Next-generation sequencing (NGS) technologies allow the sequencing of microbial communities directly from the environment without prior culturing. The output of environmental DNA sequencing consists of many reads from genomes of different unknown species, making the clustering together reads from the same (or similar) species (also known as binning) a crucial step. The difficulties of the binni...

Gaussian kernel regularization is widely used in the machine learning literature and has proved successful in many empirical experiments. The periodic version of Gaussian kernel regularization has been shown to be minimax rate optimal in estimating functions in any finite order Sobolev space. However, for a data set with n points, the computation complexity of the Gaussian kernel regularization...

BACKGROUND Traditional cine imaging for cardiac functional assessment requires breath-holding, which can be problematic in some situations. Free-breathing techniques have relied on multiple averages or real-time imaging, producing images that can be spatially and/or temporally blurred. To overcome this, methods have been developed to acquire real-time images over multiple cardiac cycles, which ...

One very effective method for managing large data sets is aggregation or binning. In this paper we consider two aggregation methods that are tightly coupled with interactive manipulation and the visual representation of the data. Through this integration we hope to provide effective support for the aggregation process, specifically by enabling: 1) automatic aggregation, 2) continuous change and...

ClaMS - "Classifier for Metagenomic Sequences" - is a Java application for binning assembled contigs in metagenomes using user-specified training sets and initial parameters. Since ClaMS trains on sequence composition-based genomic signatures, it is much faster than binning tools that rely on alignments to homologs; ClaMS can bin ~20,000 sequences in 3 minutes on a laptop with a 2.4 GH× Intel C...

Article history: Received 23 February 2017 Received in revised form 16 May 2017 Accepted 21 May 2017 Available online xxxx