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» Predicting Nucleolar Proteins Using Support-Vector Machines
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141
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ICML
2005
IEEE
16 years 4 months ago
Predicting protein folds with structural repeats using a chain graph model
Protein fold recognition is a key step towards inferring the tertiary structures from amino-acid sequences. Complex folds such as those consisting of interacting structural repeat...
Yan Liu, Eric P. Xing, Jaime G. Carbonell
177
Voted
TON
2010
167views more  TON 2010»
14 years 10 months ago
A Machine Learning Approach to TCP Throughput Prediction
TCP throughput prediction is an important capability in wide area overlay and multi-homed networks where multiple paths may exist between data sources and receivers. In this paper...
Mariyam Mirza, Joel Sommers, Paul Barford, Xiaojin...
BMCBI
2008
100views more  BMCBI 2008»
15 years 3 months ago
Hotspot Hunter: a computational system for large-scale screening and selection of candidate immunological hotspots in pathogen p
Background: T-cell epitopes that promiscuously bind to multiple alleles of a human leukocyte antigen (HLA) supertype are prime targets for development of vaccines and immunotherap...
Guanglan Zhang, Asif M. Khan, Kellathur N. Sriniva...
136
Voted
ICML
2010
IEEE
15 years 4 months ago
COFFIN: A Computational Framework for Linear SVMs
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...
Sören Sonnenburg, Vojtech Franc
131
Voted
AIIA
2007
Springer
15 years 7 months ago
Advanced Tree-Based Kernels for Protein Classification
One of the aims of modern Bioinformatics is to discover the molecular mechanisms that rule the protein operation. This would allow us to understand the complex processes involved i...
Elisa Cilia, Alessandro Moschitti