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» Input Modeling Using Quantile Statistical Methods
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BMCBI
2011
14 years 4 months ago
In-silico prediction of disorder content using hybrid sequence representation
Background: Intrinsically disordered proteins play important roles in various cellular activities and their prevalence was implicated in a number of human diseases. The knowledge ...
Marcin J. Mizianty, Tuo Zhang, Bin Xue, Yaoqi Zhou...
123
Voted
CVPR
2006
IEEE
16 years 2 months ago
Groupwise point pattern registration using a novel CDF-based Jensen-Shannon Divergence
In this paper, we propose a novel and robust algorithm for the groupwise non-rigid registration of multiple unlabeled point-sets with no bias toward any of the given pointsets. To...
Fei Wang, Baba C. Vemuri, Anand Rangarajan
94
Voted
NIPS
2007
15 years 2 months ago
Expectation Maximization and Posterior Constraints
The expectation maximization (EM) algorithm is a widely used maximum likelihood estimation procedure for statistical models when the values of some of the variables in the model a...
João Graça, Kuzman Ganchev, Ben Task...
101
Voted
BIBM
2007
IEEE
159views Bioinformatics» more  BIBM 2007»
15 years 7 months ago
Predicting Future High-Cost Patients: A Real-World Risk Modeling Application
Health care data from patients in the Arizona Health Care Cost Containment System, Arizona’s Medicaid program, provides a unique opportunity to exploit state-of-the-art data pro...
Sai T. Moturu, William G. Johnson, Huan Liu
105
Voted
DAC
2003
ACM
15 years 6 months ago
Low-power design methodology for an on-chip bus with adaptive bandwidth capability
This paper describes a low-power design methodology for a bus architecture based on hybrid current/voltage mode signaling for deep sub-micrometer on-chip interconnects that achiev...
Rizwan Bashirullah, Wentai Liu, Ralph K. Cavin III