Results 261 to 270 of about 1,730,357 (294)

Protocol for evaluating RNA-protein associations in mammalian cells with RIP-seq and RIP-qPCR. [PDF]

STAR Protoc
Trotman JB, Li S, Eberhard QE, Zhang Z, Calabrese JM.   +4 more
europepmc   +1 more source

A digitization workflow of dry-pinned collections of Lepidoptera. [PDF]

Zookeys
Kaminsky L, Huber S, Deuel T, Tran NV, Howard EJ, Leopold A, Priyadarshini A, Plotkin D, Kawahara AY.   +8 more
europepmc   +1 more source

Evaluating the performance of ancient DNA genetic relatedness estimation methods using high-fidelity pedigree simulations. [PDF]

Genome Biol
Lefeuvre M, Marsolier MC, Bon C.
europepmc   +1 more source

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Preserving File Provenance Using Principles of Blockchain to Ensure Scientific Reproducibility

2023 IEEE 19th International Conference on e-Science (e-Science), 2023
Shweta Purawat
exaly   +2 more sources

Die IAB-Beschäftigtenstrichprobe als scientific use file [PDF]

Mitteilungen aus der Arbeitsmarkt- und Berufsforschung, 1995
"Die seit 1973 aufgebaute Beschäftigtenstatistik ist neben der Volks- und Berufszählung, dem Mikrozensus und der Einkommens- und Verbrauchsstichprobe (EVS) eine der für die Sozialforschung wichtigsten Datenquellen der deutschen Sozialstatistik. Angesichts der Bedeutung, die die Beschäftigtenstatistik als Datenquelle für die Arbeitsmarktforschung hat ...
Bender, Stefan, Hilzendegen, Jürgen
openaire  

Using XQuery for Flat-File Based Scientific Datasets

2004
XQuery is a recently developed query language for XML datasets. In this paper, we focus on the use of XQuery and other XML technologies for flat-file based scientific datasets. Traditionally, complex and domain-specific data layouts have complicated the processing of large datasets arising from scientific applications. The use of XML schemas and XQuery’
Xiaogang Li 0001, Gagan Agrawal
openaire   +1 more source

POSTER: Optimizing scientific file I/O patterns using advice based knowledge

2014 IEEE International Conference on Cluster Computing (CLUSTER), 2014
Before us, other works have used data prefetching to boost applications performance [1]–[8]. Our approach differs from these works since we do not rely on precise I/O pattern information to predict and prefetch every chunck of data in advance. Instead we use data prefetching to group many small requests in a few big ones, improving applications ...
Giuseppe Congiu, Matthias Grawinkel, Federico Padua, James Morse, Tim Süß, André Brinkmann   +5 more
openaire   +1 more source