Tjasa Kumelj
About
Dr. Tjaša Kumelj received her Ph.D. degree in Biotechnology within Computational System Biology. Research work within PhD included Mechanistic Genome-scale Constraint-based Mechanistic Metabolic Modeling, Flux Balance Analysis, Omics Data Analyses, Metabolic Engineering, Computational Systems Medicines, Mechanistic and Statistical Modeling at Norwegian University of Science and Technology, NTNU.
Doctoral thesis 2021: Genome-scale models and consequences of mass constraints and availability of enzymes: dissertation
She has a M.Sc. degree in Chemistry with specialization within Biochemistry/Molecular Biology, University of Ljubljana, Slovenia.
Overall, research work included Mechanistic and Statistical Computational Modeling, and Computational Modeling applying Moldecular Dynamic Simulations and Quantum Mechanics.
Research work: research work (publications, posters, presentations).
Her present work integrates Development of Models in Precision Medicine, Clinical Database Development and Data Management (NTNU, Institute for Neuromedicine and Movement, NorHead (Norwegian Researh Center for Headache, Medical Faculty, Institute of Neurology).
The projects, she is currently involved in, include:
1. NorHead Research Registry and Biobank (Clinical database development, NorHead, NTNU)
2. Machine intelligence in HEADaches (MI-HEAD project, NorHead, NTNU): machine learning in classifing migraine from Genome-Wide Genotype data (GWAS), clinical data and health registry data, combining genomic-based and machine learning methods with the ultimate goal to study mechanistic interpretation of non-additive effects in headache disorders. In collaboration with University College London, UK and International Headache Genetic Consortium.
3. Applied Ethical Al on Nordic Patient Records (Anvendt Etisk AI på nordiske pasientjournaler, FEHLS.2021.AI), NorHead, NTNU & Nordic Applied Ethical AI Consortium: The ultimate goal of the study is development of machine learning model to interpret the non-structured clinical notes and referrals for possible prediction of medication efficacy and possibly disease progression, applying federated machine learning approach, in collaboration with Aalborg University, Denmark & Z-Inspection-Tempere University, Finland.
4. Headache in Norway (Hodepine i Norge)-NorHEAD MiHEAD; NTNU, NorHead in collaboration with University of Bergen (UiB) and Oslo Univerisy Hospital (OUS).
5. COST action CA25112 (Multidisciplinary AI driven research (MigrAInet))
MigrAInet - Network for comprehensive characterization and management of MIGRAINE subTypes: Multidisciplinary AI-driven approach
MigrAInet is an EU COST action uniting headache and AI experts, patient organizations, and policymakers to transform migraine research and care. We aim to advance precision medicine through standardized multimodal data, AI, and knowledge exchange.
WG1 - Standardization and integration of clinical, neuroimaging, and multiomics data in migraine research
WG3 - AI-driven data analysis and Digital Twin approaches for biomarker discovery, subtype classification
Competencies
- Bioinformatics
- Chemistry
- Complex Network Analysis
- Computational Mechanistic and Statistical Modeling
- Computational Systems Biology
- Data science
- Data science clinical database development data governance
- Genetical Epidemiology (EpiGenetics)
- Genome Scale Metabolic Modeling
- Molecular Biology and Biochemistry
- Omics Analysis
- Statistical Genetics and Functional Genomics
Research
1. Clinical DataBase Development and Development of Models in Precision Medicine and Data Management, NTNU, Faculty of Medicine, Institut for Neuromedicine, NeuroØst, St.Olof Hospital, NorHead-Norwegian Research Center for Headache.
-Computational Systems Biology & Bioinformatics
-Computational Statistical & Mechanistic Modeling and Data Science
-Genome-scale Metabolic Modeling and Reconstruction of Genome-scale Metabolic Models
-Database development
-Omics analysis
-Genetic Epidemiology
-Statistical Genetics and Functional Genomics
2. Computational Systems Biology-Genome Scale Metabolic Modeling, Metabolic Engineering, Complex Network Analysis and Omics Analysis with Application in Biotechnology, Bioengineering and Biomedicine (NTNU, Professor Eivind Almaas Lab)-PhD degree.
3. Theoretical (Computational) Chemistry within Molecular Modleing and Computer Molecular Dynamics (MD) Simulation (NTNU)-medical research.
4. Experimental Chemistry, Biochemistry/Molecular Biology, Analytical Chemistry- Drug Discovery Unit (Pharmaceutical firm LEK (Sandoz), a generic part og Swiss Company Novartis).
Publications
Diagnosing migraine from genome-wide genotype data: a machine learning analysis
Brain
2025-05-06 | Journal article
Contirbutors: Antonios Danelakis, Tjaša Kumelj , Bendik S Winsvold , Marte Helene Bjørk , Parashkev Nachev , Manjit Matharu , Dominic Giles , Erling Tronvik , Helge Langseth , Anker Stubberud , The International Headache Genetics Consortium.
