of Candidates in Mining Frequent Itemsets. In: Proceedings of the IEEE ICDM Workshop on Frequent Itemset Mining Implementations , 90, 43 - 49, 2003.
• Attila Gyenesei, Jukka Teuhola, Multidimensional Partitioning of Attribute Ranges for Mining Frequent Fuzzy Patterns. In: Proceeding of International Conference on Fuzzy Information Processing, 413-422, Tsinghua University Press, Springer, 2003.
• Attila Gyenesei, Jukka Teuhola, Mining Fuzzy Frequent Patterns Without Repeated Candidate Generation. In: Proceedings of the 1st International Conference on Fuzzy Systems and Knowledge Discovery, 374-380, 2002.
• Attila Gyenesei, Determining Fuzzy Sets for Quantitative Attributes in Data Mining Problems. In: Advances in Fuzzy Systems and Evolutionary Computation, Artificial Intelligence Series, A Series of Reference Books and Textbooks, 48-53, World Scientific Engineering Society (WSES), 2001.
• Attila Gyenesei, Jukka Teuhola, Interestingness Measures for Fuzzy Association Rules. In: Principles of Data Mining and Knowledge Discovery, Lecture Notes in Artificial Intelligence 2168, 152-164, Springer-Verlag, 2001.
• Attila Gyenesei, A Fuzzy Approach for Mining Interesting Quantitative Association Rules. In: Volume of Extended Abstracts of the Conference of PhD Students in Computer Science (CSCS), 40-41, 2000.
• Attila Gyenesei, Mining Weighted Association Rules for Fuzzy Quantitative Items. In: Jan Komorowski Jan Zytkow Djamel A. Zighed (Ed.), Principles of Data Mining and Knowledge Discovery, Lecture Notes in Artificial Intelligence 1910, 416-423, Springer-Verlag, 2000.

Chapters in edited books (1):

• Attila Gyenesei, Jukka Teuhola, A Probabilistic Approach to Mining Fuzzy Frequent Patterns. In: Saman K. Halgamuge,, Lipo Wang (Eds.), Classification and Clustering for Knowledge Discovery, Studies in Computational Intelligence 4, 73–90, Springer, 2005.

Ph.D. thesis (1):

• Attila Gyenesei, Discovering Frequent Fuzzy Patterns in Relations of Quantitative Attributes. TUCS Dissertations 51. Turku Centre for Computer Science, 2004.

Technical reports (3):

• Attila Gyenesei, A Fuzzy Approach for Mining Quantitative Association Rules. TUCS Technical Reports 336, Turku Centre for Computer Science, 2000.
• Attila Gyenesei, Mining Weighted Association Rules for Fuzzy Quantitative Items. TUCS Technical Reports 346, Turku Centre for Computer Science, 2000.
• Attila Gyenesei, Fuzzy Partitioning of Quantitative Attribute Domains by a Cluster Goodness Index. TUCS Technical Reports 368, Turku Centre for Computer Science, 2000.