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1. Post-translational regulation of cathepsin B, but not of other cysteine cathepsins, contributes to increased glioblastoma cell invasiveness in vitro
Boris Gole, María Beatriz Durán-Alonso, Vinko V. Dolenc, Tamara Lah Turnšek, 2009, izvirni znanstveni članek

Ključne besede: brain tumours, cysteine cathepsins, cystatins, glioma, invasion (biology), proteolysis, stefins
Celotno besedilo (povezava drugam)

2. iTRAQ based proteomic profiling reveals increased metabolic activity and cellular crosstalk in angiogenic compared to invasive glioblastoma phenotype
Uroš Rajčević, 2009, izvirni znanstveni članek

Ključne besede: iTRAQ, MALDI TOF/TOF, glioma, xenograft, tumor host interaction, cancer biomarker, invasion (biology), angiogenesis, bioinformatics
Celotno besedilo (povezava drugam)

3. Glioma proteomics
Simone P. Niclou, Fred Fack, Uroš Rajčević, 2010, pregledni znanstveni članek

Ključne besede: proteome, glioma, astrocytoma, brain tumour, mass spectrometry, biomarker, metabolomics
Celotno besedilo (povezava drugam)

4. Resveratrol reduces the invasive growth and promotes the acquisition of a long-lasting differentiated phenotype in human glioblastoma cells
Roberta Castino, Anja Pucer, Roberta Veneroni, Federica Morani, Claudia Peracchio, Tamara Lah Turnšek, Ciro Isidoro, 2011, izvirni znanstveni članek

Ključne besede: resveratrol, cancer, apoptosis, glioma, tumor invasion, cancer stem cells
Celotno besedilo (povezava drugam)

5. Algorithmically deduced FREM2 molecular pathway is a potent grade and survival biomarker of human gliomas
Marianna Zolotovskaia, Alja Zottel, Neja Šamec, Ivana Jovchevska, 2021, izvirni znanstveni članek

Ključne besede: glioma, glioblastoma, survival prognosis, FREM2, algorithmically deduced molecular pathway, transcriptomics
Celotno besedilo (datoteka, 4,76 MB) Gradivo ima več datotek! Več...

6. Brain Tumor Segmentation on MRI BraTS Data using convolutional neural networks: experimental study and comparison
Irena Dragičević, 2023, magistrsko delo

Ključne besede: master's theses, radiologic technology, convolutional neural networks, U-Net, BraTS, glioma segmentation, multimodal segmentation, medical image segmentation, machine learning
Celotno besedilo (datoteka, 4,11 MB)
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