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ISMB
1994
13 years 5 months ago
Predicting Location and Structure Of beta-Sheet Regions Using Stochastic Tree Grammars
We describe and demonstrate the effectiveness of a method of predicting protein secondary structures, sheet regions in particular, using a class of stochastic tree grammars as rep...
Hiroshi Mamitsuka, Naoki Abe
CSB
2004
IEEE
208views Bioinformatics» more  CSB 2004»
13 years 8 months ago
Pair Stochastic Tree Adjoining Grammars for Aligning and Predicting Pseudoknot RNA Structures
Motivation: Since the whole genome sequences for many species are currently available, computational predictions of RNA secondary structures and computational identifications of t...
Hiroshi Matsui, Kengo Sato, Yasubumi Sakakibara
ICIP
2003
IEEE
14 years 6 months ago
Stochastic attributed K-d tree modeling of technical paper title pages
Structural information about a document is essential for structured query processing, indexing, and retrieval. A document page can be partitioned into a hierarchy of homogeneous r...
Song Mao, Azriel Rosenfeld, Tapas Kanungo
LATA
2010
Springer
13 years 11 months ago
Extending Stochastic Context-Free Grammars for an Application in Bioinformatics
We extend stochastic context-free grammars such that the probability of applying a production can depend on the length of the subword that is generated from the application and sho...
Frank Weinberg, Markus E. Nebel
ISMB
1993
13 years 5 months ago
Knowledge Discovery in GENBANK
Wedescribe various methods designed to discover knowledge in the GenBanknucleic acid sequence database. Using a grammatical model of gene structure, we create a parse tree of a ge...
Jeffery S. Aaronson, Juergen Haas, G. Christian Ov...