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ORCIDJuho Rousu
Person information
- affiliation: Aalto University, Espoo, Finland
- affiliation (former): University of Helsinki, Finland
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2020 – today
- 2024
[j40]Robert Ebo Armah-Sekum
, Sándor Szedmák, Juho Rousu:
Protein function prediction through multi-view multi-label latent tensor reconstruction. BMC Bioinform. 25(1): 174 (2024)- [j39]Maryam Astero, Juho Rousu:
Learning symmetry-aware atom mapping in chemical reactions through deep graph matching. J. Cheminformatics 16(1): 46 (2024) - [j38]Sándor Szedmák, Riikka Huusari, Tat Hong Duong Le, Juho Rousu:
Scalable variable selection for two-view learning tasks with projection operators. Mach. Learn. 113(6): 3525-3544 (2024) - [i12]Fatemeh Abbasi, Juho Rousu:
New methods for drug synergy prediction: a mini-review. CoRR abs/2404.02484 (2024) - 2023
- [i11]Sándor Szedmák, Riikka Huusari, Tat Hong Duong Le, Juho Rousu:
Scalable variable selection for two-view learning tasks with projection operators. CoRR abs/2307.01558 (2023) - 2022
- [j37]Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc:
Vector-Valued Least-Squares Regression under Output Regularity Assumptions. J. Mach. Learn. Res. 23: 344:1-344:50 (2022) - [j36]Eric Bach, Emma Schymanski, Juho Rousu:
Joint structural annotation of small molecules using liquid chromatography retention order and tandem mass spectrometry data. Nat. Mac. Intell. 4(12): 1224-1237 (2022) - [j35]Maryam Sabzevari, Sándor Szedmák, Merja Penttilä, Paula Jouhten, Juho Rousu:
Strain design optimization using reinforcement learning. PLoS Comput. Biol. 18(6) (2022) - [c40]Luc Brogat-Motte, Rémi Flamary, Céline Brouard, Juho Rousu, Florence d'Alché-Buc:
Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters. ICML 2022: 2321-2335 - [i10]Luc Brogat-Motte, Rémi Flamary, Céline Brouard, Juho Rousu, Florence d'Alché-Buc:
Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters. CoRR abs/2202.03813 (2022) - [i9]Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc:
Vector-Valued Least-Squares Regression under Output Regularity Assumptions. CoRR abs/2211.08958 (2022) - 2021
- [j34]Eric Bach, Simon Rogers, John Williamson, Juho Rousu:
Probabilistic framework for integration of mass spectrum and retention time information in small molecule identification. Bioinform. 37(12): 1724-1731 (2021) - [j33]Tianduanyi Wang, Sándor Szedmák, Haishan Wang, Tero Aittokallio, Tapio Pahikkala, Anna Cichonska, Juho Rousu:
Modeling drug combination effects via latent tensor reconstruction. Bioinform. 37(Supplement): 93-101 (2021) - [j32]Grímur Hjörleifsson Eldjárn, Andrew Ramsay, Justin J. J. van der Hooft, Katherine R. Duncan, Sylvia Soldatou, Juho Rousu, Rónán Daly, Joe Wandy, Simon Rogers:
Ranking microbial metabolomic and genomic links in the NPLinker framework using complementary scoring functions. PLoS Comput. Biol. 17(5) (2021) - [i8]Riikka Huusari, Sahely Bhadra, Cécile Capponi, Hachem Kadri, Juho Rousu:
Learning primal-dual sparse kernel machines. CoRR abs/2108.12199 (2021) - 2020
- [i7]Sándor Szedmák, Anna Cichonska, Heli Julkunen, Tapio Pahikkala, Juho Rousu:
