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TIT
2008
116views more  TIT 2008»
13 years 7 months ago
On the Complexity of Hardness Amplification
We study the task of transforming a hard function f, with which any small circuit disagrees on (1 - )/2 fraction of the input, into a harder function f , with which any small circ...
Chi-Jen Lu, Shi-Chun Tsai, Hsin-Lung Wu
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...
BMCBI
2005
73views more  BMCBI 2005»
13 years 7 months ago
Evaluation of Glycine max mRNA clusters
Background: Clustering the ESTs from a large dataset representing a single species is a convenient starting point for a number of investigations into gene discovery, genome evolut...
Ronald L. Frank, Fikret Erçal
UAIS
2008
104views more  UAIS 2008»
13 years 7 months ago
A knowledge-based sign synthesis architecture
This paper presents the modules that comprise a knowledge-based sign synthesis architecture for Greek sign language (GSL). Such systems combine natural language (NL) knowledge, mac...
Stavroula-Evita Fotinea, Eleni Efthimiou, George C...
AI
2002
Springer
13 years 7 months ago
The size distribution for Markov equivalence classes of acyclic digraph models
Bayesian networks, equivalently graphical Markov models determined by acyclic digraphs or ADGs (also called directed acyclic graphs or dags), have proved to be both effective and ...
Steven B. Gillispie, Michael D. Perlman