Pekka Marttinen

Assistant Professor (Tenure track) in Machine Learning
M.Sc. in Applied Mathematics (University of Helsinki, 2004)
Ph.D. in Statistics (University of Helsinki, 2008)
Title of docent in Information and Computer Science (Aalto University, 2015)

Academy of Finland Research Fellow (started in September 2015)
Postal Address:
Helsinki Institute for Information Technology HIIT, Department of Computer Science
Aalto University
P.O.Box 15400
FIN-00076 AALTO, FINLAND
Street Address:
Room B334, Konemiehentie 2, Espoo, Finland
Email:
pekka.marttinen (at) aalto.fi

Research Interests



Articles in Journals

  1. Lintusaari, J., Vuollekoski, H., Kangasrääsiö, A., Skytén, K., Järvenpää, M., Marttinen, P., Gutmann, M., Vehtari, A., Corander, J., and Kaski, S. (2018). ELFI: Engine for Likelihood Free Inference. Journal of Machine Learning Research, in press. Preprint

  2. Sipola, A., Marttinen, P., and Corander, J. (2018). Bacmeta: simulator for genomic evolution in bacterial metapopulations. Bioinformatics, bty093. Available online

  3. Järvenpää, M., Gutmann, M., Vehtari, A., and Marttinen, P. (2018). Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria. Annals of Applied Statistics, Accepted for publication. Preprint

  4. Marttinen, P. and Hanage, W.P. (2017). Speciation trajectories in recombining bacterial species. PLOS Computational Biology, 13(7):e1005640. Available online

  5. David, S., Sanchez-Buso, L., Harris, S.R., Marttinen, P., Rusniok, C., Buchrieser, C., Harrison, T.G., and Parkhill, J. (2017). Dynamics and impact of homologous recombination on the evolution of Legionella pneumophila. PLOS Genetics, 13(6):e1006855. Available online

  6. Pirinen, M., Benner, C., Marttinen, P., Järvelin, M.-R., Rivas, M.A., and Ripatti, S. (2017). biMM: Efficient estimation of genetic variances and covariances for cohorts with high-dimensional phenotype measurements. Bioinformatics, 33(15):2405-2407. Available online

  7. Villa, P.M., Marttinen, P., Gillberg, L., Lokki, A.I., Majander, K., Taipale, P., Pesonen, A., Räikkönen, K., Hämäläinen, E., Kajantie, E., and Laivuori, H. (2017). Cluster Analysis to Estimate the Risk of Preeclampsia in the High-Risk Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) Study. PLoS ONE, 12(3): e0174399. Available online

  8. Mostowy, R., Croucher, N.J., Andam, C.P., Corander, J., Hanage, W.P., and Marttinen, P. (2017). Efficient inference of recent and ancestral recombination within bacterial populations. Molecular Biology and Evolution, 34(5):1167-1182. Available online

    Pre-print

  9. Harms, K., Lunnan, A., Hülter, N., Mourier, T., Vinner, L., Andam, C.P., Marttinen, P., Fridholm, H., Hansen, A.J., Hanage, W.P., Nielsen, K.M., Willerslev, E., and Johnsen, P.J. (2016). Substitutions of short heterologous DNA segments of intra- or extragenomic origins produce clustered genomic polymorphisms. Proceedings of the National Academy of Sciences of the United States of America, 113(52):15066-15071. doi:10.1073/pnas.1615819114. Available online

  10. Lees, J.A., Vehkala, M., Välimäki, N., Harris, S.R., Chewapreecha, C., Croucher, N.J., Marttinen, P., Davies, M.R., Steer, A.C., Tong, S.Y.C., Honkela, A., Parkhill, J., Bentley, S.D., and Corander, J. (2016). Sequence element enrichment analysis to determine the genetic basis of bacterial phenotypes. Nature Communications, 7:12797, doi:10.1038/ncomms12797. Available online

