Developing Leave One Out GFP Based Biosensors

GFP-Based Biosensors

Green fluorescent protein (GFP) is a 27 kD protein consisting of 238 amino acid residues [1]. GFP was first identified in the aquatic jellyfish Aequorea victoria by Osamu Shimomura et al. in 1961 while studying aequorin, a Ca2+-activated photoprotein.Aequorin and GFP are local‐ ized in the light organs of A. victoria and GFP was accidentally discovered when the energy of the blue light emitted ...

The Leave - one - out

The Leave-One-Out Kernel

Recently, several attempts have been made for deriving datadependent kernels from distribution estimates with parametric models (e.g. the Fisher kernel). In this paper, we propose a new kernel derived from any distribution estimators, parametric or nonparametric. This kernel is called the Leave-one-out kernel (i.e. LOO kernel), because the leave-one-out process plays an important role to comput...

Leave-One-Out Support Vector Machines

We present a new learning algorithm for pattern recognition inspired by a recent upper bound on leave-one-out error [Jaakkola and Haussler, 1999] proved for Support Vector Machines {SVMs) [Vapnik, 1995; 1998]. The new approach directly minimizes the expression given by the bound in an attempt to minimize leave-one-out error. This gives a convex optimization problem which constructs a sparse lin...

Fast leave-one-out evaluation for dynamic gene selection

Gene selection procedure is a necessary step to increase the accuracy of machine learning algorithms that help in disease diagnosis based on gene expression data. This is commonly known as a feature subset selection problem in machine learning domain. A fast leave-one-out (LOO) evaluation formula for least-squares support vector machines (LSSVMs) is introduced here that can guide our backward f...