Machine Diagnostics and Machine Phenotyping of Migraine
Neurology
Forecasting migraine with time-series machine learning from mobile health data
2026
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Almaas, Eivind;
Kumelj, Tjasa.
(2026)
Competing constraints on protein availability and nutrient uptake reshape yeast genetic interactions.
BioArchive
Academic article
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Danelakis, Antonios;
Abildsnes, Håkon Kvisle;
Faisal, Fahim;
Bjørk, Marte-Helene;
Giles, Dominic;
Hagen, Knut;
Kumelj, Tjasa;
Matharu, Manjit;
Nachev, Parashkev;
Tronvik, Erling Andreas.
(2026)
Machine Diagnostics and Machine Phenotyping of Migraine A HUNT Study.
Neurology
Academic article
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Faisal, Fahim;
Poole, Amalie Christine;
Danelakis, Antonios;
Wergeland, Tore;
Bjørk, Marte-Helene;
Khanevski, Andrej;
Kristoffersen, Espen Saxhaug;
Kumelj, Tjasa;
Larsen, Iben Cornelia Keim;
Lunder, Oda Vardenær.
(2026)
Forecasting migraine with time-series machine learning from mobile health data.
The Journal of Headache and Pain
Academic article
2025
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Danelakis, Antonios;
Kumelj, Tjasa;
Winsvold, Bendik S.;
Bjørk, Marte Helene;
Nachev, Parashkev;
Matharu, Manjit;
Giles, Dominic;
IHGC, Int. Headache Genetic Cons.;
Tronvik, Erling Andreas;
Langseth, Helge.
(2025)
Diagnosing migraine from genome-wide genotype data: a machine learning analysis.
Brain
Academic article
2021
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Schulz, Christian;
Kumelj, Tjasa;
Karlsen, Emil;
Almaas, Eivind.
(2021)
Genome-scale metabolic modelling when changes in environmental conditions affect biomass composition.
PLoS Computational Biology
Academic article
2020
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Sulheim, Snorre;
Kumelj, Tjasa;
van Dissel, Dino;
Salehzadeh-Yazdi, Ali;
Du, Chao;
Wezel, Gilles P. Van;
Nieselt, Kay;
Almaas, Eivind;
Wentzel, Alexander;
Kerkhoven, Eduard J.
(2020)
Enzyme-Constrained Models and Omics Analysis of Streptomyces coelicolor Reveal Metabolic Changes that Enhance Heterologous Production.
iScience
Academic article
2019
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Kumelj, Tjasa;
Sulheim, Snorre;
Wentzel, Alexander;
Almaas, Eivind.
(2019)
Predicting strain engineering strategies using iKS1317: a genome-scale metabolic model of Streptomyces coelicolor.
Biotechnology Journal
Academic article
Journal publications
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Almaas, Eivind;
Kumelj, Tjasa.
(2026)
Competing constraints on protein availability and nutrient uptake reshape yeast genetic interactions.
BioArchive
Academic article
-
Danelakis, Antonios;
Abildsnes, Håkon Kvisle;
Faisal, Fahim;
Bjørk, Marte-Helene;
Giles, Dominic;
Hagen, Knut;
Kumelj, Tjasa;
Matharu, Manjit;
Nachev, Parashkev;
Tronvik, Erling Andreas.
(2026)
Machine Diagnostics and Machine Phenotyping of Migraine A HUNT Study.
Neurology
Academic article
-
Faisal, Fahim;
Poole, Amalie Christine;
Danelakis, Antonios;
Wergeland, Tore;
Bjørk, Marte-Helene;
Khanevski, Andrej;
Kristoffersen, Espen Saxhaug;
Kumelj, Tjasa;
Larsen, Iben Cornelia Keim;
Lunder, Oda Vardenær.
(2026)
Forecasting migraine with time-series machine learning from mobile health data.
The Journal of Headache and Pain
Academic article
-
Sulheim, Snorre;
Kumelj, Tjasa;
van Dissel, Dino;
Salehzadeh-Yazdi, Ali;
Du, Chao;
Wezel, Gilles P. Van;
Nieselt, Kay;
Almaas, Eivind;
Wentzel, Alexander;
Kerkhoven, Eduard J.
(2020)
Enzyme-Constrained Models and Omics Analysis of Streptomyces coelicolor Reveal Metabolic Changes that Enhance Heterologous Production.
iScience
Academic article
-
Danelakis, Antonios;
Kumelj, Tjasa;
Winsvold, Bendik S.;
Bjørk, Marte Helene;
Nachev, Parashkev;
Matharu, Manjit;
Giles, Dominic;
IHGC, Int. Headache Genetic Cons.;
Tronvik, Erling Andreas;
Langseth, Helge.
