Professor Natasa Miskov-Zivanov focuses on automating information retrieval and modeling complex biological systems. Her research aims to bridge knowledge-driven and data-driven approaches, particularly in systems biology and synthetic biology. Her group investigates systems such as the immune response and cancer microenvironments, exploring their dynamics and how they respond to various perturbations. This work includes the development of computational tools for understanding and predicting the behavior of these complex systems.
"The BioRECIPE Knowledge Representation Format"
Holtzapple E, Zhou G, Luo H, Tang D, Arazkhani N, Hansen C, Telmer C, Miskov-Zivanov N, ACS Synth Biol. 2024, 13, 8, 2621-2624
"Context-aware knowledge selection and reliable model recommendation with ACCORDION"
Ahmed Y, Telmer CA, Zhou G, Miskov-Zivanov N. Front Syst Biol. 2024, 4, 1308292
"Post-translational covalent assembly of CAR and synNotch receptors for programmable antigen targeting"
Ruffo E, Butchy AA, Tivon Y, So V, Kvorjak M, Parikh A, Adams EL, Miskov-Zivanov N, Finn OJ, Deiters A, Lohmueller J. Nat Commun. 2023,14, 1, 2463
"CLARINET: efficient learning of dynamic network models from literature"
Ahmed Y, Telmer CA, Miskov-Zivanov N Bioinform Adv. 2021,1, 1, vbab006
"FLUTE: Fast and reliable knowledge retrieval from biomedical literature"
Holtzapple E, Telmer CA, Miskov-Zivanov N. Database (Oxford). 2020, 2020, baaa056