Juho Rousu's publications

2008-

• Towards Structured Output Prediction of Enzyme Function (with Katja Astikainen, Liisa Holm, Esa Pitkänen, Sandor Szedmak). BMC Proceedings, 2008, accepted
• FiD: a software for ab initio structural identification of product ions from tandem mass spectrometric data (with Markus Heinonen, Ari Rantanen, Taneli Mielikainen, Juha Kokkonen, Jari Kiuru, Raimo A. Ketola). Rapid Communications in Mass Spectrometry, accepted
• An analytic and systematic framework for estimating metabolic flux ratios from 13C tracer experiments (with Ari Rantanen, Paula Jouhten, Nicola Zamboni, Hannu Maaheimo, Esko Ukkonen). BMC Bioinformatics 2008, 9:266.
• A computational method for reconstructing gapless metabolic networks (with Esa Pitkanen, Ari Rantanen, Esko Ukkonen). Proc. 2nd International Conference on Bioinformatics Research and Development (BIRD '08). Communications in Computer and Information Science, Vol. 13, Springer, 2008

2007

• Editorial: Information Theoretic Methods for Bioinformatics (with J. Rissanen, P. Grunwald, J. Heikkonen, P. Myllymäki, T Roos). EURASIP Journal on Bioinformatics and Systems Biology, vol. 2007, (2007)
• Editorial: Probabilistic modeling and machine learning in structural and systems biology (with Samuel Kaski, Esko Ukkonen, eds.). PMSB 2006 special issue. BMC Bioinformatics 2007, 8 (Suppl 2), S1
• An Efficient Method for Large Margin Parameter Optimization in Structured Prediction Problems (with Huizhen Yu), Technical report C-2007-87, Dept. Computer Science, Univ. of Helsinki, 2007.
• Towards Structured Prediction of Enzyme Function (with Katja Astikainen, Liisa Holm, Esa Pitkanen and Sandor Szedmak). Machine Learning in Systems Biology (MLSB-2007), Evry, France, September 2007
• Experiments for Completion of Biological Networks with Output Kernel Trees (with Cheng Lu). Report C-2007-10, Department of Computer Science, University of Helsinki, 2007
  
•  Efficient algorithms for max-margin structured classification (with Craig Saunders, Sandor Szedmak and John Shawe-Taylor). In G. Bakir, T. Hofmann, B. Schölkopf, A. Smola, B. Taskar, S.V.N Vishwanathan (eds.): Predicting Structured Data, MIT Press, 2007

2006

• Practical Approximation of Optimal Multivariate Discretization (with Tapio Elomaa and Jussi Kujala). Proc. 16th International Symposium on Methodologies for Intelligent Systems (ISMIS-2006)- Lecture Notes in Computer Science 4203, 2006, pp. 612 - 621
• Kernel-based Learning of Hierarchical Multilabel Classification Models (with Craig Saunders, Sandor Szedmak and John Shawe-Taylor). Journal of Machine Learning Research 7 (2006), pp. 1601 - 1626. MATLAB implementation of the learning algorithm is available here.
• Equivalence of metabolite fragments and flow analysis of isotopomer distributions for flux estimation (with Ari Rantanen, Hannu Maaheimo,Esa Pitkänen and Esko Ukkonen). Transactions on Computational Systems Biology, Lecture Notes in Computer Science 4220, 2006, pp. 198 - 220
• Probabilistic Modeling and Machine Learning in Structural and Systems Biology (ed., with Samuel Kaski and Esko Ukkonen). Workshop proceedings. Series of publications B, report B-2006-4, Department of Computer Science, University of Helsinki, 2006
• Planning optimal measurements of isotopomer distributions for estimation of metabolic fluxes (with Ari Rantanen, Taneli Mielikäinen, Juho Rousu, Hannu Maaheimo, Esko Ukkonen). Bioinformatics, Vol. 22, Number 10 (2006), pp. 1198 - 1206.
• Ab initio prediction of molecular fragments from tandem mass spectrometry data (with Heinonen, M.,Rantanen, A.,Mielikäinen, T.,Pitkänen, E.,Kokkonen, J.). German Conference on Bioinformatics, GCB 2006. Gesellschaft für Informatik 2006. p. 40-53

