Search Results for "big data"

Please cite: An, J., Lai, J., Lehman, M.L. and Nelson, C.C. (2013) miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data. Nucleic Acids Res, 41, 727-737. We will create index for you if you tell us your interested species (j.an@qut.edu.au). download command line version "MDS_command_line_Vxx.zip" clicking "Browse All Files" please find miRPlant in sourceforge for plant miRNA prediction.

MarDRe is a de novo MapReduce-based parallel tool to remove duplicate and near-duplicate DNA reads through the clustering of single-end and paired-end sequences from FASTQ/FASTA datasets. This tool allows bioinformatics to avoid the analysis of not necessary reads, reducing the time of subsequent procedures with the dataset. MarDRe is the Big Data counterpart of ParDRe (link above), which employs HPC technologies (i.e., hybrid MPI/multithreading) to reduce runtime on multicore systems. Instead, MarDRe takes advantage of the MapReduce programming model to significantly improve ParDRe performance on distributed systems, especially on cloud-based infrastructures. Written in pure Java to maximize cross-platform compatibility, MarDRe is built upon the open-source Apache Hadoop project, the most popular distributed computing framework for Big Data processing.

...This tool allows bioinformatics researchers to efficiently distribute their mapping tasks over the nodes of a cluster by combining a fast multithreaded spliced aligner (HISAT2) with Apache Hadoop, which is a distributed computing framework for scalable Big Data processing. HSRA currently supports single-end and paired-end read alignments from FASTQ/FASTA datasets. Moreover, our tool uses the Hadoop Sequence Parser (HSP) library (link above) to efficiently read the input datasets stored on the Hadoop Distributed File System (HDFS), being able to process datasets compressed with Gzip and BZip2 codecs.

A general OWL reasoning framework for the analysis of big biomedical data and implement a MapReduce-based property chain reasoning prototype system. OWL reasoning method is ideally suitable for problems involved complex semantic associations because it is able to infer logical consequences based on a set of asserted rules or axioms. MapReduce framework isused to solve the problem of scalability.

Biodiversity Information Group develops software tools and data standards that enable herbaria and museums to create dynamic distributed queries of their online databases. See http://bit.ly/bfirSh and http://bit.ly/bwpnSY for latest developments.