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Probabilistic Mechanistic Models for Genomics

We develop methods for efficient Bayesian inference in complex modelling problems. Our main applications are in developing statistical methods for modelling molecular biology time series based on Gaussian processes, as well as methods for RNA-sequencing and metagenomics data analysis.

Markus Nuorento

markus.nuorento@hiit.fi +358 50 344 7627 It specialist Helsinki Institute for Information Technology HIIT

HIIT at CSCW 2014: Network Hospitality and Account Sharing

Tue, 18.02.2014

HIIT researchers Airi Lampinen and Tapio Ikkala are contributing to timely debates on the sharing economy with their new research, published this week at the internationally renowned ACM CSCW 2014 conference. The conference is held this year in Baltimore in the United States. CSCW is the largest annual research conference focusing on computer-supported cooperative work.

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