A Solution for Large Scale Nonlinear Regression with High Rank and Degree at Constant Memory Complexity via Latent Tensor Reconstruction. CoRR abs/2005.01538 (2020) - [i6]Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d'Alché-Buc:
Learning Output Embeddings in Structured Prediction. CoRR abs/2007.14703 (2020)
2010 – 2019
- 2019
- [j31]Markus Heinonen, Maria Osmala, Henrik Mannerström, Janne Wallenius, Samuel Kaski, Juho Rousu, Harri Lähdesmäki:
Bayesian metabolic flux analysis reveals intracellular flux couplings. Bioinform. 35(14): i548-i557 (2019) - [c39]Viivi Uurtio, Sahely Bhadra, Juho Rousu:
Large-Scale Sparse Kernel Canonical Correlation Analysis. ICML 2019: 6383-6391 - 2018
- [j30]Anna Cichonska, Tapio Pahikkala, Sándor Szedmák, Heli Julkunen, Antti Airola, Markus Heinonen, Tero Aittokallio, Juho Rousu:
Learning with multiple pairwise kernels for drug bioactivity prediction. Bioinform. 34(13): i509-i518 (2018) - [j29]Sahely Bhadra, Peter Blomberg, Sandra Castillo, Juho Rousu:
Principal metabolic flux mode analysis. Bioinform. 34(14): 2409-2417 (2018) - [j28]Eric Bach, Sándor Szedmák, Céline Brouard, Sebastian Böcker, Juho Rousu:
Liquid-chromatography retention order prediction for metabolite identification. Bioinform. 34(17): i875-i883 (2018) - [j27]Viivi Uurtio, João M. Monteiro, Jaz S. Kandola, John Shawe-Taylor, Delmiro Fernandez-Reyes, Juho Rousu:
A Tutorial on Canonical Correlation Methods. ACM Comput. Surv. 50(6): 95:1-95:33 (2018) - [c38]Viivi Uurtio, Sahely Bhadra, Juho Rousu:
Sparse Non-linear CCA through Hilbert-Schmidt Independence Criterion. ICDM 2018: 1278-1283 - [i5]Markus Heinonen, Maria Osmala, Henrik Mannerström, Janne Wallenius, Samuel Kaski, Juho Rousu, Harri Lähdesmäki:
Bayesian Metabolic Flux Analysis reveals intracellular flux couplings. CoRR abs/1804.06673 (2018) - 2017
- [j26]Emma Schymanski, Christoph Ruttkies, Martin Krauss, Céline Brouard, Tobias Kind, Kai Dührkop, Felicity Allen, Arpana Vaniya, Dries Verdegem, Sebastian Böcker, Juho Rousu, Huibin Shen, Hiroshi Tsugawa, Tanvir Sajed, Oliver Fiehn, Bart Ghesquière, Steffen Neumann:
Critical Assessment of Small Molecule Identification 2016: automated methods. J. Cheminformatics 9(1): 22:1-22:21 (2017) - [j25]Sahely Bhadra, Samuel Kaski, Juho Rousu:
Multi-view kernel completion. Mach. Learn. 106(5): 713-739 (2017) - [j24]Anna Cichonska, Balaguru Ravikumar, Elina Parri, Sanna Timonen, Tapio Pahikkala, Antti Airola, Krister Wennerberg, Juho Rousu, Tero Aittokallio:
Computational-experimental approach to drug-target interaction mapping: A case study on kinase inhibitors. PLoS Comput. Biol. 13(8) (2017) - [c37]Céline Brouard, Eric Bach, Sebastian Böcker, Juho Rousu:
Magnitude-Preserving Ranking for Structured Outputs. ACML 2017: 407-422 - [i4]Viivi Uurtio, João M. Monteiro, Jaz S. Kandola, John Shawe-Taylor, Delmiro Fernandez-Reyes, Juho Rousu:
A Tutorial on Canonical Correlation Methods. CoRR abs/1711.02391 (2017) - 2016
- [j23]Céline Brouard, Huibin Shen, Kai Dührkop, Florence d'Alché-Buc, Sebastian Böcker, Juho Rousu:
Fast metabolite identification with Input Output Kernel Regression. Bioinform. 32(12): 28-36 (2016) - [j22]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:
metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis. Bioinform. 32(13): 1981-1989 (2016) - [j21]Aalt D. J. van Dijk, Harri Lähdesmäki, Dick de Ridder, Juho Rousu:
Selected proceedings of Machine Learning in Systems Biology: MLSB 2016. BMC Bioinform. 17(S-16): 51-52 (2016) - [c36]Markus Heinonen, Henrik Mannerström, Juho Rousu, Samuel Kaski, Harri Lähdesmäki:
Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo. AISTATS 2016: 732-740 - [c35]Huibin Shen, Sándor Szedmák, Céline Brouard, Juho Rousu:
Soft Kernel Target Alignment for Two-Stage Multiple Kernel Learning. DS 2016: 427-441 - [i3]Sahely Bhadra, Samuel Kaski, Juho Rousu:
Multi-view Kernel Completion. CoRR abs/1602.02518 (2016) - 2015
- [j20]Hongyu Su, Juho Rousu:
Multilabel classification through random graph ensembles. Mach. Learn. 99(2): 231-256 (2015) - [c34]Viivi Uurtio, Malin Bomberg, Kristian Nybo, Merja Itävaara, Juho Rousu:
Canonical Correlation Methods for Exploring Microbe-Environment Interactions in Deep Subsurface. Discovery Science 2015: 299-307 - [i2]Sebastian Böcker, Juho Rousu, Emma Schymanski:
Computational Metabolomics (Dagstuhl Seminar 15492). Dagstuhl Reports 5(11): 180-192 (2015) - 2014
- [j19]Huibin Shen, Kai Dührkop, Sebastian Böcker, Juho Rousu:
Metabolite identification through multiple kernel learning on fragmentation trees. Bioinform. 30(12): 157-164 (2014) - [j18]Esa Pitkänen, Paula Jouhten, Jian Hou, Muhammad Fahad Syed, Peter Blomberg, Jana Kludas, Merja Oja, Liisa Holm, Merja Penttilä, Juho Rousu, Mikko Arvas:
Comparative Genome-Scale Reconstruction of Gapless Metabolic Networks for Present and Ancestral Species. PLoS Comput. Biol. 10(2) (2014) - [c33]Hongyu Su, Aristides Gionis, Juho Rousu:
Structured Prediction of Network Response. ICML 2014: 442-450 - [c32]Mario Marchand, Hongyu Su, Emilie Morvant, Juho Rousu, John Shawe-Taylor:
Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov Networks. NIPS 2014: 873-881 - 2013
- [j17]Juho Rousu, Daniel D. Agranoff, Olugbemiro Sodeinde, John Shawe-Taylor, Delmiro Fernandez-Reyes:
Biomarker Discovery by Sparse Canonical Correlation Analysis of Complex Clinical Phenotypes of Tuberculosis and Malaria. PLoS Comput. Biol. 9(4) (2013) - [c31]Hongyu Su, Juho Rousu:
Multilabel Classification through Random Graph Ensembles. ACML 2013: 404-418 - [i1]Hongyu Su, Juho Rousu:
Multilabel Classification throughout Random Graph Ensembles. CoRR abs/1310.8428 (2013) - 2012
- [j16]Markus Heinonen, Huibin Shen, Nicola Zamboni, Juho Rousu:
Metabolite identification and molecular fingerprint prediction through machine learning. Bioinform. 28(18): 2333-2341 (2012) - [c30]Markus Heinonen, Niko Välimäki, Veli Mäkinen, Juho Rousu:
Efficient Path Kernels for Reaction Function Prediction. BIOINFORMATICS 2012: 202-207 - 2011
- [j15]Markus Heinonen, Sampsa Lappalainen, Taneli Mielikäinen, Juho Rousu:
Computing Atom Mappings for Biochemical Reactions without Subgraph Isomorphism. J. Comput. Biol. 18(1): 43-58 (2011) - [c29]Esa Pitkänen, Juho Rousu, Mikko Arvas:
Minimum Mutation Algorithm for Gapless Metabolic Network Evolution. BIOINFORMATICS 2011: 28-38 - [c28]Esa Pitkänen, Mikko Arvas, Juho Rousu:
