Ola Spjuth

Professor, AI coordinator, Advisor e-infrastructure, Uppsala University

Key publications

Wieslander H., Harrison P, Skogberg G, Jackson S, Fridén M, Karlsson J, Spjuth O, and Wählby C.
Deep learning with conformal prediction for hierarchical analysis of large-scale whole-slide tissue images
IEEE Journal of Biomedical and Health InformaticsEarly access (2020). DOI: 10.1109/JBHI.2020.2996300

Capuccini M, Dahlö M, Toor S, and Spjuth O
MaRe: Container-Based Parallel Computing with Data Locality
Gigascience9, 5, giaa042. (2020). DOI: 10.1093/gigascience/giaa042

Kensert A, Harrison PJ, Spjuth O
Transfer learning with deep convolutional neural network for classifying cellular morphological changes
SLAS DISCOVERY: Advancing Life Sciences R&D24, 4 (2019). DOI: 10.1177/2472555218818756

Khoonsari PE, Moreno P, Bergmann S, Burman J, Capuccini M, Carone M, Cascante M, de Atauri P, Foguet C, Gonzalez-Beltran A, Hankemeier T, Haug K, He S, Herman S, Johnson D, Kale N, Larsson A, Neumann S, Peters K, Pireddu L, Rocca-Serra P, Roger P, Rueedi R, Ruttkies C, Sadawi N, Salek RM, Sansone SA, Schober D, Selivanov V, Thévenot EA, van Vliet M, Zanetti G, Steinbeck C, Kultima K, and Spjuth O.
Interoperable and scalable data analysis with microservices: Applications in Metabolomics
Bioinformatics. btz160 (2019). DOI: 10.1093/bioinformatics/btz160

Lampa S, Dahlö M, Alvarsson J, Spjuth O
SciPipe: A workflow library for agile development of complex and dynamic bioinformatics pipelines
Gigascience8, 5 (2019). DOI: 10.1093/gigascience/giz044

Lampa S, Alvarsson J, Arvidsson Mc Shane S, Berg A, Ahlberg E, Spjuth O
Predicting off-target binding profiles with confidence using Conformal Prediction
Frontiers in Pharmacology9, 1256. (2018). DOI: 10.3389/fphar.2018.01256

Lampa S, Alvarsson J, Spjuth O
Towards agile large-scale predictive modelling in drug discovery with flow-based programming design principles
Journal of Cheminformatics8, 67. (2016). DOI: 10.1186/s13321-016-0179-6

See the complete publication list here: https://pharmb.io/publication/


Research Interests

The Pharmaceutical Bioinformatics research group focuses on mathematical and statistical modeling, informatics and quantitative analysis of pharmacological systems. We develop methods, algorithms and software to study and model pharmaceutical interactions, and a key focus in the group is how artificial intelligence (AI) and machine learning can aid the drug discovery process; e.g. in drug screening and when studying drug toxicity, metabolism and resistance. We combine in silico and in vitro experiments at the cellular level, and have access to a robotized high-content imaging lab connected to a modern IT-infrastructure to manage and analyze large-scale data. We are involved in several national and international consortia and have a tight connection to the pharmaceutical industry, Uppsala University Hospital, and Science for Life Laboratory.

Group members

Ola Spjuth,  Professor
Jordi Carreras-Puigvert, Lecturer
Jonathan Alvarsson, Researcher
Maris Lapins, Researcher
Wesley Schaal, Researcher
Polina Georgiev, Researcher
Ernst Ahlberg, Guest Researcher
Ulf Norinder, Guest Researcher
Maria Andreina Francisco Rodriguez, Postdoc
Ebba Bergman, PhD Student
Jonne Rietdijk, PhD Student
Phil Harrison, PhD Student
Staffan Arvidsson, PhD Student
Martin Dahlö, PhD Student
Anders Larsson, Software Engineer
Morgan Ekmefjord, Software Engineer

Research group website




Last updated: 2022-11-30

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