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Richard S. Sandstrom

dblp:196/3975 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2012
0000-0002-3356-1547ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › genomics
genomic data compression
0.112012
BEDOPS: high-performance genomic feature operations · Bioinform. 2012
Bioinformatics and computational biology › genomics › genomic interval analysis
genomic interval operations
0.112012
BEDOPS: high-performance genomic feature operations · Bioinform. 2012
Bioinformatics and computational biology
genomics
0.112012
BEDOPS: high-performance genomic feature operations · Bioinform. 2012
Bioinformatics and computational biology › genomics › genomic data compression
lossless compression
0.112012
BEDOPS: high-performance genomic feature operations · Bioinform. 2012

Methods — techniques the papers use, named apart from their topics

parallel processing · 0.1interval tree · 0.1
YearPublicationVenuePosition
2012 BEDOPS: high-performance genomic feature operations
abstract
Abstract Summary: The large and growing number of genome-wide datasets highlights the need for high-performance feature analysis and data comparison methods, in addition to efficient data storage and retrieval techniques. We introduce BEDOPS, a software suite for common genomic analysis tasks which offers improved flexibility, scalability and execution time characteristics over previously published packages. The suite includes a utility to compress large inputs into a lossless format that can provide greater space savings and faster data extractions than alternatives. Availability: http://code.google.com/p/bedops/ includes binaries, source and documentation. Contact: [email protected] and [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.
Shane J. Neph, Scott Kuehn, Alex P. Reynolds, Eric Haugen, Robert E. Thurman, Audra K. Johnson, Eric Rynes, Matthew T. Maurano, Jeff Vierstra, Sean Thomas, Richard S. Sandstrom, Richard Humbert, John A. Stamatoyannopoulos
Bioinform.11