2D fingerprint based similarity searching using a single bioactive reference is the most popular and effective virtual screening tool. In our last paper, we have introduced a novel method for similarity searching using Bayesian inference network (BIN). In this study, we have compared BIN with other similarity searching methods when multiple bioactive reference molecules are available. Three dif...

Given n data points in d-dimensional space, nearest-neighbor searching involves determining the nearest of these data points to a given query point. Most averagecase analyses of nearest-neighbor searching algorithms are made under the simplifying assumption that d is fixed and that n is so large relative to d that boundary effects can be ignored. This means that for any query point the statisti...

TECHNIQUES FOR EFFICIENT K-NEAREST NEIGHBOR SEARCHING IN NON-ORDERED DISCRETE AND HYBRID DATA SPACES

We present NearptD, a very fast parallel nearest neighbor algorithm and implementation, which has processed 10 points in E and 184 · 10 points in E. It uses 1/5 the space and as little as 1/100 the preprocessing time FLANN (a well-known approximate nearest neighbor program). Up to E, its query time is also faster, by up to a factor of 100. NearptD uses Nvidia Thrust and CUDA in C++ to perform p...

Nearest neighbor searching is a fundamental building block of most sampling-based motion planners. We present a novel method for fast exact nearest neighbor searching in SE(3)—the 6 dimensional space that represents rotations and translations in 3 dimensions. SE(3) is commonly used when planning the motions of rigid body robots. Our approach starts by projecting a 4-dimensional cube onto the 3-...

Given a set of n points in d-dimensional Euclidean space, S E d , and a query point q 2 E d , we wish to determine the nearest neighbor of q, that is, the point of S whose Euclidean distance to q is minimum. The goal is to preprocess the point set S, such that queries can be answered as eeciently as possible. We assume that the dimension d is a constant independent of n. Although reasonably goo...

In our context, a complex vague query means a multifeature nearest neighbor query. Answering such queries requires the system to search on some feature spaces individually and then combine the searching results to find the final answers. The feature spaces are commonly multidimensional spaces and may consist of a vast amount of data. Therefore searching costs, including IO-cost and CPU-cost, ar...

In this work, one and two-dimensional lattices are studied theoretically by a statistical mechanical approach. The nearest and next-nearest neighbor interactions are both taken into account, and the approximate thermodynamic properties of the lattices are calculated. The results of our calculations show that: (1) even though the next-nearest neighbor interaction may have an insignificant ef...