  11. Gillberg, J., Marttinen, P., Pirinen, M., Kangas, A.-J., Soininen, P., Ali, M., Havulinna, A. S., Järvelin, M.-R., Ala-Korpela, M., and Kaski, S. (2016). Multiple output regression with latent noise. Journal of Machine Learning Research, 17:1-35. Available online

  12. Sieberts, S., Zhu, F., García-García, J., Stahl, E., Pratap, A., Pandey, G., Pappas, D., Aguilar, D., Anton, B., Bonet, J., Eksi, R., Fornés, O., Guney, E., Li, H., Marín, M., Panwar, B., Planas-Iglesias, J., Poglayen, D., Cui, J., Falcao, A., Suver, C., Hoff, B., Balagurusamy, V., Dillenberger, D., Chaibub Neto, E., Norman, T., Aittokallio, T., Ammad-ud-din, M., Azencott, C.-A., Bellón, V., Boeva, V., Bunte, K., Chheda, H., Cheng, L., Corander, J., Dumontier, M., Goldenberg, A., Gopalacharyulu, P., Hajiloo, M., Hidru, D., Jaiswal, A., Kaski, S., Khalfaoui, B., Khan, S., Kramer, E., Marttinen, P., Mezlini, A., Molparia, B., Pirinen, M., Saarela, J., Samwald, M., Stoven, V., Tang, H., Tang, J., Torkamani, A., Vert, J.P., Wang, B., Wang, T., Wennerberg, K., Wineinger, N., Xiao, G., Xie, Y., Yeung, R., Zhan, X., Zhao, C., Greenberg, J., Kremer, J., Michaud, K., Barton, A., Coenen, M., Mariette, X., Miceli, C., Shadick, N., Weinblatt, M., de Vries, N, Tak, P., Gerlag, D., Huizinga, T.W.J., Kurreeman, F., Allaart, C., Bridges, S., Criswell, L., Moreland, L., Klareskog, L., Saevarsdottir, S., Padyukov, L., Gregersen, P., Friend, S., Plenge, R., Stolovitzky, G., Oliva, B., Guan, Y., and Mangravite, L. (2016). Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis. Nature Communications, 7:12460, doi:10.1038/ncomms12460 Available online

  13. Numminen, E., Gutmann, M., Shubin, M., Marttinen, P., Meric, G.,van Schaik, W., Coque, T., Baquero, F., Willems, R., Sheppard, S., Feil, E., Hanage, W.P., and Corander, J. (2016). The impact of host metapopulation structure on the population genetics of colonizing bacteria. Journal of Theoretical Biology, 396: 53-62. Pre-print

  14. Cichonska, A., Rousu, J., Marttinen, P., Kangas, A.J., Soininen, P., Lehtimäki, T., Raitakari, O.T., Järvelin, M.-R., Salomaa, V., Ala-Korpela, M., Ripatti, S. and Pirinen, M. (2016). metaCCA: Summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis. Bioinformatics, 32(13):1981-1989, doi: 10.1093/bioinformatics, Available online

  15. Marttinen, P., Croucher, N.J., Gutmann, M.U., Corander, J. and Hanage, W.P. (2015). Recombination produces coherent bacterial species clusters in both core and accessory genomes. Microbial Genomics, 1, doi:10.1099/mgen.0.000038, Available online (Supplement)

  16. Chewapreecha, C., Marttinen, P., Croucher, N.J.,Salter, S.J., Harris, S.R., Mather, A.E.,Hanage, W.P., Goldblatt, D., Nosten, F.H., Turner, C., Turner, P., Bentley, S.D. and Parkhill, J. (2014). Comprehensive identification of single nucleotide polymorphisms associated with beta-lactam resistance within pneumococcal mosaic genes. PLoS Genetics, 10(8):e1004547. doi:10.1371/journal.pgen.1004547