2005

• Learning Hierarchies at Two-class Complexity (with Sandor Szedmak, Craig Saunders, John Shawe-Taylor). NIPS 2005 Workshop on Kernel Methods and Structured Domains, 2005.
• Finding Feasible Pathways in Metabolic Networks (with Esa Pitkänen, Ari Rantanen and Esko Ukkonen). 10th Panhellenic Conference on Informatics 2005. Lecture Notes in Computer Science 3746 (2005), pp. 123 - 133.
• Planning isotopomer measurements for estimation of metabolic fluxes (with Ari Rantanen, Taneli Mielikäinen and Esko Ukkonen). GCB'2005. Lecture Notes in Informatics Vol. P-71 (2005), pp. 177 - 191
• Efficient Computation of Gapped Substring Kernels on Large Alphabets (with John Shawe-Taylor). Journal of Machine Learning Research 6 (2005), 1323-1344,
• Approximation algorithms for minimizing Empirical Error by Axis-Parallel Hyperplanes (with Tapio Elomaa and Jussi Kujala). 16th European Conference on Machine Learning (ECML-2005), Lecture Notes in Artificial Intelligence 3720, pp. 547--555
• Learning Hierarchical Multi-Category Text Classification Models (with Craig Saunders, Sandor Szedmak and John Shawe-Taylor). 22nd International Conference on Machine Learning (ICML'2005), 745--752
• Flow analysis of metabolite fragments for flux estimation (with Ari Rantanen, Esa Pitkänen, Hannu Maaheimo and E. Ukkonen). Proc. Computational Methods in Systems Biology (CMSB'2005), University of Edinburgh, 2005, 242--255
• Isotopomer distribution computation from tandem mass spectrometric data with overlapping fragment spectra (with Ari Rantanen, Raimo A. Ketola and Juha T. Kokkonen). Spectroscopy 19, 1 (2005), 53-67

2004

• A Rapidly Computable String Kernel Based on the Discrete Fourier Transform: Derivation and Experiments (with Chris Watkins). Manuscript, 2004
• On Maximum Margin Hierarchical Multilabel Classification (with Craig Saunders, Sandor Szedmak and John Shawe-Taylor). NIPS Workshop on Learning with Structured Outputs, 2004. Extended abstract.
• Applying machine learning methods in studying relationships between mouthfeel and microstructure in oat bread (with M. Salmenkallio-Marttila, K. Roininen, J. T. Lindgren, K. Autio and L. Lähteenmäki). Journal of Texture Studies 35, 3 (2004), 225-250
• Efficient multisplitting revisited: Optima-preserving elimination of partition candidates (with Tapio Elomaa). Data Mining and Knowledge Discovery 8, 2 (2004) 97-126
• Efficient Computation of Gap-Weighted String Kernels on Large Alphabets (with John Shawe-Taylor). PASCAL workshop on text understanding and mining, Grenoble, France, January 2004.

2003

• On Decision Boundaries of Naive Bayes in Continuous Domains (with Tapio Elomaa). Principles of Data mining and Knowledge Discovery, PKDD-2003, Lecture Notes in Computer Science 2838 (2003), 144-155
• Improved Computation of 13C-Isotopomer Distributions from Tandem-MS Data (with Ari Rantanen). Report C-2003-9,  Department of Computer Science, University of Helsinki, 2003
• Optimal Multivariate Discretization for Naive Bayesian Classifiers is NP-hard. Report C-2003-8, Department of Computer Science, University of Helsinki, 2003
  
• A method for estimating metabolic fluxes from incomplete isotopomer information (with Ari Rantanen, Hannu Maaheimo, Esa Pitkänen, Katja Saarela and Esko Ukkonen). International Workshop on Computational methods in Systems Biology,  Rovereto, Italy, February 2003.  Lecture Notes in Computer Science 2602 (2003),  88-103
  
• Necessary and Sufficient Preprocessing in Numerical Range Discretization (with Tapio Elomaa).  Knowledge and Information Systems 5, 2 (Apr. 2003) 162-182
• Novel Computational Tools in Bakery Process Data Analysis: a Comparative Study (with Laura Flander,Jaana Suutarinen, Karin Autio, Ari Rantanen and Petri Kontkanen). Journal of Food Engineering 57, 1 (2003), pp.  45-56

2002

• Linear-time preprocessing in optimal numerical range partitioning (with  Tapio Elomaa). Journal of Intelligent Information Systems 18, 1 (2002), pp. 55--70
• Computing Positional Isotopomer Distributions from Tandem Mass Spectrometric Data (with Ari Rantanen, Raimo Ketola,Juha T. Kokkonen and Virpi Tarkiainen). Metabolic Engineering 4 (2002), pp. 285-294
• Fast Minimum Training Error Discretization (with Tapio Elomaa). Proc. 19th International Conference on Machine Learning,  ICML 2002,  pp. 131-138
• Flux estimation using incomplete isotopomer information (ps.gz, 160kb) (pdf ,455kB) (with A. Rantanen and E. Ukkonen). Technical Report C-2002-55, Department of Computer Science, University of Helsinki, 2002
• Microscopy image analysis of bread using machine learning methods (ps.gz)  (pdf) (with J. T. Lindgren).  Technical Report C-2002-68,  Department of Computer Science, University of Helsinki, 2002
  

