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Personal profile


Artificial intelligence and big data in medicine and life science

  1. Use of artificial intelligence for image analysis (e.g. microscopy and histology)
  2. Use of artificial intelligence for text mining (Swedish and English)
  3. Use of artificial intelligence for protein/gene function prediction
  4. Use of artificial intelligence for integrating medical and life science-related "big data"
  5. Database mining


Understanding lysosomes and cell death and their relation with the health of humans and other species

  1. Deciphering the molecular machinery of lysosome regulation and cell death, including interactions between different signalling pathways
  2. Understanding how excessive or impaired cell death and lysosome function is linked to human diseases and diseases in other species
  3. Understanding how environmental toxins affect lysosomes and cell death in humans and other species
  4. Targeted modulation of lysosome function and cell death
  5. Development of novel tools and methods for studying lysosomes and cell death


Besides these core areas I am also involved in collaborations related to artificial intelligence, cell death, lysosomes, and sustainability/environmental science.

I am also associated with several local and international research networks:

  • NEUBIAS European Bioimage Analysis Network
  • Nordic Autophagy Society
  • StrokeSyd
  • AI Lund
  • BioCARE
  • eHealth@LU
  • EpiHealth
  • CEC
  • LUCC

UKÄ subject classification

  • Medical Biotechnology
  • Bioinformatics and Systems Biology
  • Bioinformatics (Computational Biology)
  • Cell and Molecular Biology
  • Biochemistry and Molecular Biology
  • Environmental Health and Occupational Health
  • Neurosciences
  • Other Basic Medicine
  • Signal Processing
  • Computer Vision and Robotics (Autonomous Systems)
  • Language Technology (Computational Linguistics)
  • Information Systems
  • Environmental Sciences

Free keywords

  • deep learning
  • cell death
  • lysosomes
  • Natural Language Processing
  • Functional genomics
  • Image analysis
  • Microscopy
  • Mitochondria
  • Screening
  • Bioinformatics
  • Neuroscience
  • Cancer biology
  • Autophagy
  • Phenotypic screening
  • Neurodegeneration
  • Artificial Intelligence
  • Machine learning
  • Computational modelling
  • Computer vision
  • High-content microscopy
  • Apoptosis
  • toxins
  • environmental science
  • Sustainability


Dive into the research topics where Sonja Aits is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years

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