  17. Sheppard, S.K., Cheng, L., Méric, G., de Haan, C.P.A., Llarena, A.-K., Marttinen, P., Vidal, A., Ridley, A., Clifton-Hadley, F., Connor, T.R., Strachan, N.J.C, Forbes, K., Colles, F.M., Jolley, K.A., Bentley, S.D., Maiden, M.C.J., Hänninen, M.-L., Parkhill, J., Hanage, W.P. and Corander, J. (2014). Cryptic ecology among host generalist Campylobacter jejuni in domestic animals. Molecular Ecology, 23(10):2442-51. doi: 10.1111/mec.12742

  18. Kashtan, N., Roggensack, S.E., Rodrigue, S., Thompson, J.W., Biller, S.J., Coe, A., Ding, H., Marttinen, P., Malmstrom, R.R., Stocker, R., Follows, M.J., Stepanauskas, R. and Chisholm, S.W. (2014). Single-cell genomics reveals hundreds of coexisting subpopulations in wild Prochlorococcus. Science, 344(6182): 416-420.

  19. Marttinen, P., Pirinen, M., Sarin, A.P., Gillberg, J., Kettunen, J., Surakka, I., Kangas, A.J., Soininen, P., O’Reilly, P.F., Kaakinen, M., Kähönen, M., Lehtimäki, T., Ala-Korpela, M., Raitakari, O.T., Salomaa, V., Järvelin, M.-R., Ripatti, S. and Kaski, S. (2014). Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression. Bioinformatics, 30(14):2026-34. doi: 10.1093/bioinformatics/btu140

  20. Chewapreecha, C., Harris, S.R., Croucher, N.J., Turner, C., Marttinen, P., Cheng, L., Pessia, A., Aanensen, D.M., Mather, A.E., Page, A.J., Salter, S.J., Harris, D., Nosten, F., Goldblatt, D., Corander, J., Parkhill, J., Turner, P. and Bentley, S.D. (2014). Dense genomic sampling identifies highways of pneumococcal recombination. Nature Genetics, 46: 305-309.

  21. Marttinen, M., Pajari, A.-M., Päivärinta, E., Storvik, M., Marttinen, P., Nurmi, T., Niku, M., Piironen, V. and Mutanen, M. (2014). Plant sterol feeding induces tumor formation and alters sterol metabolism in the intestine of ApcMin mice. Nutrition and Cancer: An International Journal, 66(2). doi: 10.1080/01635581.2014.865244

  22. Marttinen, P., Gillberg, J., Havulinna, A., Corander, J. and Kaski, S. (2013). Genome-wide association studies with high-dimensional phenotypes. Statistical Applications in Genetics and Molecular Biology, 12(4): 413-431.

  23. Castillo-Ramírez, S., Corander, J., Marttinen, P., Aldeljawi, M., Hanage, W.P., Westh, H., Boye, K.,Gulay, Z., Bentley, S.D., Parkhill, J., Holden M.T. and Feil, E.J. (2012). Phylogeographic variation in recombination rates within a global clone of Methicillin-Resistant Staphylococcus aureus (MRSA). Genome Biology, 13(12):R126. doi:10.1186/gb-2012-13-12-r126

  24. Peltola, T., Marttinen P., and Vehtari, A. (2012). Finite Adaptation and Multistep Moves in the Metropolis-Hastings Algorithm for Variable Selection in Genome-Wide Association Analysis. PLoS ONE, 7(11): e49445. doi:10.1371/journal.pone.0049445

  25. Delezuch, W., Marttinen, P., Kokki, H., Heikkinen, M., Lintula, H., Vanamo, K., Pulkki, K. and Matinlauri, I. (2012). Serum and CSF soluble CD26 and CD30 concentrations in healthy pediatric surgical outpatients. Tissue antigens, doi: 10.1111/j.1399-0039.2012.01938.x.

