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Visar resultat 1 - 5 av 79 avhandlingar som matchar ovanstående sökkriterier.
1. Integrating multi-omics for type 2 diabetes : Data science and big data towards personalized medicine
Sammanfattning : Type 2 diabetes (T2D) is a complex metabolic disease characterized by multi-tissue insulin resistance and failure of the pancreatic β-cells to secrete sufficient amounts of insulin. Cells recruit transcription factors (TF) to specific genomic loci to regulate gene expression that consequently affects the protein and metabolite abundancies. LÄS MER
2. Image-based multi-omics data integration : Exploring whole-body PET/MRI, -omics data and body composition
Sammanfattning : Advanced body composition analysis with whole-body imaging could uncover novel associations between regional tissue composition and metabolic disease. Imiomics is an automated image analysis framework that enables large-scale integration of magnetic resonance imaging (MRI) data and orthogonal technologies such as metabolomics and genomics for the detailed study of body composition. LÄS MER
3. Interpretation of variation in omics data : Applications in proteomics for sustainable agriculture
Sammanfattning : Biomarkers are used in molecular biology to predict characteristics of interest and are applied in agriculture to accelerate the breeding of target traits. Proteomics has emerged as a promising technology for improved markers by providing a closer view to the phenotype than conventional genome-based approaches. LÄS MER
4. Uncovering biomarkers and molecular heterogeneity of complex diseases : Utilizing the power of Data Science
Sammanfattning : 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. LÄS MER
5. Omics Data Analysis of Complex Diseases and Traits
Sammanfattning : Following the advent of the high-throughput techniques for producing massive omics data, new possibilities and challenges have also emerged in different fields of biology and medicine. Dealing with such data on different scales with different scopes such as genomics, transcriptomics, proteomics and metabolomics, demands appropriate data collection, preprocessing, statistical analysis, interpretation and visualization. LÄS MER