Search for dissertations about: "Computational Biology"
Showing result 6 - 10 of 287 swedish dissertations containing the words Computational Biology.
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6. Approximation and Online Algorithms with Applications in Computational Biology and Computational Geometry
Abstract : The main contributions of this thesis are in the area of approximation and online algorithm design and derivation of lower bounds on the approximability for a number of combinatorial optimization problems with applications in computational biology and computational geometry. Approximation and online algorithms are fundamental tools used to deal with computationally hard problems and problems in which the input is gradually disclosed over time. READ MORE
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7. Computational Protein Evolution : Modeling the Selectivity and Promiscuity of Engineered Enzymes
Abstract : Enzymes are biological catalysts that significantly increase the rate of all biochemical reactions that take place within cells and are essential to maintain life. Many questions regarding their function remain unknown. READ MORE
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8. Uncovering the genetics underlying host-parasite interactions during Plasmodium falciparum malaria transmission
Abstract : In eukaryotes, cellular differentiation is often orchestrated by programmed arrays of activation and repression of genes underlying the specific phenotypes of cell-types. To complete its life cycle, the single-celled Apicomplexan parasite Plasmodium falciparum, the most deadly of the human malaria parasites, must repeatedly differentiate and convert into unique cell types that can exploit niches within their human and mosquito hosts. READ MORE
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9. Multiscale Modeling in Systems Biology : Methods and Perspectives
Abstract : In the last decades, mathematical and computational models have become ubiquitous to the field of systems biology. Specifically, the multiscale nature of biological processes makes the design and simulation of such models challenging. READ MORE
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10. Manifold Learning in Computational Biology
Abstract : This thesis deals with manifold learning techniques and their application in gene expression data analysis. Manifold learning is the study of methods that aim to infer geometrical structure from data sampled from manifolds, enabling nonlinear solutions to various machine learning tasks. READ MORE