𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Predicting nucleosome positioning using a duration Hidden Markov Model

✍ Scribed by Liqun Xi; Yvonne Fondufe-Mittendorf; Lei Xia; Jared Flatow; Jonathan Widom; Ji-Ping Wang


Book ID
114999207
Publisher
BioMed Central
Year
2010
Tongue
English
Weight
722 KB
Volume
11
Category
Article
ISSN
1471-2105

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


Predicting protein structure using hidde
✍ Karplus, Kevin; SjΓΆlander, Kimmen; Barrett, Christian; Cline, Melissa; Haussler, πŸ“‚ Article πŸ“… 1997 πŸ› John Wiley and Sons 🌐 English βš– 79 KB πŸ‘ 2 views

We discuss how methods based on hidden Markov models performed in the fold-recognition section of the CASP2 experiment. Hidden Markov models were built for a representative set of just over 1,000 structures from the Protein Data Bank (PDB). Each CASP2 target sequence was scored against this library

Disease surveillance using a hidden Mark
✍ Rochelle E Watkins; Serryn Eagleson; Bert Veenendaal; Graeme Wright; Aileen J Pl πŸ“‚ Article πŸ“… 2009 πŸ› BioMed Central 🌐 English βš– 687 KB
Haplotype inference using a Bayesian Hid
✍ Shuying Sun; Celia M.T. Greenwood; Radford M. Neal πŸ“‚ Article πŸ“… 2007 πŸ› John Wiley and Sons 🌐 English βš– 191 KB

## Abstract Knowledge of haplotypes is useful for understanding block structure in the genome and disease risk associations. Direct measurement of haplotypes in the absence of family data is presently impractical, and hence, several methods have been developed for reconstructing haplotypes from pop

Hidden Markov models that use predicted
✍ Jeanette Hargbo; Arne Elofsson πŸ“‚ Article πŸ“… 1999 πŸ› John Wiley and Sons 🌐 English βš– 112 KB πŸ‘ 2 views

There are many proteins that share the same fold but have no clear sequence similarity. To predict the structure of these proteins, so called ''protein fold recognition methods'' have been developed. During the last few years, improvements of protein fold recognition methods have been achieved throu