Department of Computer Science

Computational Life Sciences

Research on Computational modelling, data analysis and design of biological systems.
Dna origami, illustration: Matti Ahlgren / Aalto University

The research area covers the multi-disciplinary activities on computational modelling, data analysis and design of biological systems. The field focuses on the development of original computational methods and their application in collaboration with leading national and international experts in different branches of life sciences.

The research area is linked to health-related research programmes in HIIT and FCAI, and Aalto key research areas of Health and Wellbeing as well as Materials and Sustainable Use of Natural Resources.

Research topics: bioinformatics, cheminformatics, complex systems, computational chemistry, computational immunology, computational metabolomics, computational systems biology, DNA nanotechnology, medical imaging, neuroinformatics, personalized medicine, pharmacoinformatics, statistical epidemology, synthetic biology.

Lääkäri juttelee lapsen kanssa

Researchers develop better way to determine safe drug doses for children

New research on organ maturation models could lead to improvements in drug development

: Kuvan on tehnyt Jani Huuhtanen -sovelluksella.

Artificial intelligence model developed by Finnish researchers predicts which key of the immune system opens the locks of coronavirus

With an artificial intelligence (AI) method developed by researchers at Aalto University and University of Helsinki, researchers can now link immune cells to their targets and for example uncouple which white blood cells recognize SARS-CoV-2. The developed tool has broad applications in understanding the function of immune system in infections, autoimmune disorders, and cancer.

Some medicine capsules and equations

AI predicts which drug combinations kill cancer cells

A machine learning model can help us treat cancer more effectively

Kuva: Matti Ahlgren.

Pekka Marttinen: It is very important to take good care of health and social services data

The DataLit project develops understandable and reliable practices for using health and social services data

Anna Cichonska by the sea photo Matti Ahlgren Aalto University

Anna Cichonska uses data science to develop better healthcare

Dr. Cichonska has received two awards for her dissertation and now she helps develop preventive medicine using data science

Illustration of neural networks in a hospital environment

Neural network for elderly care could save millions

A deep neural network model helps predict healthcare visits by elderly people, with the potential to save millions


Related research groups

Latest publications

Characterization of human T cell receptor repertoire data in eight thymus samples and four related blood samples

Nelli Heikkilä, Iivari Kleino, Reetta Vanhanen, Dawit A. Yohannes, Ilkka P. Mattila, Jari Saramäki, T. Petteri Arstila 2021 Data in Brief

Predicting recognition between T cell receptors and epitopes with TCRGP

Emmi Jokinen, Jani Huuhtanen, Satu Mustjoki, Markus Heinonen, Harri Lähdesmäki 2021 PLoS computational biology

Somatic mutations in lymphocytes in patients with immune-mediated aplastic anemia

Sofie Lundgren, Mikko A.I. Keränen, Matti Kankainen, Jani Huuhtanen, Gunilla Walldin, Cassandra M. Kerr, Michael Clemente, Freja Ebeling, Hanna Rajala, Oscar Brück, Harri Lähdesmäki, Sari Hannula, Tiina Hannunen, Pekka Ellonen, Neal S. Young, Seishi Ogawa, Jaroslaw P. Maciejewski, Eva Hellström-Lindberg, Satu Mustjoki 2021 Leukemia

The effects of seasons and weather on sleep patterns measured through longitudinal multimodal sensing

Stephen M. Mattingly, Ted Grover, Gonzalo J. Martinez, Talayeh Aledavood, Pablo Robles-Granda, Kari Nies, Aaron Striegel, Gloria Mark 2021 npj Digital Medicine

Congruent microbiome signatures in fibrosis-prone autoimmune diseases

Damian R. Plichta, Juhi Somani, Matthieu Pichaud, Zachary S. Wallace, Ana D. Fernandes, Cory A. Perugino, Harri Lähdesmäki, John H. Stone, Hera Vlamakis, Daniel C. Chung, Dinesh Khanna, Shiv Pillai, Ramnik J. Xavier 2021 GENOME MEDICINE

Latent Gaussian process with composite likelihoods and numerical quadrature


Longitudinal Variational Autoencoder

Siddharth Ramchandran, Gleb Tikhonov, Kalle Kujanpaa, Miika Koskinen, Harri Lahdesmaki 2021 24TH INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS (AISTATS)

Cotranscriptional Kinetic Folding of RNA Secondary Structures Including Pseudoknots

Vo Hong Thanh, Dani Korpela, Pekka Orponen 2021 JOURNAL OF COMPUTATIONAL BIOLOGY

lgpr: an interpretable non-parametric method for inferring covariate effects from longitudinal data

Juho Timonen, Henrik Mannerström, Aki Vehtari, Harri Lähdesmäki 2021 Bioinformatics

Modeling drug combination effects via latent tensor reconstruction

Tianduanyi Wang, Sandor Szedmak, Haishan Wang, Tero Aittokallio, Tapio Pahikkala, Anna Cichonska, Juho Rousu 2021 Bioinformatics
More information on our research in the Research database.
Research database

Related units

Helsinki Institute for Information Technology HIIT (external link)

HIIT is a joint research institute of Aalto University and the University of Helsinki for basic and applied research on information technology.


Finnish Center for Artificial Intelligence FCAI (external link)

Nation-wide competence center for Artificial Intelligence in Finland.

Finnish Center for Artificial Intelligence
PML research gropu at department of computer science, photo Matti Ahlgren

Research areas

Research areas in the Department of Computer Science

Department of Computer Science
PML Research Group in Department of Computer Science

Department of Computer Science

To foster future science and society.

Artistic depiction of a bright light in space / made by Ray Scipak

School of Science

Science for tomorrow’s technology, innovations and businesses

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