An approach to histone nearest neighbours in extended chromatin

Extended k-Nearest Neighbours based on Evidence Theory

An evidence theoretic classification method is proposed in this paper. In order to classify a pattern we consider its neighbours, which are taken as parts of a single source of evidence to support the class membership of the pattern. A single mass function or basic belief assignment is then derived, and the belief function and the pignistic (“betting rates”) probability function can be calculat...

An Efficient Algorithm for Bayesian Nearest Neighbours

K-Nearest Neighbours (k-NN) is a popular classification and regression algorithm, yet one of its main limitations is the difficulty in choosing the number of neighbours. We present a Bayesian algorithm to compute the posterior probability distribution for k given a target point within a dataset, efficiently and without the use of Markov Chain Monte Carlo (MCMC) methods or simulation—alongside a...

Smoothing Using Nearest Neighbours

NAP1 modulates binding of linker histone H1 to chromatin and induces an extended chromatin fiber conformation.

NAP1 (nucleosome assembly protein 1) is a histone chaperone that has been described to bind predominantly to the histone H2A.H2B dimer in the cell during shuttling of histones into the nucleus, nucleosome assembly/remodeling, and transcription. Here it was examined how NAP1 interacts with chromatin fibers isolated from HeLa cells. NAP1 induced a reversible change toward an extended fiber confor...

An Approximate Nearest Neighbours Search Algorithm Based on the Extended General Spacefilling Curves Heuristic

In this paper, an algorithm for approximate nearest neighbours search in vector spaces is proposed. It is based on the Extended General Spacefilling Curves Heuristic (EGSH). Under this general scheme, a number of mappings are established between a region of a multidimensional real vector space and an interval of the real line, and then for each mapping the problem is solved in one dimension. To...