Towards CBR for Bioprocess Planning. - Robert J. Aarts; Juho Rousu (EWCBR, 1996)

Adaptation Cost as a Criterion for Solution Evaluation. - Juho Rousu; Robert J. Aarts (EWCBR, 1996)

Qualitative Knowledge to Support Reasoning About Cases. - Robert J. Aarts; Juho Rousu (ICCBR, 1997)

Well-Behaved Evaluation Functions for Numerical Attributes. - Tapio Elomaa; Juho Rousu (ISMIS, 1997)

Efficient Multisplitting on Numerical Data. - Tapio Elomaa; Juho Rousu (PKDD, 1997)

On the Well-Behavedness of Important Attribute Evaluation Functions. - Tapio Elomaa; Juho Rousu (SCAI, 1997)

Postponing the Evaluation of Attributes with a High Number of Boundary Points. - Tapio Elomaa; Juho Rousu (PKDD, 1998)

Predicting the Speed of Beer Fermentation in Laboratory and Industrial Scale. - Juho Rousu; Tapio Elomaa; Robert J. Aarts (IWANN (2), 1999)

Speeding Up the Search for Optimal Partitions. - Tapio Elomaa; Juho Rousu (PKDD, 1999)

General and Efficient Multisplitting of Numerical Attributes. - Tapio Elomaa; Juho Rousu (Mach. Learn., 1999)

Generalizing Boundary Points. - Tapio Elomaa; Juho Rousu (AAAI/IAAI, 2000)

On the Complexity of Optimal Multisplitting. - Tapio Elomaa; Juho Rousu (ISMIS, 2000)

Preprocessing Opportunities in Optimal Numerical Range Partitioning. - Tapio Elomaa; Juho Rousu (ICDM, 2001)

On the Computational Complexity of Optimal Multisplitting. - Tapio Elomaa; Juho Rousu (Fundam. Informaticae, 2001)

An integrated approach to bioprocess recipe design. - Juho Rousu; Robert J. Aarts (Integr. Comput. Aided Eng., 2001)

Fast Minimum Training Error Discretization. - Tapio Elomaa; Juho Rousu (ICML, 2002)

Linear-Time Preprocessing in Optimal Numerical Range Partitioning. - Tapio Elomaa; Juho Rousu (J. Intell. Inf. Syst., 2002)

A Method for Estimating Metabolic Fluxes from Incomplete Isotopomer Information. - Juho Rousu; Ari Rantanen; Hannu Maaheimo; Esa Pitkänen; Katja Saarela; Esko Ukkonen (CMSB, 2003)

On Decision Boundaries of Naïve Bayes in Continuous Domains. - Tapio Elomaa; Juho Rousu (PKDD, 2003)

Necessary and Sufficient Pre-processing in Numerical Range Discretization. - Tapio Elomaa; Juho Rousu (Knowl. Inf. Syst., 2003)

Efficient Multisplitting Revisited: Optima-Preserving Elimination of Partition Candidates. - Tapio Elomaa; Juho Rousu (Data Min. Knowl. Discov., 2004)

Approximation Algorithms for Minimizing Empirical Error by Axis-Parallel Hyperplanes. - Tapio Elomaa; Jussi Kujala; Juho Rousu (ECML, 2005)

Planning isotopomer measurements for estimation of metabolic fluxes. - Ari Rantanen; Taneli Mielikäinen; Juho Rousu; Esko Ukkonen (German Conference on Bioinformatics, 2005)

Learning hierarchical multi-category text classification models. - Juho Rousu; Craig Saunders; Sándor Szedmák; John Shawe-Taylor (ICML, 2005)

Finding Feasible Pathways in Metabolic Networks. - Esa Pitkänen; Ari Rantanen; Juho Rousu; Esko Ukkonen (Panhellenic Conference on Informatics, 2005)

Efficient Computation of Gapped Substring Kernels on Large Alphabets. - Juho Rousu; John Shawe-Taylor (J. Mach. Learn. Res., 2005)

Ab Initio Prediction of Molecular Fragments from Tandem Mass Spectrometry Data. - Markus Heinonen; Ari Rantanen; Taneli Mielikäinen; Esa Pitkänen; Juha Kokkonen; Juho Rousu (German Conference on Bioinformatics, 2006)

Practical Approximation of Optimal Multivariate Discretization. - Tapio Elomaa; Jussi Kujala; Juho Rousu (ISMIS, 2006)

