Zelmina Lubovac

MODalyseR—a novel software for inference of disease module hub regulators identified a putative multiple sclerosis regulator supported by independent eQTL data

Hendrik A. de Weerd, Julia Åkesson, Dimitri Guala, Mika Gustafsson, Zelmina Lubovac-Pilav

Bioinformatics Advances

2022. Artikel. https://doi.org/10.1093/bioadv/vbac006 Open Access

A validated generally applicable approach using the systematic assessment of disease modules by GWAS reveals a multi-omic module strongly associated with risk factors in multiple sclerosis

Tejaswi V. S. Badam, Hendrik A. de Weerd, David Martínez-Enguita, Tomas Olsson, Lars Alfredsson, Ingrid Kockum, Maja Jagodic, Zelmina Lubovac-Pilav, Mika Gustafsson

BMC Genomics

2021. Artikel. https://doi.org/10.1186/s12864-021-07935-1 Open Access

TFTenricher: a python toolbox for annotation enrichment analysis of transcription factor target genes

Rasmus Magnusson, Zelmina Lubovac-Pilav

BMC Bioinformatics

2021. Artikel. https://doi.org/10.1186/s12859-021-04357-4 Open Access

ComHub: Community predictions of hubs in gene regulatory networks

Julia Åkesson, Zelmina Lubovac-Pilav, Rasmus Magnusson, Mika Gustafsson

BMC Bioinformatics

2021. Artikel. https://doi.org/10.1186/s12859-021-03987-y Open Access

Whole-genome sequencing and gene network modules predict gemcitabine/carboplatin-induced myelosuppression in non-small cell lung cancer patients

Niclas Björn, Tejaswi Badam, Rapolas Spalinskas, Eva Brandén, Hirsh Koyi, Rolf Lewensohn, Luigi De Petris, Zelmina Lubovac-Pilav, Pelin Sahlén, Joakim Lundeberg,, Mika Gustafsson, Henrik Gréen

NPJ Systems Biology and Applications

2020. Artikel. https://doi.org/10.1038/s41540-020-00146-6 Open Access

MODifieR: an ensemble R package for inference of disease modules from transcriptomics networks

Hendrik A. de Weerd, Tejaswi V. S. Badam, David Martínez-Enguita, Julia Åkesson, Daniel Muthas, Mika Gustafsson, Zelmina Lubovac-Pilav

Bioinformatics

2020. Artikel. https://doi.org/10.1093/bioinformatics/btaa235 Open Access

miRFA: an automated pipeline for microRNA functional analysis with correlation support from TCGA and TCPA expression data in pancreatic cancer

Emmy Borgmästars, Hendrik Arnold de Weerd, Zelmina Lubovac-Pilav, Malin Sund

BMC Bioinformatics

2019. Artikel. https://doi.org/10.1186/s12859-019-2974-3 Open Access

Using next-generation sequencing to study biodiversity in Klebsiella spp. isolated from patients with suspected sepsis

Diana Tilevik, Patricia Saxenborn, Andreas Tilevik, Magnus Fagerlind, Zelmina Lubovac-Pilav, Anna-Karin Pernestig, Helena Enroth

29th European Congress of Clinical Microbiology and Infectious Diseases, ECCMID, Amsterdam, Netherlands, 13-16 April, 2019

2019. Konferensbidrag, poster. Open Access

Batch-normalization of cerebellar and medulloblastoma gene expression datasets utilizing empirically defined negative control genes

Holger Weishaupt, Patrik Johansson, Anders Sundström, Zelmina Lubovac-Pilav, Björn Olsson, Sven Nelander, Fredrik J. Swartling

Bioinformatics

2019. Artikel. https://doi.org/10.1093/bioinformatics/btz066 Open Access

Gene Co-Expression Network Analysis for Identifying Modules and Functionally Enriched Pathways in Type 1 Diabetes

Ignacio Riquelme Medina, Zelmina Lubovac-Pilav

PLOS ONE

2016. Artikel. https://doi.org/10.1371/journal.pone.0156006 Open Access

Using expression profiling to understand the effects of chronic cadmium exposure on mcf-7 breast cancer cells

