Sökning: "gene expression analysis"
Visar resultat 1 - 5 av 186 uppsatser innehållade orden gene expression analysis.
1. Regulatory Driven Clustering of Single-Cell Data; Clustering of single-cell RNA sequencing from glioblastoma with a novel mathematical method
Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaperSammanfattning : Cancer is a leading cause of death worldwide. Single-cell RNA sequencing has arisen as an important method to explore the gene expression of biological cells, including cancer cells. In this study, we deployed a computational algorithm known as ScRegClust to dissect single-cell RNA-sequencing (scRNA-seq) data from brain tumors. LÄS MER
2. Predicting tumour growth-driving interactions from transcriptomic data using machine learning
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Neuroonkologi och neurodegenerationSammanfattning : The mortality rate is high for cancer patients and treatments are only efficient in a fraction of patients. To be able to cure more patients, new treatments need to be invented. Immunotherapy activates the immune system to fight against cancer and one treatment targets immune checkpoints. LÄS MER
3. Investigating the crosstalk between estrogen receptor beta in colorectal cancer and tumor-associated macrophages
Master-uppsats, KTH/ProteinvetenskapSammanfattning : Tjock-och ändtarmscancer (kolorektalcancer) är den tredje vanligaste cancertypen och den näst vanligaste cancer-relaterade dödsorsaken i världen. Östrogen har visat sig ha en skyddande roll mot kolorektalcancer och östrogenreceptor beta är den dominerande östrogenreceptorn i normalt kolonepitel. LÄS MER
4. Pseudomonas aeruginosa gene expression analysis using pangenome and PAO1 reference genomes
Master-uppsats, Lunds universitet/Examensarbeten i bioinformatikSammanfattning : Development in sequencing technologies has made the analyses of genetic material much more accessible. Processing sequenced data for an accurate analysis comes with its challenges, especially with the studies in microbial in clinical in vivo samples where difficulties in the collection of these samples for sequencing could lower the quality and contamination from the human host which might affect the accuracy of downstream analysis. LÄS MER
5. Predicting Biomarkers/ Candidate Genes involved in iALL, using Rough Sets based Interpretable Machine Learning Model.
Master-uppsats, Uppsala universitet/Institutionen för biologisk grundutbildningSammanfattning : Acute lymphoblastic leukemia is a hematological malignancy that gains a proliferative advantage and originates in the bone marrow. One of the more common genetic alterations in ALL is KMT2A-rearrangement which constitutes 80% of the cases of ALL in infants. LÄS MER