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Visar resultat 11 - 15 av 21 avhandlingar som matchar ovanstående sökkriterier.

1. 11. Inter and intra-tumor models of somatic evolution in cancer

   Författare :Mohammadreza Mohaghegh Neyshabouri; Jens Lagergren; Ben Raphael; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Cancer progression models; MCMC; Tillämpad matematik och beräkningsmatematik; Applied and Computational Mathematics;

   Sammanfattning : Cancer is a disease caused by the accumulation of somatic mutations in an evolutionary process. Mutations in so-called cancer driver genes provide the harboring cells with particular selective advantages and result in cancer progression. LÄS MER

3. 12. Bayesian Models for Spatiotemporal Data from Transportation Networks

   Författare :Héctor Rodriguez Déniz; Mattias Villani; Augusto Voltes-Dorta; Yusak Susilo; Linköpings universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Bayesian statistics; Transportation networks; Spatiotemporal data; Machine learning; Bayesiansk statistik; Transportnätverk; Spatiotemporal data; Maskininlärning;

   Sammanfattning : Urbanization has caused a historical transformation at a global scale, and humanity is moving towards a fully connected society where cities will concentrate population, infrastructure and economic activity. A key element in the cities’ infrastructure is the transportation system, as it facilitates the mobility of people and goods. LÄS MER

4. 13. Machine Learning methods in shotgun proteomics

   Författare :Patrick Truong; Lukas Käll; Peter Nilsson; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; mass spectrometry protein summarization Bayesian hierarchical modelling label-free quantification data-independent acquisition mass spectrometry; benchmark mathematical methods; transformers; computational proteomics; proteomics; bioinformatics; bert; ms2 intensity; probabilistic modelling; Biotechnology; Bioteknologi;

   Sammanfattning : 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. LÄS MER

5. 14. Chain Graphs : Interpretations, Expressiveness and Learning Algorithms

   Författare :Dag Sonntag; M. Jose Peña; Nahid Shahmehri; Jirka Vomlel; Linköpings universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Chain Graphs; Probabilitstic Grapical Models;

   Sammanfattning : Probabilistic graphical models are currently one of the most commonly used architectures for modelling and reasoning with uncertainty. The most widely used subclass of these models is directed acyclic graphs, also known as Bayesian networks, which are used in a wide range of applications both in research and industry. LÄS MER

7. 15. A Study of Chain Graph Interpretations

   Författare :Dag Sonntag; Jose M. Peña; Nahid Shahmehri; Jirka Vomlel; Linköpings universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY;

   Sammanfattning : Probabilistic graphical models are today one of the most well used architectures for modelling and reasoning about knowledge with uncertainty. The most widely used subclass of these models is Bayesian networks that has found a wide range of applications both in industry and research. LÄS MER