2001

• Efficient range partitioning in classification learning. PhD Thesis, Report A-2001-1, Department of Computer Science, University of Helsinki, 2001. (Abstract (43kB)) (Summary (682kB)).
• On the computational complexity of optimal multisplitting (with Tapio Elomaa). Fundamenta Informaticae 47, 1-2 (2001), pp. 35-52
• An integrated approach to bioprocess recipe design (pdf, 123kB) (withRobert Aarts). Integrated Computer-Aided Engineering 8, 4 (2001), 363-373. (c) 2001 IOS Press
• A Neural Network Tool for Brewery Fermentations (pdf, 251kB)  (ps.gz, 340kB) (with Jermu Pöllänen and Jukka Kronlöf). Automation'2001 seminar days , SAS Julkaisusarja 24 (2001), 246-251
• Preprocessing Opportunities in Optimal Numerical Range Partitioning (with Tapio Elomaa). First IEEE International Conference on Data Mining, San Diego, Nov/Dec 2001, pp. 115-122
  

2000

• Generalizing Boundary Points (ps.gz, 54kb) (with Tapio Elomaa). Proc. 17th Natl. Conf on Artificial Intelligence, AAAI-2000,  pp. 570-576. (c) 2000 AAAI Press
• On the Complexity of Optimal Multisplitting (with Tapio Elomaa). Proc. 12th International Symposium on Methodologies for Intelligent Systems,
    ISMIS-2000. Lecture Notes in Artificial Intelligence 1932 (2000), pp. 552-561
  
• On splitting properties of common attribute evaluation functions (with Tapio Elomaa). Report C-2000-1, Department of Computer Science, University of Helsinki, 2000
• Uses of convexity in numerical domain partitioning (with Tapio Elomaa). NeuroCOLT2 Technical Report NC2-TR-2000-074,  Royal Holloway University of London, 2000
  

1999

• General and Efficient Multisplitting of Numerical Attributes (ps.gz, 184kb)  (with Tapio Elomaa). Machine Learning 36, 3 (1999), pp. 201-244. (c) 1999 Kluwer Academic Publishers
• Speeding up the search for optimal partitions (ps.gz, 81kb) (with Tapio Elomaa ). In J. Zytkow & J. Rauch (eds.), Principles and Practise of Data Mining and Knowledge Discovery in Databases, Proc 3rd PKDD. Lecture Notes in Artificial Intelligence 1704 (1999), pp. 89-97. (c) 1999 Springer
• Adaptive Planning of Fermentation Recipes. Proc. Tool Environments and Development Methods for Intelligent Systems (TOOLMET'99),
  Oulun Yliopistopaino, 1999, pp. 118--122
• Predicting the speed of beer fermentation in laboratory and industrial scale (with Tapio Elomaa and Robert Aarts). Proc. 5th IWANN. Lecture
  Notes in Computer Science 1607 (1999), pp. 893-901
  

1998

• Case-based planning methods in biotechnical and food processes (with Robert Aarts). Proc. Int. Symp. Automatic Control of food and biological processes, Part One. SIK (1998), pp. 215 - 224.
• Boundary points as an indication of attribute relevance (with  Tapio Elomaa). Proc. 8th Finnish Artificial Intelligence Conference, Finnish Artificial Intelligence Society, 1998, pp. 21 - 30.
• Postponing the evaluation of attributes with a high number of boundary points (with  Tapio Elomaa). Principles of Data Mining and Knowledge Discovery, Proc. 2nd PKDD . Lecture Notes in Artificial Intelligence 1510 (1998), pp. 121-129
• Model-based reasoning about cases (with Robert Aarts). Proc. 1998 AAAI Spring Symposium, AAAI Technical Report SS-98-04, AAAI press,  pp. 6-9
  

1997

• Well-behaved attribute evaluation functions for numerical attributes (with  Tapio Elomaa). Proc. 10th International Symposium on Technologies for Intelligent Systems. Lecture Notes in Artifical Intelligence 1325 (1997), pp. 147-156
• Efficient multisplitting on numerical data (with Tapio Elomaa). In Proc. 1st European Symposium on Principles of Data Mining and Knowledge Discovery. Lecture Notes in Artificial Intelligence 1263 (1997), pp. 178-188
• Qualitative knowledge to support reasoning about cases (with Robert Aarts). Lecture Notes in Artificial Intelligence Vol. 1266 (1997), pp. 489-498
• On the well-behavedness of important attribute evaluation functions (with  Tapio Elomaa). In Proc. Sixth Scandinavian Conference on Artificial Intelligence SCAI'97, IOS Press (1997), pp. 95-106
  

1996

•  Finding Optimal Multi-Splits for Numerical Attributes in Decision Tree Learning (with Tapio Elomaa). NeuroCOLT Technical Report NC-TR-96-041, Royal Holloway University of London, 1996
• Päätöspuiden ja -listojen muodostaminen MDL-periaatteen avulla (in Finnish). MSc Thesis, Technical Report C-1996-15,
    Department of Computer Science, University of Helsinki, 1996
  
• Adaptation cost as a criterion for solution evaluation (with Robert Aarts). Advances in case-based reasoning. Lecture Notes in Artificial Intelligence Vol. 1168 (1996), pp. 354 - 361
• Towards CBR for bioprocess planning (with Robert Aarts ). Advances in case-based reasoning. Lecture Notes in Artificial Intelligence Vol. 1168 (1996), pp. 16 - 27