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Visar resultat 1 - 5 av 79 avhandlingar som matchar ovanstående sökkriterier.

1. 1. Network and gene expression analyses for understanding protein function

   Författare :Oliver Frings; Erik Sonnhammer; Rune Linding; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; biological networks; network inference; network analysis; clustering; network module; network crosstalk; expression analysis; gene signature; biomarker; biokemi; inriktning teoretisk kemi; Biochemistry with Emphasis on Theoretical Chemistry;

   Sammanfattning : Biological function is the result of a complex network of functional associations between genes or their products. Modeling the dynamics underlying biological networks is one of the big challenges in bioinformatics. LÄS MER

3. 2. Towards Reliable Gene Regulatory Network Inference

   Författare :Daniel Morgan; Erik Sonnhammer; John Quackenbush; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; GRN; network inference; biological systems; Biochemistry towards Bioinformatics; biokemi med inriktning mot bioinformatik;

   Sammanfattning : Phenotypic traits are now known to stem from the interplay between genetic variables across many if not every level of biology. The field of gene regulatory network (GRN) inference is concerned with understanding the regulatory interactions between genes in a cell, in order to build a model that captures the behaviour of the system. LÄS MER

4. 3. Exploring the Boundaries of Gene Regulatory Network Inference

   Författare :Andreas Tjärnberg; Erik Sonnhammer; Richard Bonneau; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; GRN; gene regulatory network; network inference; signal to noise ratio; model selection; variable selection; data properties; reverse engineering; ordinary differential equations; gene networks; linear regression; lasso; Biochemistry towards Bioinformatics; biokemi med inriktning mot bioinformatik;

   Sammanfattning : To understand how the components of a complex system like the biological cell interact and regulate each other, we need to collect data for how the components respond to system perturbations. Such data can then be used to solve the inverse problem of inferring a network that describes how the pieces influence each other. LÄS MER

5. 4. Robust inference of gene regulatory networks : System properties, variable selection, subnetworks, and design of experiments

   Författare :Torbjörn E. M. Nordling; Elling W Jacobsen; Rolf Findeisen; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; network inference; reverse engineering; variable selection; model selection; feature selection; subset selection; system identification; system theory; network theory; subnetworks; design of experiments; perturbation experiments; gene regulatory networks; biological networks;

   Sammanfattning : In this thesis, inference of biological networks from in vivo data generated by perturbation experiments is considered, i.e. deduction of causal interactions that exist among the observed variables. Knowledge of such regulatory influences is essential in biology. LÄS MER

7. 5. Percolation: Inference and Applications in Hydrology

   Författare :Oscar Hammar; Göteborgs universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; percolation; inference; consistency; Markov chain Monte Carlo; hydrology; consistency;

   Sammanfattning : Percolation theory is a branch of probability theory describing connectedness in a stochastic network. The connectedness of a percolation process is governed by a few, typically one or two, parameters. LÄS MER