The Open Collections site will be undergoing maintenance 8-11am PST on Tuesday Dec. 3rd. No service interruption is expected, but some features may be temporarily impacted.
- Library Home /
- Search Collections /
- Open Collections /
- Browse Collections /
- UBC Theses and Dissertations /
- HMM converter a tool box for hidden Markov models...
Open Collections
UBC Theses and Dissertations
UBC Theses and Dissertations
HMM converter a tool box for hidden Markov models with two novel, memory efficient parameter training algorithms Lam, Tin Yin
Abstract
Hidden Markov models (HMMs) are powerful statistical tools for biological sequence analysis. Many recently developed Bioinformatics applications employ variants of HMMs to analyze diverse types of biological data. It is typically fairly easy to design the states and the topological structure of an HMM. However, it can be difficult to estimate parameter values which yield a good prediction performance. As many HMM-based applications employ similar algorithms for generating predictions, it is also time-consuming and error-prone to have to re-implement these algorithms whenever a new HMM-based application is to be designed. This thesis addresses these challenges by introducing a tool-box, called HMMC0NvERTER, which only requires an XML-input file to define an HMM and to use it for sequence decoding and parameter training. The package not only allows for rapid proto-typing of HMM-based applications, but also incorporates several algorithms for sequence decoding and parameter training, including two new, linear memory algorithms for parameter training. Using this software package, even users without programming knowledge can quickly set up sophisticated HMMs and pair-HMMs and use them with efficient algorithms for parameter training and sequence analyses. We use HMMCONVERTER to construct a new comparative gene prediction program, called ANNOTAID, which can predict pairs of orthologous genes by integrating prior information about each input sequence probabilistically into the gene prediction process and into parameter training. ANNOTAID can thus be readily adapted to predict orthologous gene pairs in newly sequenced genomes.
Item Metadata
| Title |
HMM converter a tool box for hidden Markov models with two novel, memory efficient parameter training algorithms
|
| Creator | |
| Publisher |
University of British Columbia
|
| Date Issued |
2008
|
| Description |
Hidden Markov models (HMMs) are powerful statistical tools for biological sequence analysis.
Many recently developed Bioinformatics applications employ variants of HMMs to analyze
diverse types of biological data. It is typically fairly easy to design the states and the topological
structure of an HMM. However, it can be difficult to estimate parameter values which yield a
good prediction performance. As many HMM-based applications employ similar algorithms
for generating predictions, it is also time-consuming and error-prone to have to re-implement
these algorithms whenever a new HMM-based application is to be designed.
This thesis addresses these challenges by introducing a tool-box, called HMMC0NvERTER,
which only requires an XML-input file to define an HMM and to use it for sequence decoding
and parameter training. The package not only allows for rapid proto-typing of HMM-based
applications, but also incorporates several algorithms for sequence decoding and parameter
training, including two new, linear memory algorithms for parameter training. Using this
software package, even users without programming knowledge can quickly set up sophisticated
HMMs and pair-HMMs and use them with efficient algorithms for parameter training and
sequence analyses. We use HMMCONVERTER to construct a new comparative gene prediction
program, called ANNOTAID, which can predict pairs of orthologous genes by integrating prior
information about each input sequence probabilistically into the gene prediction process and
into parameter training. ANNOTAID can thus be readily adapted to predict orthologous gene
pairs in newly sequenced genomes.
|
| Extent |
2755022 bytes
|
| Genre | |
| Type | |
| File Format |
application/pdf
|
| Language |
eng
|
| Date Available |
2009-03-09
|
| Provider |
Vancouver : University of British Columbia Library
|
| Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
|
| DOI |
10.14288/1.0051281
|
| URI | |
| Degree | |
| Program | |
| Affiliation | |
| Degree Grantor |
University of British Columbia
|
| Graduation Date |
2009-05
|
| Campus | |
| Scholarly Level |
Graduate
|
| Rights URI | |
| Aggregated Source Repository |
DSpace
|
Item Media
Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International