Results 1 - 10 of 11,425

Linear models and empirical bayes methods for assessing differential expression in microarray experiments.

by Gordon K Smyth , Gordon K Smyth - Stat. Appl. Genet. Mol. Biol. , 2004
"... Abstract The problem of identifying differentially expressed genes in designed microarray experiments is considered. Lonnstedt and Speed (2002) derived an expression for the posterior odds of differential expression in a replicated two-color experiment using a simple hierarchical parametric model. ..."
Abstract - Cited by 1321 (24 self) - Add to MetaCart
-null prior for the fold changes are not required. The moderated t-statistic is shown to follow a t-distribution with augmented degrees of freedom. The moderated t inferential approach extends to accommodate tests of composite null hypotheses through the use of moderated F-statistics. The performance

A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection

by Ron Kohavi - INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE , 1995
"... We review accuracy estimation methods and compare the two most common methods: cross-validation and bootstrap. Recent experimental results on artificial data and theoretical results in restricted settings have shown that for selecting a good classifier from a set of classifiers (model selection), te ..."
Abstract - Cited by 1283 (11 self) - Add to MetaCart
-validation, we vary the number of folds and whether the folds are stratified or not; for bootstrap, we vary the number of bootstrap samples. Our results indicate that for real-word datasets similar to ours, the best method to use for model selection is ten-fold stratified cross validation, even if computation

A Bayesian Framework for the Analysis of Microarray Expression Data: Regularized t-Test and Statistical Inferences of Gene Changes

by Pierre Baldi, Anthony D. Long - Bioinformatics , 2001
"... Motivation: DNA microarrays are now capable of providing genome-wide patterns of gene expression across many different conditions. The first level of analysis of these patterns requires determining whether observed differences in expression are significant or not. Current methods are unsatisfactory ..."
Abstract - Cited by 491 (6 self) - Add to MetaCart
-test or fold methods, and partly compensate for the lack of replication. Availability: The approach is implemented in a software called Cyber-T accessible through a Web interface at www.genomics.uci.edu/software.html. The code is available as Open Source and is written in the freely available statistical

Model-Based Analysis of Oligonucleotide Arrays: Model Validation, Design Issues and Standard Error Application

by Cheng Li, Wing Hung Wong , 2001
"... Background: A model-based analysis of oligonucleotide expression arrays we developed previously uses a probe-sensitivity index to capture the response characteristic of a specific probe pair and calculates model-based expression indexes (MBEI). MBEI has standard error attached to it as a measure of ..."
Abstract - Cited by 775 (28 self) - Add to MetaCart
correlations with the original 20-probe PM/MM difference model. MBEI method is able to extend the reliable detection limit of expression to a lower mRNA concentration. The standard errors of MBEI can be used to construct confidence intervals of fold changes, and the lower confidence bound of fold change is a

A Sequential Algorithm for Training Text Classifiers

by David D. Lewis, William A. Gale , 1994
"... The ability to cheaply train text classifiers is critical to their use in information retrieval, content analysis, natural language processing, and other tasks involving data which is partly or fully textual. An algorithm for sequential sampling during machine learning of statistical classifiers was ..."
Abstract - Cited by 631 (10 self) - Add to MetaCart
was developed and tested on a newswire text categorization task. This method, which we call uncertainty sampling, reduced by as much as 500-fold the amount of training data that would have to be manually classified to achieve a given level of effectiveness. 1 Introduction Text classification is the automated

A discriminatively trained, multiscale, deformable part model

by Pedro Felzenszwalb, David Mcallester, Deva Ramanan - In IEEE Conference on Computer Vision and Pattern Recognition (CVPR-2008 , 2008
"... This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the best performance in the 2006 PASCAL person detection challenge. It also outperforms the best results in the 2007 challenge ..."
Abstract - Cited by 555 (11 self) - Add to MetaCart
This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the best performance in the 2006 PASCAL person detection challenge. It also outperforms the best results in the 2007

Dual polyhedra and mirror symmetry for Calabi–Yau hypersurfaces in toric varieties

by Victor V. Batyrev - J. Alg. Geom , 1994
"... We consider families F(∆) consisting of complex (n − 1)-dimensional projective algebraic compactifications of ∆-regular affine hypersurfaces Zf defined by Laurent polynomials f with a fixed n-dimensional Newton polyhedron ∆ in n-dimensional algebraic torus T = (C ∗ ) n. If the family F(∆) defined by ..."
Abstract - Cited by 467 (20 self) - Add to MetaCart
that the properties of this duality coincide with the properties of Mirror Symmetry discovered by physicists for Calabi-Yau 3-folds. Our method allows to construct many new examples of Calabi-Yau 3-folds and new candidates for their mirrors which were previously unknown for physicists. We conjecture that there exists

Hidden Markov models for detecting remote protein homologies

by Kevin Karplus, Christian Barrett, Richard Hughey - Bioinformatics , 1998
"... A new hidden Markov model method (SAM-T98) for nding remote homologs of protein sequences is described and evaluated. The method begins with a single target sequence and iteratively builds a hidden Markov model (hmm) from the sequence and homologs found using the hmm for database search. SAM-T98 is ..."
Abstract - Cited by 462 (15 self) - Add to MetaCart
is also used to construct model libraries automatically from sequences in structural databases. We evaluate the SAM-T98 method with four datasets. Three of the test sets are fold-recognition tests, where the correct answers are determined by structural similarity. The fourth uses a curated database

REMARKS ON MIURA-ORI, A JAPANESE FOLDING METHOD

by Hellmuth Stachel - ACTA TECHNICA NAPOCENSIS , 2009
"... Miura-ori is a Japanese folding technique named after Prof. Koryo Miura, The University of Tokyo. It is used for solar panels because it can be unfolded into its rectangular shape by pulling on one corner only. On the other hand it is used as kernel to stiffen sandwich structures. In this paper some ..."
Abstract - Cited by 5 (3 self) - Add to MetaCart
some insight will be given into the geometric structure of this folding method combined with an outlook to analogues and generalizations.

A FOLDING METHOD FOR EXTREME QUANTILES ESTIMATION Authors:

by Armelle Guillou, Alexandre You
"... In order to estimate extreme quantiles from independent and identically distributed random variables, we propose and study a novel folding procedure that improves quantile estimates obtained from the classical Peaks-Over-Threshold method (POT) used in Extreme Value Theory. The idea behind the foldin ..."
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In order to estimate extreme quantiles from independent and identically distributed random variables, we propose and study a novel folding procedure that improves quantile estimates obtained from the classical Peaks-Over-Threshold method (POT) used in Extreme Value Theory. The idea behind
Results 1 - 10 of 11,425