Zelmina Lubovac-Pilav, Daniel M. Borràs, Esmeralda Ponce, Maggie C. Louie

PLOS ONE

2013. Artikel. https://doi.org/10.1371/journal.pone.0084646 Open Access

Integrative Approach for Detection of Functional Modules from Protein-Protein Interaction Networks

Zelmina Lubovac-Pilav

Protein-Protein Interactions: Computational and Experimental Tools

2012. Kapitel i bok. https://doi.org/10.5772/37858 Open Access

The mitochondrial transporter SLC25A43 is frequently deleted and may influence cell proliferation in HER2-positive breast tumors

Elisabet Tina, Breezy Malakkaran Lindqvist, Marike Gabrielson, Zelmina Lubovac, Pia Wegman, Sten Wingren

BMC Cancer

2012. Artikel. https://doi.org/10.1186/1471-2407-12-350 Open Access

A miRNA expression signature that separates between normal and malignant prostate tissues

Jessica Carlsson, Sabina Davidsson, Gisela Helenius, Mats Karlsson, Zelmina Lubovac, Ove Andren, Björn Olsson, Karin Klinga-Levan

Cancer Cell International

2011. Artikel. https://doi.org/10.1186/1475-2867-11-14

Validation of suitable endogenous control genes for expression studies of miRNA in prostate cancer tissues

Jessica Carlsson, Gisela Helenius, Mats Karlsson, Zelmina Lubovac, Ove Andrén, Björn Olsson, Karin Klinga-Levan

Cancer Genetics and Cytogenetics

2010. Artikel. https://doi.org/10.1016/j.cancergencyto.2010.02.009

Network Properties for Ranking Predicted miRNA Targets in Breast Cancer

Jörg Linde, Björn Olsson, Zelmina Lubovac

Advances in Bioinformatics

2009. Artikel. https://doi.org/10.1155/2009/182689

Investigating Topological and Functional Features of Multimodular Proteins

Zelmina Lubovac

Journal of Biomedicine and Biotechnology

2009. Artikel. https://doi.org/10.1155/2009/472415

Temporal analysis of oncogenesis using microRNA expression data

Thomas Zichner, Zelmina Lubovac, Björn Olsson

German Conference on Bioinformatics, GCB 2008: Proceedings

2008. Konferensbidrag. Open Access

Weighted Cohesiveness for Identification of Functional Modules and their Interconnectivity

Zelmina Lubovac, David Corne, Jonas Gamalielsson, Björn Olsson

Bioinformatics Research and Development: First International Conference, BIRD 2007 Berlin, Germany, March 12-14, 2007 Proceedings

2007. Konferensbidrag. https://doi.org/10.1007/978-3-540-71233-6_15

Thesis Materials: Knowledge-based Methods for Identification of Functional Modules in Protein Interaction Networks

Zelmina Lubovac

2006. Rapport.

Combining functional and topological properties to identify core modules in protein interaction networks

Zelmina Lubovac, Jonas Gamalielsson, Björn Olsson

Proteins

2006. Artikel. https://doi.org/10.1002/prot.21071

Weighted Clustering Coefficient for Identifying Modular Formations in Protein-Protein Interaction Networks

Zelmina Lubovac, Björn Olsson, Jonas Gamalielsson

Proceedings of World Academy of Science, Engineering and Technology, Vol 14

2006. Konferensbidrag.

Simulations of simple artificial genetic networks reveal features in the use of Relevance Networks

Angelica Lindlöf, Zelmina Lubovac

In Silico Biology

2005. Artikel.

Exploring protein networks with a semantic similarity measure across Gene Ontology

Zelmina Lubovac, Jonas Gamalielsson, Björn Olsson, Angelica Lindlöf

Proceedings of the 8th Joint Conference on Information Sciences, Vols 1-3

2005. Konferensbidrag.

Combining topological characteristics and domain knowledge reveals functional modules in protein interaction networks

Zelmina Lubovac, Björn Olsson, Jonas Gamalielsson

Proceedings of CompBioNets 2005: Algorithms and Computational Methods for Biochemical and Evolutionary Networks

2005. Konferensbidrag.

Towards Reverse Engineering of Genetic Regulatory Networks

Zelmina Lubovac, Björn Olsson

2003. Rapport.

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