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Zelmina Lubovac-Pilav

Showing results (1-10 of 15) with videos related to

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BMC Bioinformatics|September 17, 2021
TFTenricher: a python toolbox for annotation enrichment analysis of transcription factor target genesRasmus Magnusson, Zelmina Lubovac-Pilav
Plos One|June 4, 2016
Gene Co-Expression Network Analysis for Identifying Modules and Functionally Enriched Pathways in Type 1 DiabetesIgnacio Riquelme Medina, Zelmina Lubovac-Pilav
BMC Bioinformatics|February 10, 2021
ComHub: Community predictions of hubs in gene regulatory networksJulia Åkesson, Zelmina Lubovac-Pilav, Rasmus Magnusson, et al.
Plos One|December 31, 2013
Using expression profiling to understand the effects of chronic cadmium exposure on MCF-7 breast cancer cellsZelmina Lubovac-Pilav, Daniel M Borràs, Esmeralda Ponce, et al.
BMC Bioinformatics|July 18, 2019
miRFA: an automated pipeline for microRNA functional analysis with correlation support from TCGA and TCPA expression data in pancreatic cancerEmmy Borgmästars, Hendrik Arnold de Weerd, Zelmina Lubovac-Pilav, et al.
Scientific Reports|November 17, 2022
Bioinformatics analysis of miRNAs in the neuroblastoma 11q-deleted region reveals a role of miR-548l in both 11q-deleted and MYCN amplified tumour cellsSanja Jurcevic, Simon Keane, Emmy Borgmästars, et al.
Bioinformatics Advances|January 26, 2023
MODalyseR-a novel software for inference of disease module hub regulators identified a putative multiple sclerosis regulator supported by independent eQTL dataHendrik A de Weerd, Julia Åkesson, Dimitri Guala, et al.
Bioinformatics (Oxford, England)|February 5, 2019
Batch-normalization of cerebellar and medulloblastoma gene expression datasets utilizing empirically defined negative control genesHolger Weishaupt, Patrik Johansson, Anders Sundström, et al.
Patterns (New York, N.Y.)|November 21, 2024
Latent space arithmetic on data embeddings from healthy multi-tissue human RNA-seq decodes disease modulesHendrik A de Weerd, Dimitri Guala, Mika Gustafsson, et al.
Bioinformatics (Oxford, England)|April 10, 2020
MODifieR: an Ensemble R Package for Inference of Disease Modules from Transcriptomics NetworksHendrik A de Weerd, Tejaswi V S Badam, David Martínez-Enguita, et al.
Pageof 2

Showing results (1-10 of 15) with videos related to

Sort By:
Pageof 2
BMC Bioinformatics|September 17, 2021
TFTenricher: a python toolbox for annotation enrichment analysis of transcription factor target genesRasmus Magnusson, Zelmina Lubovac-Pilav
Plos One|June 4, 2016
Gene Co-Expression Network Analysis for Identifying Modules and Functionally Enriched Pathways in Type 1 DiabetesIgnacio Riquelme Medina, Zelmina Lubovac-Pilav
BMC Bioinformatics|February 10, 2021
ComHub: Community predictions of hubs in gene regulatory networksJulia Åkesson, Zelmina Lubovac-Pilav, Rasmus Magnusson, et al.
Plos One|December 31, 2013
Using expression profiling to understand the effects of chronic cadmium exposure on MCF-7 breast cancer cellsZelmina Lubovac-Pilav, Daniel M Borràs, Esmeralda Ponce, et al.
BMC Bioinformatics|July 18, 2019
miRFA: an automated pipeline for microRNA functional analysis with correlation support from TCGA and TCPA expression data in pancreatic cancerEmmy Borgmästars, Hendrik Arnold de Weerd, Zelmina Lubovac-Pilav, et al.
Scientific Reports|November 17, 2022
Bioinformatics analysis of miRNAs in the neuroblastoma 11q-deleted region reveals a role of miR-548l in both 11q-deleted and MYCN amplified tumour cellsSanja Jurcevic, Simon Keane, Emmy Borgmästars, et al.
Bioinformatics Advances|January 26, 2023
MODalyseR-a novel software for inference of disease module hub regulators identified a putative multiple sclerosis regulator supported by independent eQTL dataHendrik A de Weerd, Julia Åkesson, Dimitri Guala, et al.
Bioinformatics (Oxford, England)|February 5, 2019
Batch-normalization of cerebellar and medulloblastoma gene expression datasets utilizing empirically defined negative control genesHolger Weishaupt, Patrik Johansson, Anders Sundström, et al.
Patterns (New York, N.Y.)|November 21, 2024
Latent space arithmetic on data embeddings from healthy multi-tissue human RNA-seq decodes disease modulesHendrik A de Weerd, Dimitri Guala, Mika Gustafsson, et al.
Bioinformatics (Oxford, England)|April 10, 2020
MODifieR: an Ensemble R Package for Inference of Disease Modules from Transcriptomics NetworksHendrik A de Weerd, Tejaswi V S Badam, David Martínez-Enguita, et al.
Pageof 2