A Database System for High-Throughput Transposon Display Analyses of Rice

2006 ◽  
Vol 16 (1) ◽  
pp. 28-38
Author(s):  
Etsuko INOUE ◽  
Takuya YOSHIHIRO ◽  
Hideya KAWAJI ◽  
Akira HORIBATA ◽  
Masaru NAKAGAWA
Keyword(s):  
High Throughput ◽  
Database System ◽  
Transposon Display

scholarly journals Next-Generation Sequencing Based Transposon Display to Detect High-Throughput Insertion Polymorphism Markers in Brassica

2016 ◽  
Vol 4 (3) ◽  
pp. 285-296 ◽  
Author(s):  
Sampath Perumal ◽  
Nomar Espinosa Waminal ◽  
Jonghoon Lee ◽  
Nur Kholilatul Izzah ◽  
Mina Jin ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
High Throughput ◽  
Insertion Polymorphism ◽  
Next Generation ◽  
Transposon Display ◽  
Generation Sequencing

scholarly journals GENIUS II: a high-throughput database system for linking ORFs in complete genomes to known protein three-dimensional structures

2004 ◽  
Vol 20 (4) ◽  
pp. 596-598 ◽  
Author(s):  
Y. Yabuki ◽  
Y. Mukai ◽  
M. B. Swindells ◽  
M. Suwa
Keyword(s):  
High Throughput ◽  
Three Dimensional ◽  
Database System ◽  
Complete Genomes

A high-throughput distributed DNA sequence analysis and database system

2001 ◽  
Vol 40 (2) ◽  
pp. 464-486 ◽  
Author(s):  
J. T. Inman ◽  
H. R. Flores ◽  
G. D. May ◽  
J. W. Weller ◽  
C. J. Bell
Keyword(s):  
Sequence Analysis ◽  
Dna Sequence ◽  
High Throughput ◽  
Database System ◽  
Dna Sequence Analysis

scholarly journals An application of a relational database system for high-throughput prediction of elemental compositions from accurate mass values

2012 ◽  
Vol 29 (2) ◽  
pp. 290-291 ◽  
Author(s):  
Nozomu Sakurai ◽  
Takeshi Ara ◽  
Shigehiko Kanaya ◽  
Yukiko Nakamura ◽  
Yoko Iijima ◽  
...  
Keyword(s):  
High Throughput ◽  
Relational Database ◽  
Database System ◽  
Accurate Mass ◽  
Elemental Compositions ◽  
Relational Database System

Sharing opportunities for OLTP workloads in different isolation levels

2020 ◽  
Vol 13 (10) ◽  
pp. 1696-1708
Author(s):  
Robin Rehrmann ◽  
Carsten Binnig ◽  
Alexander Böhm ◽  
Kihong Kim ◽  
Wolfgang Lehner
Keyword(s):  
High Throughput ◽  
Experimental Evaluation ◽  
Database System ◽  
Formal Framework ◽  
Query Patterns

OLTP applications are usually executed by a high number of clients in parallel and are typically faced with high throughput demand as well as a constraint latency requirement for individual statements. Interestingly, OLTP workloads are often read-heavy and comprise similar query patterns, which provides a potential to share work of statements belonging to different transactions. Consequently, OLAP techniques for sharing work have started to be applied also to OLTP workloads, lately. In this paper, we present an approach for merging read statements within interactively submitted multi-statement transactions consisting of reads and writes. We first define a formal framework for merging transactions running under a given isolation level and provide insights into a prototypical implementation of merging within a commercial database system. In our experimental evaluation, we show that, depending on the isolation level, the load in the system and the read-share of the workload, an improvement of the transaction throughput by up to a factor of 2.5X is possible without compromising the transactional semantics.

scholarly journals Evaluating the Cassandra NoSQL Database Approach for Genomic Data Persistency

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Rodrigo Aniceto ◽  
Rene Xavier ◽  
Valeria Guimarães ◽  
Fernanda Hondo ◽  
Maristela Holanda ◽  
...  
Keyword(s):  
High Throughput ◽  
Relational Database ◽  
Large Scale ◽  
High Throughput Sequencing ◽  
Genomic Data ◽  
Real Data ◽  
Database System ◽  
Data Models ◽  
Relational Database System ◽  
Nosql Database

Rapid advances in high-throughput sequencing techniques have created interesting computational challenges in bioinformatics. One of them refers to management of massive amounts of data generated by automatic sequencers. We need to deal with the persistency of genomic data, particularly storing and analyzing these large-scale processed data. To find an alternative to the frequently considered relational database model becomes a compelling task. Other data models may be more effective when dealing with a very large amount of nonconventional data, especially for writing and retrieving operations. In this paper, we discuss the Cassandra NoSQL database approach for storing genomic data. We perform an analysis of persistency and I/O operations with real data, using the Cassandra database system. We also compare the results obtained with a classical relational database system and another NoSQL database approach, MongoDB.

154: Integration of TPSA and High-Throughput Mass Spectrometry Data Improves Prostate Cancer Prediction

2007 ◽  
Vol 177 (4S) ◽  
pp. 52-53
Author(s):  
Stefano Ongarello ◽  
Eberhard Steiner ◽  
Regina Achleitner ◽  
Isabel Feuerstein ◽  
Birgit Stenzel ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Mass Spectrometry ◽  
High Throughput ◽  
Mass Spectrometry Data ◽  
Cancer Prediction
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