HISAT-3N: a rapid and accurate three-nucleotide sequence aligner

Nucleotide conversion sequencing technologies such as bisulfite-seq and SLAM-seq are powerful tools to explore the intricacies of cellular processes. In this paper, we describe HISAT-3N (hierarchical indexing for spliced alignment of transcripts - 3 nucleotides), which rapidly and accurately aligns sequences consisting of nucleotide conversions by leveraging powerful hierarchical index and repeat index algorithms originally developed for the HISAT software. Tests on real and simulated data sets demonstrate that HISAT-3N is over 7 times faster, has greater alignment accuracy, and has smaller memory requirements than other modern systems. Taken together HISAT-3N is the ideal aligner for use with converted sequence technologies.

Evaluating the presence of marketing capabilities: A multidimensional, hierarchical index

We propose a multidimensional instrument to assess the degree of presence of marketing capabilities a firm possesses, at three levels of abstraction. We first present the theoretical framework for marketing capabilities and discuss the main scales proposed by Vorhies et al. Then, we detail the steps required to develop and validate our third-order formative instrument. We assess the convergent and discriminant validity of the proposed instrument via partial least squares path modelling (PLS-PM) applied to a sample of 199 French small- and medium-sized enterprises (SMEs). Finally, we check the nomological validity of our instrument by testing the positive effect of marketing capabilities on organisational performance.

Efficient Querying Distributed Big-XML Data using MapReduce

MapReduce is a widely adopted computing framework for data-intensive applications running on clusters. This paper proposed an approach to exploit data parallelisms in XML processing using MapReduce in Hadoop. The authors' solution seamlessly integrates data storage, labeling, indexing, and parallel queries to process a massive amount of XML data. Specifically, the authors introduce an SDN labeling algorithm and a distributed hierarchical index using DHTs. More importantly, an advanced two-phase MapReduce solution are designed that is able to efficiently address the issues of labeling, indexing, and query processing on big XML data. The experimental results show the efficiency and effectiveness of the proposed parallel XML data approach using Hadoop.