Evidence map›Paper›PMID 26558254›Full record

ArticleInternational journal of genomics2015

Evaluating the Cassandra NoSQL Database Approach for Genomic Data Persistency.

Rodrigo Aniceto, Rene Xavier, Valeria Guimarães, Fernanda Hondo, Maristela Holanda, Maria Emilia Walter, Sérgio Lifschitz

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Article in International journal of genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Rodrigo AnicetoComputer Science Department, University of Brasilia (UNB), 70910-900 Brasilia, DF, Brazil.
Rene XavierComputer Science Department, University of Brasilia (UNB), 70910-900 Brasilia, DF, Brazil.
Valeria GuimarãesComputer Science Department, University of Brasilia (UNB), 70910-900 Brasilia, DF, Brazil.
Fernanda HondoComputer Science Department, University of Brasilia (UNB), 70910-900 Brasilia, DF, Brazil.
Maristela HolandaComputer Science Department, University of Brasilia (UNB), 70910-900 Brasilia, DF, Brazil.
Maria Emilia WalterComputer Science Department, University of Brasilia (UNB), 70910-900 Brasilia, DF, Brazil.
Sérgio LifschitzInformatics Department, Pontifical Catholic University of Rio de Janeiro (PUC-Rio), 22451-900 Rio de Janeiro, RJ, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Identifiers

PMID26558254
PMCPMC4629038

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.