Planning optimal measurements of isotopomer distributions for estimation of metabolic fluxes. - Ari Rantanen; Taneli Mielikäinen; Juho Rousu; Hannu Maaheimo; Esko Ukkonen (Bioinform., 2006)

Kernel-Based Learning of Hierarchical Multilabel Classification Models. - Juho Rousu; Craig Saunders; Sándor Szedmák; John Shawe-Taylor (J. Mach. Learn. Res., 2006)

Equivalence of Metabolite Fragments and Flow Analysis of Isotopomer Distributions for Flux Estimation. - Ari Rantanen; Hannu Maaheimo; Esa Pitkänen; Juho Rousu; Esko Ukkonen (Trans. Comp. Sys. Biology, 2006)

Probabilistic modeling and machine learning in structural and systems biology. - Samuel Kaski; Juho Rousu; Esko Ukkonen (BMC Bioinform., 2007)

Information Theoretic Methods for Bioinformatics. - Jorma Rissanen; Peter D. Grünwald; Jukka Heikkonen; Petri Myllymäki; Teemu Roos; Juho Rousu (EURASIP J. Bioinform. Syst. Biol., 2007)

A Computational Method for Reconstructing Gapless Metabolic Networks. - Esa Pitkänen; Ari Rantanen; Juho Rousu; Esko Ukkonen (BIRD, 2008)

Efficient Discriminative Training Method for Structured Predictions. - Huizhen Yu; Dimitri P. Bertsekas; Juho Rousu (MLG@ICML, 2008)

An analytic and systematic framework for estimating metabolic flux ratios from 13C tracer experiments. - Ari Rantanen; Juho Rousu; Paula Jouhten; Nicola Zamboni; Hannu Maaheimo; Esko Ukkonen (BMC Bioinform., 2008)

Inferring branching pathways in genome-scale metabolic networks. - Esa Pitkänen; Paula Jouhten; Juho Rousu (BMC Syst. Biol., 2009)

Structured Output Prediction of Novel Enzyme Function with Reaction Kernels. - Katja Astikainen; Liisa Holm; Esa Pitkänen; Sándor Szedmák; Juho Rousu (BIOSTEC (Selected Papers), 2010)

Reaction Kernels - Structured Output Prediction Approaches for Novel Enzyme Function. - Katja Astikainen; Esa Pitkänen; Juho Rousu; Liisa Holm; Sándor Szedmák (BIOINFORMATICS, 2010)

Structured Output Prediction of Anti-cancer Drug Activity. - Hongyu Su; Markus Heinonen; Juho Rousu (PRIB, 2010)

Preface. - Saso Dzeroski; Pierre Geurts; Juho Rousu (MLSB, 2010)

Reconstructing Gapless Ancestral Metabolic Networks. - Esa Pitkänen; Mikko Arvas; Juho Rousu (BIOSTEC (Selected Papers), 2011)

Minimum Mutation Algorithm for Gapless Metabolic Network Evolution. - Esa Pitkänen; Juho Rousu; Mikko Arvas (BIOINFORMATICS, 2011)

Multi-task Drug Bioactivity Classification with Graph Labeling Ensembles. - Hongyu Su; Juho Rousu (PRIB, 2011)

Computing Atom Mappings for Biochemical Reactions without Subgraph Isomorphism. - Markus Heinonen; Sampsa Lappalainen; Taneli Mielikäinen; Juho Rousu (J. Comput. Biol., 2011)

Efficient Path Kernels for Reaction Function Prediction. - Markus Heinonen; Niko Välimäki; Veli Mäkinen; Juho Rousu (BIOINFORMATICS, 2012)

Metabolite identification and molecular fingerprint prediction through machine learning. - Markus Heinonen; Huibin Shen; Nicola Zamboni; Juho Rousu (Bioinform., 2012)

Multilabel Classification throughout Random Graph Ensembles. - Hongyu Su; Juho Rousu (CoRR, 2013)

Biomarker Discovery by Sparse Canonical Correlation Analysis of Complex Clinical Phenotypes of Tuberculosis and Malaria. - Juho Rousu; Daniel D. Agranoff; Olugbemiro Sodeinde; John Shawe-Taylor; Delmiro Fernandez-Reyes (PLoS Comput. Biol., 2013)

Structured Prediction of Network Response. - Hongyu Su; Aristides Gionis; Juho Rousu (ICML, 2014)

Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov Networks. - Mario Marchand; Hongyu Su; Emilie Morvant; Juho Rousu; John Shawe-Taylor (NIPS, 2014)

Metabolite identification through multiple kernel learning on fragmentation trees. - Huibin Shen; Kai Dührkop; Sebastian Böcker; Juho Rousu (Bioinform., 2014)

Comparative Genome-Scale Reconstruction of Gapless Metabolic Networks for Present and Ancestral Species. - Esa Pitkänen; Paula Jouhten; Jian Hou 007; Muhammad Fahad Syed; Peter Blomberg; Jana Kludas; Merja Oja; Liisa Holm; Merja Penttilä; Juho Rousu; Mikko Arvas (PLoS Comput. Biol., 2014)

Canonical Correlation Methods for Exploring Microbe-Environment Interactions in Deep Subsurface. - Viivi Uurtio; Malin Bomberg; Kristian Nybo; Merja Itävaara; Juho Rousu (Discovery Science, 2015)

Computational Metabolomics (Dagstuhl Seminar 15492). - Sebastian Böcker; Juho Rousu; Emma Schymanski (Dagstuhl Reports, 2015)

Multilabel classification through random graph ensembles. - Hongyu Su; Juho Rousu (Mach. Learn., 2015)

Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo. - Markus Heinonen; Henrik Mannerström; Juho Rousu; Samuel Kaski; Harri Lähdesmäki (AISTATS, 2016)

Soft Kernel Target Alignment for Two-Stage Multiple Kernel Learning. - Huibin Shen; Sándor Szedmák; Céline Brouard; Juho Rousu (DS, 2016)

Fast metabolite identification with Input Output Kernel Regression. - Céline Brouard; Huibin Shen; Kai Dührkop; Florence d'Alché-Buc; Sebastian Böcker; Juho Rousu (Bioinform., 2016)

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis. - Anna Cichonska; Juho Rousu; Pekka Marttinen; Antti J. Kangas; Pasi Soininen; Terho Lehtimäki; Olli T. Raitakari; Marjo-Riitta Järvelin; Veikko Salomaa; Mika Ala-Korpela; Samuli Ripatti; Matti Pirinen (Bioinform., 2016)

Selected proceedings of Machine Learning in Systems Biology: MLSB 2016. - Aalt D. J. van Dijk; Harri Lähdesmäki; Dick de Ridder; Juho Rousu (BMC Bioinform., 2016)

Magnitude-Preserving Ranking for Structured Outputs. - Céline Brouard; Eric Bach 002; Sebastian Böcker; Juho Rousu (ACML, 2017)

Critical Assessment of Small Molecule Identification 2016: automated methods. - Emma Schymanski; Christoph Ruttkies; Martin Krauss; Céline Brouard; Tobias Kind; Kai Dührkop; Felicity Allen; Arpana Vaniya; Dries Verdegem; Sebastian Böcker; Juho Rousu; Huibin Shen; et al. (J. Cheminformatics, 2017)

Multi-view kernel completion. - Sahely Bhadra; Samuel Kaski; Juho Rousu (Mach. Learn., 2017)

Computational-experimental approach to drug-target interaction mapping: A case study on kinase inhibitors. - Anna Cichonska; Balaguru Ravikumar; Elina Parri; Sanna Timonen; Tapio Pahikkala; Antti Airola; Krister Wennerberg; Juho Rousu; Tero Aittokallio (PLoS Comput. Biol., 2017)

Sparse Non-linear CCA through Hilbert-Schmidt Independence Criterion. - Viivi Uurtio; Sahely Bhadra; Juho Rousu (ICDM, 2018)

Liquid-chromatography retention order prediction for metabolite identification. - Eric Bach 002; Sándor Szedmák; Céline Brouard; Sebastian Böcker; Juho Rousu (Bioinform., 2018)

Principal metabolic flux mode analysis. - Sahely Bhadra; Peter Blomberg; Sandra Castillo; Juho Rousu (Bioinform., 2018)

Learning with multiple pairwise kernels for drug bioactivity prediction. - Anna Cichonska; Tapio Pahikkala; Sándor Szedmák; Heli Julkunen; Antti Airola; Markus Heinonen; Tero Aittokallio; Juho Rousu (Bioinform., 2018)