Reconstructing Gapless Ancestral Metabolic Networks. BIOSTEC (Selected Papers) 2011: 126-140 - [c27]Hongyu Su, Juho Rousu:
Multi-task Drug Bioactivity Classification with Graph Labeling Ensembles. PRIB 2011: 157-167 - 2010
- [c26]Katja Astikainen, Esa Pitkänen, Juho Rousu, Liisa Holm, Sándor Szedmák:
Reaction Kernels - Structured Output Prediction Approaches for Novel Enzyme Function. BIOINFORMATICS 2010: 48-55 - [c25]Katja Astikainen, Liisa Holm, Esa Pitkänen, Sándor Szedmák, Juho Rousu:
Structured Output Prediction of Novel Enzyme Function with Reaction Kernels. BIOSTEC (Selected Papers) 2010: 367-379 - [c24]Hongyu Su, Markus Heinonen, Juho Rousu:
Structured Output Prediction of Anti-cancer Drug Activity. PRIB 2010: 38-49 - [c23]Saso Dzeroski, Pierre Geurts, Juho Rousu:
Preface. MLSB 2010: 1-2 - [e1]Saso Dzeroski, Pierre Geurts, Juho Rousu:
Proceedings of the third International Workshop on Machine Learning in Systems Biology, MLSB 2009, Ljubljana, Slovenia, September 5-6, 2009. JMLR Proceedings 8, JMLR.org 2010 [contents]
2000 – 2009
- 2009
- [j14]Esa Pitkänen, Paula Jouhten, Juho Rousu:
Inferring branching pathways in genome-scale metabolic networks. BMC Syst. Biol. 3: 103 (2009) - 2008
- [j13]Ari Rantanen, Juho Rousu, Paula Jouhten, Nicola Zamboni, Hannu Maaheimo, Esko Ukkonen:
An analytic and systematic framework for estimating metabolic flux ratios from 13C tracer experiments. BMC Bioinform. 9 (2008) - [c22]Esa Pitkänen, Ari Rantanen, Juho Rousu, Esko Ukkonen:
A Computational Method for Reconstructing Gapless Metabolic Networks. BIRD 2008: 288-302 - 2007
- [j12]Samuel Kaski, Juho Rousu, Esko Ukkonen:
Probabilistic modeling and machine learning in structural and systems biology. BMC Bioinform. 8(S-2) (2007) - [j11]Jorma Rissanen, Peter D. Grünwald, Jukka Heikkonen, Petri Myllymäki, Teemu Roos, Juho Rousu:
Information Theoretic Methods for Bioinformatics. EURASIP J. Bioinform. Syst. Biol. 2007 (2007) - 2006
- [j10]Ari Rantanen, Taneli Mielikäinen, Juho Rousu, Hannu Maaheimo, Esko Ukkonen:
Planning optimal measurements of isotopomer distributions for estimation of metabolic fluxes. Bioinform. 22(10): 1198-1206 (2006) - [j9]Juho Rousu, Craig Saunders, Sándor Szedmák, John Shawe-Taylor:
Kernel-Based Learning of Hierarchical Multilabel Classification Models. J. Mach. Learn. Res. 7: 1601-1626 (2006) - [j8]Ari Rantanen, Hannu Maaheimo, Esa Pitkänen, Juho Rousu, Esko Ukkonen:
Equivalence of Metabolite Fragments and Flow Analysis of Isotopomer Distributions for Flux Estimation. Trans. Comp. Sys. Biology 6: 198-220 (2006) - [c21]Markus Heinonen, Ari Rantanen, Taneli Mielikäinen, Esa Pitkänen, Juha Kokkonen, Juho Rousu:
Ab Initio Prediction of Molecular Fragments from Tandem Mass Spectrometry Data. German Conference on Bioinformatics 2006: 40-53 - [c20]Tapio Elomaa, Jussi Kujala, Juho Rousu:
Practical Approximation of Optimal Multivariate Discretization. ISMIS 2006: 612-621 - 2005
- [j7]Juho Rousu, John Shawe-Taylor:
Efficient Computation of Gapped Substring Kernels on Large Alphabets. J. Mach. Learn. Res. 6: 1323-1344 (2005) - [c19]Tapio Elomaa, Jussi Kujala, Juho Rousu:
Approximation Algorithms for Minimizing Empirical Error by Axis-Parallel Hyperplanes. ECML 2005: 547-555 - [c18]Ari Rantanen, Taneli Mielikäinen, Juho Rousu, Esko Ukkonen:
Planning isotopomer measurements for estimation of metabolic fluxes. German Conference on Bioinformatics 2005: 177-191 - [c17]Juho Rousu, Craig Saunders, Sándor Szedmák, John Shawe-Taylor:
Learning hierarchical multi-category text classification models. ICML 2005: 744-751 - [c16]Esa Pitkänen, Ari Rantanen, Juho Rousu, Esko Ukkonen:
Finding Feasible Pathways in Metabolic Networks. Panhellenic Conference on Informatics 2005: 123-133 - 2004
- [j6]Tapio Elomaa, Juho Rousu:
Efficient Multisplitting Revisited: Optima-Preserving Elimination of Partition Candidates. Data Min. Knowl. Discov. 8(2): 97-126 (2004) - 2003
- [j5]Tapio Elomaa, Juho Rousu:
Necessary and Sufficient Pre-processing in Numerical Range Discretization. Knowl. Inf. Syst. 5(2): 162-182 (2003) - [c15]Juho Rousu, Ari Rantanen, Hannu Maaheimo, Esa Pitkänen, Katja Saarela, Esko Ukkonen:
A Method for Estimating Metabolic Fluxes from Incomplete Isotopomer Information. CMSB 2003: 88-103 - [c14]Tapio Elomaa, Juho Rousu:
On Decision Boundaries of Naïve Bayes in Continuous Domains. PKDD 2003: 144-155 - 2002
- [j4]Tapio Elomaa, Juho Rousu:
Linear-Time Preprocessing in Optimal Numerical Range Partitioning. J. Intell. Inf. Syst. 18(1): 55-70 (2002) - [c13]Tapio Elomaa, Juho Rousu:
Fast Minimum Training Error Discretization. ICML 2002: 131-138 - 2001
- [j3]Tapio Elomaa, Juho Rousu:
On the Computational Complexity of Optimal Multisplitting. Fundam. Informaticae 47(1-2): 35-52 (2001) - [j2]Juho Rousu, Robert J. Aarts:
An integrated approach to bioprocess recipe design. Integr. Comput. Aided Eng. 8(4): 363-373 (2001) - [c12]Tapio Elomaa, Juho Rousu:
Preprocessing Opportunities in Optimal Numerical Range Partitioning. ICDM 2001: 115-122 - 2000
- [c11]Tapio Elomaa, Juho Rousu:
Generalizing Boundary Points. AAAI/IAAI 2000: 570-576 - [c10]Tapio Elomaa, Juho Rousu:
On the Complexity of Optimal Multisplitting. ISMIS 2000: 552-561
1990 – 1999
- 1999
- [j1]Tapio Elomaa, Juho Rousu:
General and Efficient Multisplitting of Numerical Attributes. Mach. Learn. 36(3): 201-244 (1999) - [c9]Juho Rousu, Tapio Elomaa, Robert J. Aarts:
Predicting the Speed of Beer Fermentation in Laboratory and Industrial Scale. IWANN (2) 1999: 893-901 - [c8]Tapio Elomaa, Juho Rousu:
Speeding Up the Search for Optimal Partitions. PKDD 1999: 89-97 - 1998
- [c7]Tapio Elomaa, Juho Rousu:
Postponing the Evaluation of Attributes with a High Number of Boundary Points. PKDD 1998: 221-229 - 1997
- [c6]Robert J. Aarts, Juho Rousu:
Qualitative Knowledge to Support Reasoning About Cases. ICCBR 1997: 489-498 - [c5]Tapio Elomaa, Juho Rousu:
Well-Behaved Evaluation Functions for Numerical Attributes. ISMIS 1997: 147-156 - [c4]Tapio Elomaa, Juho Rousu:
Efficient Multisplitting on Numerical Data. PKDD 1997: 178-188 - [c3]Tapio Elomaa, Juho Rousu:
On the Well-Behavedness of Important Attribute Evaluation Functions. SCAI 1997: 95-106 - 1996
- [c2]Robert J. Aarts, Juho Rousu:
Towards CBR for Bioprocess Planning. EWCBR 1996: 16-27 - [c1]Juho Rousu, Robert J. Aarts:
Adaptation Cost as a Criterion for Solution Evaluation. EWCBR 1996: 354-361
Coauthor Index
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