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Pair hidden Markov models on tree structures
Yasubumi Sakakibara
Department of Biosciences and Informatics
Research output
:
Contribution to journal
›
Article
›
peer-review
45
Citations (Scopus)
Overview
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Dive into the research topics of 'Pair hidden Markov models on tree structures'. Together they form a unique fingerprint.
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Mathematics
Tree Structure
92%
Alignment
84%
Markov Model
78%
Secondary Structure
20%
Context-free Grammar
11%
Gene
9%
Automata
8%
Sequence Analysis
6%
Tree Automata
6%
Comparative Analysis
5%
Genome
5%
Computational Experiments
5%
Protein
5%
Computational Methods
5%
Coding
4%
Pairwise
4%
Mathematical Model
3%
Model
3%
Observation
3%
Modeling
3%
Demonstrate
2%
Framework
2%
Concepts
2%
Chemical Compounds
RNA Sequence
100%
Secondary Structure
64%
Engineering & Materials Science
Hidden Markov models
74%
RNA
47%
Context free grammars
12%
Genes
9%
Computational methods
5%
Genomics
5%
Proteins
4%
Mathematical models
3%
Experiments
1%
Medicine & Life Sciences
Theoretical Models
22%
Untranslated RNA
20%
RNA
19%
Sequence Alignment
11%
Open Reading Frames
8%
Sequence Analysis
8%
Genes
7%
Genome
6%