Finding Consistent Gene Transmission Patterns on Large and Complex Pedigrees. - Matti Pirinen; Dario Gasbarra (IEEE ACM Trans. Comput. Biol. Bioinform., 2006)

Estimating genealogies from linked marker data: a Bayesian approach. - Dario Gasbarra; Matti Pirinen; Mikko J. Sillanpää; Elja Arjas (BMC Bioinform., 2007)

Estimating population haplotype frequencies from pooled SNP data using incomplete database information. - Matti Pirinen (Bioinform., 2009)

Estimating Haplotype Frequencies by Combining Data from Large DNA Pools with Database Information. - Dario Gasbarra; Sangita Kulathinal; Matti Pirinen; Mikko J. Sillanpää (IEEE ACM Trans. Comput. Biol. Bioinform., 2011)

Assessing association between protein truncating variants and quantitative traits. - Manuel A. Rivas; Matti Pirinen; Matthew J. Neville; Kyle J. Gaulton; Loukas Moutsianas; Cecilia M. Lindgren; Fredrik Karpe; Mark I. McCarthy; Peter Donnelly (Bioinform., 2013)

Bayesian Information Sharing Between Noise And Regression Models Improves Prediction of Weak Effects. - Jussi Gillberg; Pekka Marttinen; Matti Pirinen; Antti J. Kangas; Pasi Soininen; Marjo-Riitta Järvelin; Mika Ala-Korpela; Samuel Kaski (CoRR, 2013)

Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression. - Pekka Marttinen; Matti Pirinen; Antti-Pekka Sarin; Jussi Gillberg; Johannes Kettunen; Ida Surakka; Antti J. Kangas; Pasi Soininen; Paul F. O'Reilly; Marika Kaakinen; Mika Kähönen; Terho Lehtimäki; et al. (Bioinform., 2014)

Assessing allele-specific expression across multiple tissues from RNA-seq read data. - Matti Pirinen; Tuuli Lappalainen; Noah A. Zaitlen; Emmanouil T. Dermitzakis; Peter Donnelly; Mark I. McCarthy; Manuel A. Rivas (Bioinform., 2015)

FINEMAP: efficient variable selection using summary data from genome-wide association studies. - Christian Benner; Chris C. A. Spencer; Aki S. Havulinna; Veikko Salomaa; Samuli Ripatti; Matti Pirinen (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)

Multiple Output Regression with Latent Noise. - Jussi Gillberg; Pekka Marttinen; Matti Pirinen; Antti J. Kangas; Pasi Soininen; Mehreen Ali; Aki S. Havulinna; Marjo-Riitta Järvelin; Mika Ala-Korpela; Samuel Kaski (J. Mach. Learn. Res., 2016)

biMM: efficient estimation of genetic variances and covariances for cohorts with high-dimensional phenotype measurements. - Matti Pirinen; Christian Benner; Pekka Marttinen; Marjo-Riitta Järvelin; Manuel A. Rivas; Samuli Ripatti (Bioinform., 2017)

Differences in the Commonly used Genotype Imputation Algorithms and Their Imputation Accuracy Estimates. - Kalle Parn; Matti Pirinen; Mart Kals; Reedik Mägi; Veikko Salomaa; Michael Boehnke; Ira Hall; Nathan Stitziel; Nelson Freimer; Mark J. Daly; Aarno Palotie; Samuli Ripatti; et al. (eScience, 2018)

Machine learning in oral squamous cell carcinoma: Current status, clinical concerns and prospects for future - A systematic review. - Rasheed Omobolaji Alabi; Omar Youssef; Matti Pirinen; Mohammed Elmusrati 001; Antti A. Mäkitie; Ilmo Leivo; Alhadi Almangush (Artif. Intell. Medicine, 2021)

Comparison of nomogram with machine learning techniques for prediction of overall survival in patients with tongue cancer. - Rasheed Omobolaji Alabi; Antti A. Mäkitie; Matti Pirinen; Mohammed Elmusrati 001; Ilmo Leivo; Alhadi Almangush (Int. J. Medical Informatics, 2021)

linemodels: clustering effects based on linear relationships. - Matti Pirinen (Bioinform., 2023)

Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data. - Gabin Drouard; Juha Mykkänen; Jarkko Heiskanen; Joona Pohjonen; Saku Ruohonen; Katja Pahkala; Terho Lehtimäki; Xiaoling Wang; Miina Ollikainen; Samuli Ripatti; Matti Pirinen; Olli T. Raitakari; et al. (BMC Medical Informatics Decis. Mak., 2024)