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RECOMB
2008
Springer
16 years 42 min ago
A Bayesian Approach to Protein Inference Problem in Shotgun Proteomics
The protein inference problem represents a major challenge in shotgun proteomics. Here we describe a novel Bayesian approach to address this challenge that incorporates the predict...
Yong Fuga Li, Randy J. Arnold, Yixue Li, Predrag R...
BIOINFORMATICS
2007
83views more  BIOINFORMATICS 2007»
14 years 11 months ago
Exploring biological network structure using exponential random graph models
Motivation: The functioning of biological networks depends in large part on their complex underlying structure. When studying their systemic nature many modeling approaches focus ...
Zachary M. Saul, Vladimir Filkov
BMCBI
2004
185views more  BMCBI 2004»
14 years 11 months ago
Linear fuzzy gene network models obtained from microarray data by exhaustive search
Background: Recent technological advances in high-throughput data collection allow for experimental study of increasingly complex systems on the scale of the whole cellular genome...
Bahrad A. Sokhansanj, J. Patrick Fitch, Judy N. Qu...
JCP
2008
190views more  JCP 2008»
14 years 11 months ago
Real-time System Identification of Unmanned Aerial Vehicles: A Multi-Network Approach
In this paper, real-time system identification of an unmanned aerial vehicle (UAV) based on multiple neural networks is presented. The UAV is a multi-input multi-output (MIMO) nonl...
Vishwas R. Puttige, Sreenatha G. Anavatti
NC
2010
150views Neural Networks» more  NC 2010»
14 years 10 months ago
Deterministic and stochastic P systems for modelling cellular processes
This paper presents two approaches based on metabolic and stochastic P systems, together with their associated analysis methods, for modelling biological systems and illustrates th...
Marian Gheorghe, Vincenzo Manca, Francisco Jos&eac...