Sökning: "Systems biology"

Visar resultat 6 - 10 av 696 avhandlingar innehållade orden Systems biology.

  1. 6. Proteomics as a multifaceted tool in medicine and environmental assessment

    Författare :Jacob Kuruvilla; Susana Cristobal; Mats Lindahl; Mikael Sigvardsson; Jean Armengaud; Linköpings universitet; []
    Nyckelord :MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; NATURVETENSKAP; MEDICIN OCH HÄLSOVETENSKAP; MEDICIN OCH HÄLSOVETENSKAP; NATURAL SCIENCES; MEDICAL AND HEALTH SCIENCES; MEDICAL AND HEALTH SCIENCES;

    Sammanfattning : Proteomics is evolving as a multi-faceted tool for addressing various biochemical and biomedical queries in the field of scientific research. This involves various stages, ranging from sample preparation to data analysis and biological interpretation. LÄS MER

  2. 7. Model-Based Hypothesis Testing in Biomedicine : How Systems Biology Can Drive the Growth of Scientific Knowledge

    Författare :Rikard Johansson; Gunnar Cedersund; Tomas Strömberg; Peter Strålfors; Marija Cvijovic; Linköpings universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; systems biology; modeling; ODE; hypothesis testing; falsificationism; insulin signaling; yeast; population heterogeneity; cell-to-cell variation; facilitation; pyramidal; synaptic; bootstrapping; personalized medicine; omics;

    Sammanfattning : The utilization of mathematical tools within biology and medicine has traditionally been less widespread compared to other hard sciences, such as physics and chemistry. However, an increased need for tools such as data processing, bioinformatics, statistics, and mathematical modeling, have emerged due to advancements during the last decades. LÄS MER

  3. 8. Large-scale simulation-based experiments with stochastic models using machine learning-assisted approaches : Applications in systems biology using Markov jump processes

    Författare :Fredrik Wrede; Andreas Hellander; Ramon Grima; Uppsala universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; NATURAL SCIENCES; bioinformatics; systems biology; stochastic simulation; model exploration; approximate parameter inference; machine learning; distributed computing; Scientific Computing; Beräkningsvetenskap;

    Sammanfattning : Discrete and stochastic models in systems biology, such as biochemical reaction networks, can be modeled as Markov jump processes. The chemical master equation describes how the probability distribution of a biochemical system's states evolves. Unfortunately, solutions to the chemical master equation only exist for trivial problems. LÄS MER

  4. 9. Development of Computational Methods for Cancer Research: Strategies for closing the feedback loop in omics workflows

    Författare :Ufuk Kirik; Institutionen för immunteknologi; []
    Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; MEDICIN OCH HÄLSOVETENSKAP; NATURAL SCIENCES; NATURAL SCIENCES; MEDICAL AND HEALTH SCIENCES; cancer; proteome profiling; bioinformatics; pathway analysis; mass spectrometry; Quantitative proteomics;

    Sammanfattning : 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. LÄS MER

  5. 10. Rule-Based Approaches for Large Biological Datasets Analysis : A Suite of Tools and Methods

    Författare :Marcin Kruczyk; Jan Komorowski; Joaquin Dopazo; []
    Nyckelord :MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURVETENSKAP; MEDICIN OCH HÄLSOVETENSKAP; NATURAL SCIENCES; NATURAL SCIENCES; MEDICAL AND HEALTH SCIENCES; Rough sets; peak finding; gliomas; Alzheimer disease; STAT3; machine learning; feature selection; next generation sequencing;

    Sammanfattning : This thesis is about new and improved computational methods to analyze complex biological data produced by advanced biotechnologies. Such data is not only very large but it also is characterized by very high numbers of features. LÄS MER