School of Bioscience
|Ph.D., M.Sc., B.Sc.|
|Ph.D., School for Humanities and Informatics, Sweden, and Heriot-Watt University, School of Mathematical and Computer Science, Edinburgh, Scotland, 2008|
Member of the BioInformatics Group (BIG)
Various methods of network clustering have been applied to reveal modular organisation in protein interaction networks (PINs). However, those clustering methods are mostly based on topological properties of the network. Therefore, we are focusing on developing methods for deriving functional modules from PINs using both structural information and domain knowledge from Gene Ontology. The modules obtained by these integrated methods are characterised by high functional cohesiveness among their members. Besides deriving modular structure, we also use the proposed methods to shed light on how the functional strength of interactions affects our view of global structural organization.
Temporal analysis of oncogenesis using microRNA expression dataZichner Thomas, Lubovac Zelmina, Olsson BjörnProc. Ger. Conf. Bioinformatics, GCB (128-137). Bonn: Gesellschaft für Informatik, 2008.
Weighted Cohesiveness for Identification of Functional Modules and their InterconnectivityLubovac Zelmina, Corne David, Gamalielsson Jonas et al.Bioinformatics Research and Development: First International Conference, BIRD ’07 (185-198). Springer Berlin/Heidelberg, 2007.
Combining functional and topological properties to identify core modules in protein interaction networksLubovac Zelmina, Gamalielsson Jonas, Olsson BjörnProteins: Structure, Function, and Bioinformatics, 2006, 64(4), 948-959.
Thesis Materials: Knowledge-based Methods for Identification of Functional Modules in Protein Interaction Networks
Lubovac ZelminaSkövde: Institutionen för kommunikation och information, 2006. [Full text]
Weighted Clustering Coefficient for Identifying Modular Formations in Protein-Protein Interaction Networks
Lubovac Zelmina, Olsson Björn, Gamalielsson JonasProceedings of World Academy of Science, Engineering and Technology, Vol 14 (122-127). World Academy of Science, Engineering and Technology, 2006.
Combining topological characteristics and domain knowledge reveals functional modules in protein interaction networksLubovac Zelmina, Olsson Björn, Gamalielsson JonasProceedings of CompBioNets 2005: Algorithms and Computational Methods for Biochemical and Evolutionary Networks (93-106). 2005.
Exploring protein networks with a semantic similarity measure across Gene Ontology
Lubovac Zelmina, Gamalielsson Jonas, Olsson Björn et al.Proceedings of the 8th Joint Conference on Information Sciences, Vols 1-3 (1203-1208). Durham, NC: Joint Conference on Information Sciences, 2005.
Simulations of simple artificial genetic networks reveal features in the use of Relevance Networks
Lindlöf Angelica, Lubovac ZelminaIn Silico Biology, 2005, 5(3), 239-249.
Towards Reverse Engineering of Genetic Regulatory NetworksLubovac Zelmina, Olsson BjörnSkövde: Institutionen för kommunikation och information, 2003. [Full text]