(2025)
Diagnosing migraine from genome-wide genotype data: a machine learning analysis.
Brain
Academic article
-
Schulz, Christian;
Kumelj, Tjasa;
Karlsen, Emil;
Almaas, Eivind.
(2021)
Genome-scale metabolic modelling when changes in environmental conditions affect biomass composition.
PLoS Computational Biology
Academic article
-
Kumelj, Tjasa;
Sulheim, Snorre;
Wentzel, Alexander;
Almaas, Eivind.
(2019)
Predicting strain engineering strategies using iKS1317: a genome-scale metabolic model of Streptomyces coelicolor.
Biotechnology Journal
Academic article
Teaching
Teaching and Leading Laboratory Course in Physical Chemistry in electrolytic conductivity and transference number at Deparment of Chemistry, NTNU (closed)
Supervision
Data Management and establishement of Broad Research Database within ISO-certified HUNT Cloud environment (NorHead - Norwegian Center for Headache Research, Faculty of Medicine, Institut of Neurology) (2022- )
Teaching and Leading Laboratory Course in Physical Chemistry in electrolytic conductivity and transference number at Deparment of Chemistry, NTNU (closed)
Project leader , Drug Discovery Group, Pharmaceutical Company (part of Sandoz, Swiss Company), Slovenia (closed)
Outreach
2025
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Conference posterBarlous, Benjamin Christopher; Danelakis, Antonios; Ekman, Petra; Gils, Mark van; Happonen, Antti P.; Hau, Maïlys Françoise; Kringen, Pedro; Kumelj, Tjasa; Moreno-Sánchez, Pedro A.; Tronvik, Erling Andreas. (2025) Federated Ethical Healthcare Learning Sandbox Project. FCAI AI Day 2025
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Conference posterDanelakis, Antonios; Faisal, Fahim; Abildsnes, Håkon Kvisle; Winsvold, Bendik Kristoffer Slagsvold; Bjørk, Marte-Helene; Giles, Dominic; Nachev, Parashkev; Kumelj, Tjasa; Hagen, Knut; Matharu, Manjit. (2025) Data driven phenotyping of migraine and its correlation with ICHD-3 criteria and polygenic risk scores. European Headache Congress (EHC) 2025
2024
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Conference lectureDanelakis, Antonios; Stubberud, Anker; Winsvold, Bendik Kristoffer Slagsvold; bjørk, marte helene; Giles, Dominic; Nachev, Parashkev; Kumelj, Tjasa; Hagen, Knut; Matharu, Manjit; Nyholt, Dale R.. (2024) Machine learning versus polygenic risk scoring as migraine predictors based on genome-wide genotype data. Migraine Trust International Symposium (MTIS) 2024
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Conference lectureDanelakis, Antonios; Abildsnes, Håkon Kvisle; Faisal, Fahim; Winsvold, Bendik Kristoffer Slagsvold; bjørk, marte helene; Giles, Dominic; Nachev, Parashkev; Kumelj, Tjasa; Hagen, Knut; Matharu, Manjit. (2024) Machine learning can predict migraine from genotype and non-headache clinical data with high accuracy. European Headache Congress (EHC) 2024
2021
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Conference posterSulheim, Snorre; Kumelj, Tjasa; van Dissel, Dino; Salehzadeh-Yazdi, Ali; Du, Chao; Wezel, Gilles P. Van; Nieselt, Kay; Almaas, Eivind; Wentzel, Alexander; Kerkhoven, Eduard. (2021) A systems comparison of Streptomyces coelicolor M1152 and M145 reveals major metabolic rewiring. COBRA 2021
2019
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Conference posterSulheim, Snorre; Kumelj, Tjasa; Salehzadeh-Yazdi, Ali; Dissel, Dino van; Chao, Du; Nieselt, Kay; Almaas, Eivind; Wentzel, Alexander; Kerkhoven, Eduard. (2019) An enzyme-constrained genome-scale metabolic model of Streptomyces coelicolor reveals global effects of gene cluster deletion and rpoB mutation. Digital Life Norway Conference 2019
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Conference lectureWentzel, Alexander; Lewin, Anna; Nordborg, Anna; Nguyen, Giang-Son; Degnes, Kristin Fløgstad; Sulheim, Snorre; Borgos, Sven Even F.; Kumelj, Tjasa; Kumar, Kanhaiya; Bruheim, Per. (2019) Expanding the (meta)genomics toolbox for the discovery and production of novel natural products from microbial resources. 2nd Synthetic Biology for Natural Products Conference
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Conference lectureWentzel, Alexander; Lewin, Anna; Nordborg, Anna; Nguyen, Giang-Son; Degnes, Kristin Fløgstad; Sulheim, Snorre; Borgos, Sven Even F.; Kumelj, Tjasa; Kumar, Kanhaiya; Bruheim, Per. (2019) Expanding the (meta)genomics toolbox for the discovery and production of novel natural products from microbial resources. Functional Metageomics 2019