  26. Peltola, T., Marttinen, P., Jula, A., Salomaa, V., Perola, M. and Vehtari, A. (2012). Bayesian variable selection in searching for additive and dominant effects in genome-wide data. PLoS ONE, 7(1): e29115. doi:10.1371/journal.pone.0029115.

  27. Marttinen, P., Hanage, W.P., Nicholas, J.C., Connor, T.C., Harris, S.R., Bentley, S.D. and Corander, J. (2012). Detection of recombination events in bacterial genomes from large population samples. Nucleic Acids Research, 40(1): e6. doi: 10.1093/nar/gkr928.

  28. Sirén, J., Marttinen, P. and Corander, J. (2010). Reconstructing population histories from single-nucleotide polymorphism data. Molecular Biology and Evolution, 28(1):673-683.

  29. Marttinen, P. and Corander, J. (2010). Efficient Bayesian approach for multilocus association mapping including gene-gene interactions. BMC Bioinformatics, 11:443.

  30. Törönen, P., Ojala, P.J., Marttinen, P. and Holm, L. (2009). Robust extraction of functional signals from gene set analysis using a generalized threshold free scoring function. BMC Bioinformatics, 10:307.

  31. Marttinen, P., Myllykangas, S. and Corander, J. (2009). Bayesian clustering and feature selection for cancer tissue samples. BMC Bioinformatics, 10:90.

  32. Marttinen, P. and Corander, J. (2009). Bayesian learning of graphical vector autoregressions with unequal lag-lengths. Machine Learning, 75:217-243.

  33. Marttinen, P., Tang, J., De Baets, B., Dawyndt, P. and Corander, J. (2009). Bayesian clustering of fuzzy feature vectors using a quasi-likelihood approach. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31:74-85.

  34. Corander, J., Marttinen, P., Sirén, J. and Tang, J. (2008). Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations. BMC Bioinformatics, 9:539.

  35. Marttinen, P., Baldwin, A., Hanage, W.P., Dowson, C., Mahenthiralingam, E. and Corander, J. (2008). Bayesian modeling of recombination events in bacterial populations. BMC Bioinformatics, 9:421.

  36. Marttinen, P., Corander, J., Törönen, P. and Holm, L. (2006). Bayesian search of functionally divergent protein subgroups and their function specific residues. Bioinformatics, 22:2466-2474.

  37. Corander, J. and Marttinen, P. (2006). Bayesian identification of admixture events using multi-locus molecular markers. Molecular Ecology, 15:2833-2843.

  38. Corander, J., Marttinen, P. and Mäntyniemi, S. (2006). Bayesian identification of stock mixtures from molecular marker data. Fishery Bulletin, 104:550-558.

  39. Corander, J. and Marttinen, P. (2006). Bayesian model learning based on predictive entropy. Journal of Logic, Language and Information, 15:5-20.

  40. Corander, J., Waldmann, P., Marttinen, P. and Sillanpää, M.J. (2004). BAPS 2: enhanced possibilities for the analysis of genetic population structure. Bioinformatics, 20:2363-2369.

Articles in Conference Proceedings

  1. Sundin, I.*, Peltola, T.*, Micallef, L., Afrabandpey, H., Soare, M., Majumder, M.M., Daee, P., He, C., Serim, B., Havulinna, A., Heckman, C., Jacucci, G., Marttinen, P., and Kaski, S. (2018). Improving genomics-based predictions for precision medicine through active elicitation of expert knowledge. Proceedings of the 26th Conference on Intelligent Systems for Molecular Biology (ISMB 2018), Accepted for publication. (*equal contribution)

  2. Micallef, L.*, Sundin, I.*, Marttinen, P.*, Ammad-ud-din. M., Peltola, T., Soare, M., Jacucci, G., and Kaski, S. (2017). Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets. Proceedings of the 22nd International Conference on Intelligent User Interfaces (IUI '17), accepted for publication. (*equal contribution)

Theses

Software

I have authored/co-authored the following software:

Teaching