Search for dissertations about: "HMMs"

Showing result 1 - 5 of 20 swedish dissertations containing the word HMMs.

  1. 1. Probabilistic Sequence Models with Speech and Language Applications

    Author : Gustav Eje Henter; W. Bastiaan Kleijn; Arne Leijon; Gernot Kubin; KTH; []
    Keywords : ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; Time series; acoustic modelling; speech synthesis; stochastic processes; causal-state splitting reconstruction; robust causal states; pattern discovery; Markov models; HMMs; nonparametric models; Gaussian processes; Gaussian process dynamical models; nonlinear Kalman filters; information theory; minimum entropy rate simplification; kernel density estimation; time-series bootstrap;

    Abstract : Series data, sequences of measured values, are ubiquitous. Whenever observations are made along a path in space or time, a data sequence results. To comprehend nature and shape it to our will, or to make informed decisions based on what we know, we need methods to make sense of such data. READ MORE

  2. 2. From protein sequence to structural instability and disease

    Author : Lixiao Wang; Uwe Sauer; Sven Hovmöller; Umeå universitet; []
    Keywords : protein domain; remote homologue; intrinsically disorder unstructured proteins; protein function; point mutation; protein family protein stability; HMMs; CRFs; SVMs;

    Abstract : A great challenge in bioinformatics is to accurately predict protein structure and function from its amino acid sequence, including annotation of protein domains, identification of protein disordered regions and detecting protein stability changes resulting from amino acid mutations. The combination of bioinformatics, genomics and proteomics becomes essential for the investigation of biological, cellular and molecular aspects of disease, and therefore can greatly contribute to the understanding of protein structures and facilitating drug discovery. READ MORE

  3. 3. Structural Information and Hidden Markov Models for Biological Sequence Analysis

    Author : Jeanette Tångrot; Bo Kågström; Uwe H. Sauer; Erik Sonnhammer; Umeå universitet; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; HMM; structure alignment; protein structure; secondary structure; remote homologue; annotation; domain family; protein family; protein superfamily; protein fold recognition; Bioinformatics; Bioinformatik;

    Abstract : Bioinformatics is a fast-developing field, which makes use of computational methods to analyse and structure biological data. An important branch of bioinformatics is structure and function prediction of proteins, which is often based on finding relationships to already characterized proteins. READ MORE

  4. 4. The use of structural information to improve biological sequence similarity searches

    Author : Jeanette Tångrot; Umeå universitet; []
    Keywords : NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Bioinformatik; Hidden Markov Model; HMM; protein structure alignment; protein structure superimposition; remote homologue; FISH-server; protein annotation; Bioinformatics; Bioinformatik;

    Abstract : Bioinformatics is a fast-developing field that make use of computational methods to analyse and structure biological data. An important branch of bioinformatics is structure and function prediction of proteins. To determine the structure of a protein is a crucial part in the characterisation of the molecule. READ MORE

  5. 5. Retroviral long Terminal Repeats; Structure, Detection and Phylogeny

    Author : Farid Benachenhou; Jonas Blomberg; Göran Sperber; Aris Katzourakis; Uppsala universitet; []
    Keywords : MEDICAL AND HEALTH SCIENCES; MEDICIN OCH HÄLSOVETENSKAP; MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Retrovirus; long terminal repeats; hidden Markov models; phylogeny; alignment; conserved motif; stem-loop; Clinical virology; Klinisk virologi; Klinisk virologi; Clinical Virology;

    Abstract : Long terminal repeats (LTRs) are non-coding repeats flanking the protein-coding genes of LTR retrotransposons. The variability of LTRs poses a challenge in studying them. Hidden Markov models (HMMs), probabilistic models widely used in pattern recognition, are useful in dealing with this variability. READ MORE