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BMCBI
2005
89views more  BMCBI 2005»
13 years 5 months ago
An empirical analysis of training protocols for probabilistic gene finders
Background: Generalized hidden Markov models (GHMMs) appear to be approaching acceptance as a de facto standard for state-of-the-art ab initio gene finding, as evidenced by the re...
William H. Majoros, Steven Salzberg
ICCV
2011
IEEE
12 years 5 months ago
Localized Principal Component Analysis based Curve Evolution: A Divide and Conquer Approach
We propose a novel localized principal component analysis (PCA) based curve evolution approach which evolves the segmenting curve semi-locally within various target regions (divis...
Vikram Appia, Balaji Ganapathy, Tracy Faber, Antho...
CSDA
2008
128views more  CSDA 2008»
13 years 5 months ago
Assessing agreement of clustering methods with gene expression microarray data
In the rapidly evolving field of genomics, many clustering and classification methods have been developed and employed to explore patterns in gene expression data. Biologists face...
Xueli Liu, Sheng-Chien Lee, George Casella, Gary F...
ISI
2008
Springer
13 years 5 months ago
Probabilistic frameworks for privacy-aware data mining
Often several cooperating parties would like to have a global view of their joint data for various data mining objectives, but cannot reveal the contents of individual records due...
Joydeep Ghosh
KDD
2005
ACM
149views Data Mining» more  KDD 2005»
13 years 10 months ago
A distributed learning framework for heterogeneous data sources
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Srujana Merugu, Joydeep Ghosh