Essays about: "Gene Expression analysis"
Showing result 1 - 5 of 179 essays containing the words Gene Expression analysis.
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1. Regulatory Driven Clustering of Single-Cell Data; Clustering of single-cell RNA sequencing from glioblastoma with a novel mathematical method
University essay from Göteborgs universitet/Institutionen för matematiska vetenskaperAbstract : 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. READ MORE
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2. Predicting tumour growth-driving interactions from transcriptomic data using machine learning
University essay from Uppsala universitet/Neuroonkologi och neurodegenerationAbstract : 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. READ MORE
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3. Investigating the crosstalk between estrogen receptor beta in colorectal cancer and tumor-associated macrophages
University essay from KTH/ProteinvetenskapAbstract : 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. READ MORE
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4. Pseudomonas aeruginosa gene expression analysis using pangenome and PAO1 reference genomes
University essay from Lunds universitet/Examensarbeten i bioinformatikAbstract : 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. READ MORE
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5. Predicting Biomarkers/ Candidate Genes involved in iALL, using Rough Sets based Interpretable Machine Learning Model.
University essay from Uppsala universitet/Institutionen för biologisk grundutbildningAbstract : 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. READ MORE