A Tutorial on Canonical Correlation Methods. - Viivi Uurtio; João M. Monteiro; Jaz S. Kandola; John Shawe-Taylor; Delmiro Fernandez-Reyes; Juho Rousu (ACM Comput. Surv., 2018)

Large-Scale Sparse Kernel Canonical Correlation Analysis. - Viivi Uurtio; Sahely Bhadra; Juho Rousu (ICML, 2019)

Bayesian metabolic flux analysis reveals intracellular flux couplings. - Markus Heinonen; Maria Osmala; Henrik Mannerström; Janne Wallenius; Samuel Kaski; Juho Rousu; Harri Lähdesmäki (Bioinform., 2019)

A Solution for Large Scale Nonlinear Regression with High Rank and Degree at Constant Memory Complexity via Latent Tensor Reconstruction. - Sándor Szedmák; Anna Cichonska; Heli Julkunen; Tapio Pahikkala; Juho Rousu (CoRR, 2020)

Learning Output Embeddings in Structured Prediction. - Luc Brogat-Motte; Alessandro Rudi; Céline Brouard; Juho Rousu; Florence d'Alché-Buc (CoRR, 2020)

Probabilistic framework for integration of mass spectrum and retention time information in small molecule identification. - Eric Bach 002; Simon Rogers; John Williamson 001; Juho Rousu (Bioinform., 2021)

Modeling drug combination effects via latent tensor reconstruction. - Tianduanyi Wang; Sándor Szedmák; Haishan Wang; Tero Aittokallio; Tapio Pahikkala; Anna Cichonska; Juho Rousu (Bioinform., 2021)

Learning primal-dual sparse kernel machines. - Riikka Huusari; Sahely Bhadra; Cécile Capponi; Hachem Kadri; Juho Rousu (CoRR, 2021)

Ranking microbial metabolomic and genomic links in the NPLinker framework using complementary scoring functions. - Grímur Hjörleifsson Eldjárn; Andrew Ramsay; Justin J. J. van der Hooft; Katherine R. Duncan; Sylvia Soldatou; Juho Rousu; Rónán Daly; Joe Wandy; Simon Rogers (PLoS Comput. Biol., 2021)

Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters. - Luc Brogat-Motte; Rémi Flamary; Céline Brouard; Juho Rousu; Florence d'Alché-Buc (ICML, 2022)

Vector-Valued Least-Squares Regression under Output Regularity Assumptions. - Luc Brogat-Motte; Alessandro Rudi; Céline Brouard; Juho Rousu; Florence d'Alché-Buc (J. Mach. Learn. Res., 2022)

Strain design optimization using reinforcement learning. - Maryam Sabzevari; Sándor Szedmák; Merja Penttilä; Paula Jouhten; Juho Rousu (PLoS Comput. Biol., 2022)

Joint structural annotation of small molecules using liquid chromatography retention order and tandem mass spectrometry data. - Eric Bach 002; Emma Schymanski; Juho Rousu (Nat. Mac. Intell., 2022)

MassSpecGym: A benchmark for the discovery and identification of molecules. - Roman Bushuiev; Anton Bushuiev; Niek F. de Jonge; Adamo Young; Fleming Kretschmer; Raman Samusevich; Janne Heirman; Fei Wang 062; Luke Zhang; Kai Dührkop; Marcus Ludwig; Nils A. Haupt; et al. (NeurIPS, 2024)

New methods for drug synergy prediction: a mini-review. - Fatemeh Abbasi; Juho Rousu (CoRR, 2024)

Scalable variable selection for two-view learning tasks with projection operators. - Sándor Szedmák; Riikka Huusari; Tat Hong Duong Le; Juho Rousu (Mach. Learn., 2024)

Protein function prediction through multi-view multi-label latent tensor reconstruction. - Robert Ebo Armah-Sekum; Sándor Szedmák; Juho Rousu (BMC Bioinform., 2024)

Learning symmetry-aware atom mapping in chemical reactions through deep graph matching. - Maryam Astero; Juho Rousu (J. Cheminformatics, 2024)

Scaling up drug combination surface prediction. - Riikka Huusari; Tianduanyi Wang; Sándor Szedmák; Diogo Dias; Tero Aittokallio; Juho Rousu (Briefings Bioinform., 2025)

Enhancing atom mapping with multitask learning and symmetry-aware deep graph matching. - Maryam Astero; Juho Rousu (J. Cheminformatics, 2025)