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AAAI
1998
15 years 5 months ago
Learning to Predict User Operations for Adaptive Scheduling
Mixed-initiativesystemspresent the challengeof finding an effective level of interaction betweenhumans and computers. Machinelearning presents a promising approachto this problemi...
Melinda T. Gervasio, Wayne Iba, Pat Langley
DSRT
2006
IEEE
15 years 10 months ago
Adaptive Interest Management via Push-Pull Algorithms
Interest Management in large-scale distributed applications aims to reduce the amount of extraneous broadcast communication between nodes in the system with the aim of increasing ...
Rob Minson, Georgios K. Theodoropoulos
BMCBI
2010
133views more  BMCBI 2010»
15 years 4 months ago
Predicting enzyme targets for cancer drugs by profiling human Metabolic reactions in NCI-60 cell lines
Background: Drugs can influence the whole metabolic system by targeting enzymes which catalyze metabolic reactions. The existence of interactions between drugs and metabolic react...
Limin Li, Xiaobo Zhou, Wai-Ki Ching, Ping Wang
BMCBI
2005
114views more  BMCBI 2005»
15 years 4 months ago
A new decoding algorithm for hidden Markov models improves the prediction of the topology of all-beta membrane proteins
Background: Structure prediction of membrane proteins is still a challenging computational problem. Hidden Markov models (HMM) have been successfully applied to the problem of pre...
Piero Fariselli, Pier Luigi Martelli, Rita Casadio
RECOMB
2011
Springer
14 years 7 months ago
Rich Parameterization Improves RNA Structure Prediction
Motivation. Current approaches to RNA structure prediction range from physics-based methods, which rely on thousands of experimentally-measured thermodynamic parameters, to machin...
Shay Zakov, Yoav Goldberg, Michael Elhadad, Michal...