In this paper, hidden Markov models (HMMs) are discussed in the context of molecular biological sequence analysis. The statistics relevant in the HMM approach are described in detail. An HMM based method is used to analyze two proteins that contain short protein repeats (SPRs). As a benchmark, a state-of-the-art program for the detection of SPRs is also used for both proteins. Finally, an outlook for combination possibilities of HMMs with phylogenetic approaches is given
I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, includ...
Detecting similarity in biological sequences is a key element to understanding the mechanisms of lif...
Hidden Markov Models (HMMs) are widely used for biological sequence analysis because of their abilit...
Hidden Markov Models (HMMs) can be applied to several important problems in molecular biology. We in...
models in biological sequence analysis The vast increase of data in biology has meant that many aspe...
Hidden Markov model (HMM) techniques are used to model families of biological sequences. A smooth an...
We introduce the theory of Hidden Markov Models, with a brief historical description, and we describ...
Hidden Markov models (HMMs) have been extensively used in biological sequence analysis . HMMs and th...
Hidden Markov Models (HMMs) can be applied to several impor-tant problems in molecular biology. We i...
Hidden Markov Models (HMMs) became recently important and popular among bioinformatics researchers, ...
This tutorial was one of eight tutorials selected to be presented at the Third International Confere...
Hidden Markov models (HMMs) are well developed statistical models to capture hidden information from...
We deal with the problem of retrieving the repeated apparitions of given motifs in protein sequences...
Hidden Markov models (HMMs) are a highly effective means of modeling a family of unaligned sequences...
Plötz T, Fink GA. Pattern recognition methods for advanced stochastic protein sequence analysis usin...
I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, includ...
Detecting similarity in biological sequences is a key element to understanding the mechanisms of lif...
Hidden Markov Models (HMMs) are widely used for biological sequence analysis because of their abilit...
Hidden Markov Models (HMMs) can be applied to several important problems in molecular biology. We in...
models in biological sequence analysis The vast increase of data in biology has meant that many aspe...
Hidden Markov model (HMM) techniques are used to model families of biological sequences. A smooth an...
We introduce the theory of Hidden Markov Models, with a brief historical description, and we describ...
Hidden Markov models (HMMs) have been extensively used in biological sequence analysis . HMMs and th...
Hidden Markov Models (HMMs) can be applied to several impor-tant problems in molecular biology. We i...
Hidden Markov Models (HMMs) became recently important and popular among bioinformatics researchers, ...
This tutorial was one of eight tutorials selected to be presented at the Third International Confere...
Hidden Markov models (HMMs) are well developed statistical models to capture hidden information from...
We deal with the problem of retrieving the repeated apparitions of given motifs in protein sequences...
Hidden Markov models (HMMs) are a highly effective means of modeling a family of unaligned sequences...
Plötz T, Fink GA. Pattern recognition methods for advanced stochastic protein sequence analysis usin...
I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, includ...
Detecting similarity in biological sequences is a key element to understanding the mechanisms of lif...
Hidden Markov Models (HMMs) are widely used for biological sequence analysis because of their abilit...