Search for dissertations about: "Cancer bioinformatics"
Showing result 1 - 5 of 123 swedish dissertations containing the words Cancer bioinformatics.
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1. Development of Computational Methods for Cancer Research: Strategies for closing the feedback loop in omics workflows
Abstract : As the ultimate workhorses of the living things, proteins undergo significant regulatory activity throughout the lifetime of a cell or an organism. Many complex diseases effect the protein composition, expression or modification in the cells or tissues they arise in. READ MORE
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2. Copy Number Analysis of Cancer
Abstract : By accurately describing cancer genomes, we may link genomic mutations to phenotypic effects and eventually treat cancer patients based on the molecular cause of their disease, rather than generalizing treatment based on cell morphology or tissue of origin.Alteration of DNA copy number is a driving mutational process in the formation and progression of cancer. READ MORE
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3. RNA Sequencing for Molecular Diagnostics in Breast Cancer
Abstract : Breast cancer is the most common type of cancer in women and, in Sweden, is the most deadly second only to lung cancer. While treatment and diagnostic options have improved in the past decades and short- to mid-term survival is good, long-term survival is much poorer. READ MORE
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4. Utilization of single-cell RNA-Seq and genome-scale modeling for investigating cancer metabolism
Abstract : Cancer remains a leading cause of death worldwide, and its dysregulated metabolism is a promising target for therapy. However, metabolism is complex to study – the metabolism of a cell involves the interplay of thousands of chemical reactions that are combined in different ways across tissues and cell types. READ MORE
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5. Uncovering biomarkers and molecular heterogeneity of complex diseases : Utilizing the power of Data Science
Abstract : Uncovering causal drivers of complex diseases is yet a difficult challenge. Unlike single-gene disorders complex diseases are heterogeneous and are caused by a combination of genetic, environmental, and lifestyle factors which complicates the identification of patient subgroups and the disease causal drivers. READ MORE