Search for dissertations about: "mathematical modelling with bayesian"
Showing result 11 - 15 of 19 swedish dissertations containing the words mathematical modelling with bayesian.
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11. Machine Learning methods in shotgun proteomics
Abstract : As high-throughput biology experiments generate increasing amounts of data, the field is naturally turning to data-driven methods for the analysis and extraction of novel insights. These insights into biological systems are crucial for understanding disease progression, drug targets, treatment development, and diagnostics methods, ultimately leading to improving human health and well-being, as well as, deeper insight into cellular biology. READ MORE
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12. Modelling Allelic and DNA Copy Number Variations using Continuous-index Hidden Markov Models
Abstract : In human cells there are usually two copies of each chromosome, but in cancer cells abnormalities could exist. The differences consist of segments of chromosomes with an altered number of copies. There can be deletions as well as amplifications and the lengths of the segments can also vary. READ MORE
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13. Latent variable models for longitudinal twin data
Abstract : Longitudinal twin data provide important information for exploring sources of variation in human traits. In statistical models for twin data, unobserved genetic and environmental factors influencing the trait are represented by latent variables. In this way, trait variation can be decomposed into genetic and environmental components. READ MORE
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14. Draw control strategy for sublevel caving mines : A holistic approach
Abstract : Sublevel caving is an underground mass mining method used for extracting different types of ores from the earth crust. Mines using sublevel caving (SLC) as the primary mining method are generally highly mechanized with standardized and independent unit operations. READ MORE
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15. On a learning system for industrial automation : Model-based control and diagnostics for decision support
Abstract : Access to energy is fundamental to economic and technological advancement. Hence, the more the world develops, the greater the demand for energy becomes. Evidently, the production and consumption of energy alone account for more than 80% of global anthropogenic greenhouse gas (GHG) emissions. READ MORE