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Genetics of Sleep, Circadian Rhythms and Human Immune Disorders
Brain Autoimmunity Janna Saarela, Research Director, Professor
Hanna Ollila, FIMM-EMBL Group Leader
The group improves the understanding of biological
The group elucidates the genetic and environmental trig- pathways and pathogenic mechanisms behind rare and
gers that lead to brain autoimmune and sleep disorders common immune diseases, especially primary immune
with the aim to discover crucial mechanisms that con- deficiencies and multiple sclerosis, and utilises the new
trol sleep and how can sleep be used as a biomarker for knowledge for the benefit of patients.
disease.
Botnia Study: Genetic and Metabolic
Bioimage Profiling Characterisation of Diabetes
Lassi Paavolainen, Academy Research Fellow Tiinamaija Tuomi, Group Leader and
Leif Groop, Professor
This group uncovers complex information from bioimages
using machine learning. They develop novel deep learning The group characterises the genetic and environmental
solutions for bioimage analysis, study learning approaches factors predisposing people to diabetes and its complica-
to create models and apply these methods and models to tions. In addition to unravelling the complex metabolic
profile cancer cell and tissue samples. pathways, they aim to find tools for individualised pre-
vention and treatment of diabetes.
Genomics of Neurological and Neuropsychiatric
Disorders Genomics of Sex Differences
Aarno Palotie, Research Director, Professor Taru Tukiainen, Academy Research Fellow
The group studies the genetic mechanisms underlying sev- The group builds a better understanding of the biological
eral neurological, neurodevelopmental and neuropsychiat- underpinnings of the widespread sex differences in human
ric traits, such as cognitive impairment and schizophrenia. health and disease. Their work focuses on the investiga-
Their work draws on the unique clinical and population- tion of sex biases in both genetic and transcriptomic data
based samples collected from the Finnish founder popula- to facilitate more accurate disease risk prediction, treat-
tion. ment, and intervention.
Statistical and Population Genetics Translational Lung Cancer
Matti Pirinen, FIMM Group Leader Emmy Verschuren, FIMM Group Leader
The group develops multivariate statistical modelling The group studies the biological properties of lung cancer
methods and tools and applies them to large genomic drivers in their complex environment, and integrates this
datasets to be able to answer biologically and medically knowledge to design ex vivo diagnostic lung cancer mod-
important questions, such as the fine-scale genetic struc- els. They focus on how histopathology and functional het-
ture within the Finnish population. erogeneity relate to therapeutic response, with an overall
aim to implement diagnostic models to guide treatment
Machine Learning in Biomedicine decisions for individual cancer patients.
Esa Pitkänen, FIMM-EMBL Group Leader
Cognitive and Brain Aging
The group creates scalable and multimodal machine learn- Eero Vuoksimaa, Academy Research Fellow
ing techniques utilising genome, transcriptome, epige-
nome and imaging data to build computational tools that The group focuses on understanding the pathways from
can be translated into clinical practice. Their projects focus protective and risk factors to old age cognition and brain
on cancers and haematological malignancies. health. They aim to improve the early identification of indi-
viduals with a high risk of cognitive impairment, dementia
Complex Disease Genetics and Alzheimer’s disease.
Samuli Ripatti, FIMM Vice Director, Professor
Genomic Discoveries and Clinical Translation
The group studies genetics of common complex diseases Elisabeth Widén, FIMM Group Leader
from discovery to translation to health care, with a par-
ticular focus on cardiovascular diseases and metabolism. The group implements genomic research into medical
They develop and test models to stratify individuals based practice. As part of the GeneRISK study, they have created
on their risks for preventive actions or stratified treatment. a unique interactive web tool for interpreting and commu-
nicating personal cardio-vascular disease risk information.
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