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» Scalable, updatable predictive models for sequence data
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RECOMB
2002
Springer
14 years 8 months ago
From promoter sequence to expression: a probabilistic framework
We present a probabilistic framework that models the process by which transcriptional binding explains the mRNA expression of different genes. Our joint probabilistic model unifie...
Eran Segal, Yoseph Barash, Itamar Simon, Nir Fried...
BMCBI
2010
118views more  BMCBI 2010»
13 years 7 months ago
Predicting nucleosome positioning using a duration Hidden Markov Model
Background: The nucleosome is the fundamental packing unit of DNAs in eukaryotic cells. Its detailed positioning on the genome is closely related to chromosome functions. Increasi...
Liqun Xi, Yvonne Fondufe-Mittendorf, Lei Xia, Jare...
UAI
2004
13 years 9 months ago
Blind Construction of Optimal Nonlinear Recursive Predictors for Discrete Sequences
We present a new method for nonlinear prediction of discrete random sequences under minimal structural assumptions. We give a mathematical construction for optimal predictors of s...
Cosma Rohilla Shalizi, Kristina Lisa Shalizi
BMCBI
2005
141views more  BMCBI 2005»
13 years 7 months ago
A method for the prediction of GPCRs coupling specificity to G-proteins using refined profile Hidden Markov Models
Background: G- Protein coupled receptors (GPCRs) comprise the largest group of eukaryotic cell surface receptors with great pharmacological interest. A broad range of native ligan...
Nikolaos G. Sgourakis, Pantelis G. Bagos, Panagiot...
ISPDC
2008
IEEE
14 years 2 months ago
Load Balancing in Mesh-like Computations using Prediction Binary Trees
We present a load-balancing technique that exploits the temporal coherence, among successive computation phases, in mesh-like computations to be mapped on a cluster of processors....
Biagio Cosenza, Gennaro Cordasco, Rosario De Chiar...