2018
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Conference posterSulheim, Snorre; Kumelj, Tjasa; Sletta, Håvard; Wentzel, Alexander; Almaas, Eivind. (2018) Predicting phenotypes using iKS1317: a genome-scale metabolic model of Streptomyces coelicolor. Digital Life Conference 2018
2017
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Conference lectureSulheim, Snorre; Kumelj, Tjasa; Wentzel, Alexander; Almaas, Eivind. (2017) A genome-scale metabolic model for Streptomyces coelicolor. Modelling living systems - From foundational problems to applications
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Conference posterSulheim, Snorre; Kumelj, Tjasa; Wentzel, Alexander; Almaas, Eivind. (2017) Extended GEM of Streptomyces coelicolor for production of secondary metabolites. International conference on systems biology 2017 (ICSB 2017)
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LectureWentzel, Alexander; Lewin, Anna; Nordborg, Anna; Nguyen, Giang-Son; Degnes, Kristin Fløgstad; Sulheim, Snorre; Kumelj, Tjasa; Bruheim, Per; Almaas, Eivind; Liles, Mark R.. (2017) New bioactive compounds from environmental microbial resources by an integrated functional (meta)genomics approach. Synthetic Biology of Natural Products
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LectureWentzel, Alexander; Lewin, Anna; Nordborg, Anna; Nguyen, Giang-Son; Degnes, Kristin Fløgstad; Sulheim, Snorre; Kumelj, Tjasa; Bruheim, Per; Almaas, Eivind; Liles, Mark R.. (2017) New bioactive compounds from environmental microbial resources by an integrated functional (meta)genomics approach. BioProsp 2017, the 8th International Conference on Marine Biotechnology
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Conference posterSulheim, Snorre; Kumelj, Tjasa; Wentzel, Alexander; Almaas, Eivind. (2017) A genome-scale metabolic model for Streptomyces coelicolor. Advanced course on Metabolic engineering and Systems Biology
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Conference posterSulheim, Snorre; Kumelj, Tjasa; Wentzel, Alexander; Almaas, Eivind. (2017) A genome-scale metabolic model for Streptomyces coelicolor. Methodologies for Digital Life - Focus on Metabolic Systems
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Conference lectureSulheim, Snorre; Kumelj, Tjasa; Wentzel, Alexander; Almaas, Eivind. (2017) A genome-scale metabolic model for Streptomyces coelicolor. Lunsj-seminar
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Conference posterKumelj, Tjasa; Sulheim, Snorre; Wentzel, Alexander; Almaas, Eivind. (2017) A genome-scale metabolic model for Streptomyces coelicolor. Advanced course on Metabolic engineering and Systems Biology
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Conference lectureKumelj, Tjasa; Sulheim, Snorre; Wentzel, Alexander; Almaas, Eivind. (2017) Extended GEM of Streptomyces coelicolor for production of secondary metabolites. International conference on systems biology 2017 (ICSB 2017)
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Conference posterSulheim, Snorre; Almaas, Eivind; Kumelj, Tjasa. (2017) A genome-scale metabolic reconstruction of S. coelicolor. NORBIS annual national conference 2017
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LectureWentzel, Alexander; Lewin, Anna; Nordborg, Anna; Nguyen, Giang-Son; Degnes, Kristin Fløgstad; Sulheim, Snorre; Kumelj, Tjasa; Bruheim, Per; Almaas, Eivind; Liles, Mark R.. (2017) New bioactive compounds from environmental microbial resources by an integrated functional (meta)genomics approach. Centre for Digital Life Norway - Annual conference
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LectureWentzel, Alexander; Lewin, Anna; Nordborg, Anna; Nguyen, Giang-Son; Degnes, Kristin Fløgstad; Sulheim, Snorre; Kumelj, Tjasa; Bruheim, Per; Almaas, Eivind; Liles, Mark R.. (2017) New bioactive compounds from environmental microbial resources by an integrated functional (meta)genomics approach. Meeting with the ReDig project
2009
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Conference lectureKumelj, Tjasa; Åstrand, Per-Olof; Sanz-Navarro, Carlos F.. (2009) Towards a reactive force field for Fe(IV) with application to oxidative dealkylation of DNA. Bioinformatics Forum for Young Scientists (BFYS) April 24-26 2009, Trondheim/Selbu