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.

Stephane Deny

Learning from the brain: Stéphane Deny uses insights from neuroscience for better artificial intelligence

Machine learning models typically need gigantic data sets and a lot of energy, whereas the brain consumes as much power as a single light bulb. Aalto’s new assistant professor uses neuroscience to make computer programs more efficient.

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.

an illustration of large granular lymphocyte leukemia cell

Blood cancer cells and the immune system are best frenemies

The University of Helsinki and Aalto University collaborated in an international study, which demonstrated that the body's immune system is complicit in a rare type of blood cancer, suggesting a reconsideration of conventional knowledge on the disease.

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

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


Related research groups

Latest publications

Relationship between daily rated depression symptom severity and the retrospective self-report on PHQ-9: A prospective ecological momentary assessment study on 80 psychiatric outpatients

Ilya Baryshnikov, Talayeh Aledavood, Tom Rosenström, Roope Heikkilä, Richard Darst, Kirsi Riihimäki, Outi Saleva, Jesper Ekelund, Erkki Isometsä 2023 Journal of Affective Disorders

Single-cell characterization of anti-LAG-3 and anti-PD-1 combination treatment in patients with melanoma

Jani Huuhtanen, Henna Kasanen, Katriina Peltola, Tapio Lönnberg, Virpi Glumoff, Oscar Brück, Olli Dufva, Karita Peltonen, Johanna Vikkula, Emmi Jokinen, Mette Ilander, Moon Hee Lee, Siru Mäkelä, Marta Nyakas, Bin Li, Micaela Hernberg, Petri Bono, Harri Lähdesmäki, Anna Kreutzman, Satu Mustjoki 2023 JOURNAL OF CLINICAL INVESTIGATION

TCRconv: predicting recognition between T cell receptors and epitopes using contextualized motifs

Emmi Jokinen, Alexandru Dumitrescu, Jani Huuhtanen, Vladimir Gligorijevic, Satu Mustjoki, Richard Bonneau, Markus Heinonen, Harri Lähdesmäki 2023 Bioinformatics

Dynamics of the Negative Discourse Toward COVID-19 Vaccines : Topic Modeling Study and an Annotated Data Set of Twitter Posts

Gabriel Lindelöf, Talayeh Aledavood, Barbara Keller 2023 JOURNAL OF MEDICAL INTERNET RESEARCH

LuxHMM : DNA methylation analysis with genome segmentation via hidden Markov model

Maia H. Malonzo, Harri Lähdesmäki 2023 BMC Bioinformatics

Mental Health Coping Stories on Social Media: A Causal-Inference Study of Papageno Effect

Yunhao Yuan, Koustuv Saha, Barbara Keller, Erkki Tapio Isometsä, Talayeh Aledavood 2023 ACM Web Conference 2023 - Proceedings of the World Wide Web Conference, WWW 2023

Quantifying daily rhythms with non-negative matrix factorization applied to mobile phone data

Talayeh Aledavood, Ilkka Kivimäki, Sune Lehmann, Jari Saramäki 2022 Scientific Reports

Modeling binding specificities of transcription factor pairs with random forests

Anni A. Antikainen, Markus Heinonen, Harri Lähdesmäki 2022 BMC Bioinformatics

Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters

Luc Brogat-Motte, Rémi Flamary, Céline Brouard, Juho Rousu, Florence d'Alché-Buc 2022 Proceedings of the 39th International Conference on Machine Learning, PMLR
More information on our research in the Research database.
Research database

Related units

Helsinki Institute for Information Technology HIIT (external link)

Collaborative institute for research on information technology.

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PML research gropu at department of computer science, photo Matti Ahlgren

Research areas

Research in the Department of Computer Science

Department of Computer Science
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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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