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BMCBI
2007
104views more  BMCBI 2007»
13 years 5 months ago
Joint mapping of genes and conditions via multidimensional unfolding analysis
Background: Microarray compendia profile the expression of genes in a number of experimental conditions. Such data compendia are useful not only to group genes and conditions base...
Katrijn Van Deun, Kathleen Marchal, Willem J. Heis...
FGR
2011
IEEE
255views Biometrics» more  FGR 2011»
12 years 9 months ago
Beyond simple features: A large-scale feature search approach to unconstrained face recognition
— Many modern computer vision algorithms are built atop of a set of low-level feature operators (such as SIFT [1], [2]; HOG [3], [4]; or LBP [5], [6]) that transform raw pixel va...
David D. Cox, Nicolas Pinto
BMCBI
2010
84views more  BMCBI 2010»
13 years 5 months ago
Testing the additional predictive value of high-dimensional molecular data
Background: While high-dimensional molecular data such as microarray gene expression data have been used for disease outcome prediction or diagnosis purposes for about ten years i...
Anne-Laure Boulesteix, Torsten Hothorn
TCSB
2008
13 years 5 months ago
Clustering Time-Series Gene Expression Data with Unequal Time Intervals
Clustering gene expression data given in terms of time-series is a challenging problem that imposes its own particular constraints, namely exchanging two or more time points is not...
Luis Rueda, Ataul Bari, Alioune Ngom
STOC
2003
ACM
188views Algorithms» more  STOC 2003»
14 years 5 months ago
Almost random graphs with simple hash functions
We describe a simple randomized construction for generating pairs of hash functions h1, h2 from a universe U to ranges V = [m] = {0, 1, . . . , m - 1} and W = [m] so that for ever...
Martin Dietzfelbinger, Philipp Woelfel