Search

The human genome reference sequence remains incomplete owing to the challenge of assembling long tracts of near-identical tandem repeats in centromeres. We implemented a nanopore sequencing strategy to generate high-quality reads that span hundreds of kilobases of highly repetitive DNA in a human Y chromosome centromere. Combining these data with short-read variant validation, we assembled and characterized the centromeric region of a human Y chromosome.

By RICKY GRIGG. Honolulu: Editions Limited, 1998. 180 pp.; maps, ills. $35.00 (cloth), ISBN O915013207; $25.00 (paper), ISBN 0915013215. It might seem a not unreasonable proposition that the lives of [...]

BECOMING--AND BEING--PETER GOULD Although the title of Peter Gould's latest--and last--book, Becoming a Geographer (1999), suggests an autobiography, it consists of an infusion of papers written over almost forty years, [...]

Registration of range images of surfaces is a fundamental problem in three-dimensional modelling. This process is performed by finding a rotation matrix and translation vector between two sets of data points requiring registration. Many techniques have been developed to solve the registration problem. Therefore, it is important to understand the accuracy of various registration techniques when we decide which technique will be selected to perform registration task. This paper presents a new approach to test and compare registration techniques in terms of accuracy. Among various registration methods, iterative closest point-based algorithms and reference marker methods are two types of commonly applied methods which are used to accomplish this task because they are easy to implement and relatively low cost. These two methods have been selected to perform a comprehensively quantitative evaluation by using the proposed method and the registration results are verified using the calibrated NPL freeform standard. [ABSTRACT FROM PUBLISHER]

Three dimensional (3-D) modeling is important in applications ranging from manufacturing to entertainment. Multiview registration is one of the crucial steps in 3-D model construction. The automatic establishment of correspondences between overlapping views, without any known initial information, is the main challenge in point clouds registration. An automatic registration algorithm is proposed to solve the registration problem of rigid, unordered, scattered point clouds. This approach is especially suitable for registering datasets that are lacking in features or texture. In general, the existing techniques exhibit significant limitations in the registration of these types of point cloud data. The presented method automatically determines the best coarse registration results by exploiting the statistical technique principal component analysis and outputs translation matrices as the initial estimation for fine registration. Then, the translation matrices obtained from coarse registration algorithms are used to update the original point cloud and the optimal translation matrices are solved using an iterative algorithm. Experimental results show that the proposed algorithm is time efficient and accurate, even if the point clouds are partially overlapped and containing large missing regions. [ABSTRACT FROM AUTHOR]