Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

HIVE

General information

URL: https://hive.biochemistry.gwu.edu/
Full name: High-performance integrated virtual environment
Description: a cloud-based environment optimized for the storage and analysis of extra-large data, such as biomedical data, clinical data, next-generation sequencing (NGS) data, mass spectrometry files, confocal microscopy images, post-market surveillance data, medical recall data, and many others.
Year founded: 2014
Last update: 2016-03-17
Version:
Accessibility:
Accessible
Country/Region: United States

Classification & Tag

Data type:
Data object:
Database category:
Major species:
Keywords:

Contact information

University/Institution: US Food and Drug Administration
Address: Center for Biologics Evaluation and Research
City: Silver Spring
Province/State: Maryland
Country/Region: United States
Contact name (PI/Team): Vahan Simonyan
Contact email (PI/Helpdesk): vahansim@gmail.com

Publications

26989153
High-performance integrated virtual environment (HIVE): a robust infrastructure for next-generation sequence data analysis. [PMID: 26989153]
Simonyan V, Chumakov K, Dingerdissen H, Faison W, Goldweber S, Golikov A, Gulzar N, Karagiannis K, Vinh Nguyen Lam P, Maudru T, Muravitskaja O, Osipova E, Pan Y, Pschenichnov A, Rostovtsev A, Santana-Quintero L, Smith K, Thompson EE, Tkachenko V, Torcivia-Rodriguez J, Voskanian A, Wan Q, Wang J, Wu TJ, Wilson C, Mazumder R.

The High-performance Integrated Virtual Environment (HIVE) is a distributed storage and compute environment designed primarily to handle next-generation sequencing (NGS) data. This multicomponent cloud infrastructure provides secure web access for authorized users to deposit, retrieve, annotate and compute on NGS data, and to analyse the outcomes using web interface visual environments appropriately built in collaboration with research and regulatory scientists and other end users. Unlike many massively parallel computing environments, HIVE uses a cloud control server which virtualizes services, not processes. It is both very robust and flexible due to the abstraction layer introduced between computational requests and operating system processes. The novel paradigm of moving computations to the data, instead of moving data to computational nodes, has proven to be significantly less taxing for both hardware and network infrastructure.The honeycomb data model developed for HIVE integrates metadata into an object-oriented model. Its distinction from other object-oriented databases is in the additional implementation of a unified application program interface to search, view and manipulate data of all types. This model simplifies the introduction of new data types, thereby minimizing the need for database restructuring and streamlining the development of new integrated information systems. The honeycomb model employs a highly secure hierarchical access control and permission system, allowing determination of data access privileges in a finely granular manner without flooding the security subsystem with a multiplicity of rules. HIVE infrastructure will allow engineers and scientists to perform NGS analysis in a manner that is both efficient and secure. HIVE is actively supported in public and private domains, and project collaborations are welcomed. Database URL: https://hive.biochemistry.gwu.edu. © The Author(s) 2016. Published by Oxford University Press.

Database (Oxford). 2016:2016() | 49 Citations (from Europe PMC, 2025-12-13)
25271953
High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis. [PMID: 25271953]
Simonyan V, Mazumder R.

The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data. HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion. The platform contains a distributed storage library and a distributed computational powerhouse linked seamlessly. Resources available through the interface include algorithms, tools and applications developed exclusively for the HIVE platform, as well as commonly used external tools adapted to operate within the parallel architecture of the system. HIVE is composed of a flexible infrastructure, which allows for simple implementation of new algorithms and tools. Currently, available HIVE tools include sequence alignment and nucleotide variation profiling tools, metagenomic analyzers, phylogenetic tree-building tools using NGS data, clone discovery algorithms, and recombination analysis algorithms. In addition to tools, HIVE also provides knowledgebases that can be used in conjunction with the tools for NGS sequence and metadata analysis.

Genes (Basel). 2014:5(4) | 42 Citations (from Europe PMC, 2025-12-13)

Ranking

All databases:
1710/6895 (75.214%)
Metadata:
163/719 (77.469%)
Gene genome and annotation:
548/2021 (72.934%)
Expression:
347/1347 (74.313%)
Health and medicine:
425/1738 (75.604%)
1710
Total Rank
87
Citations
7.909
z-index

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Record metadata

Created on: 2017-03-24
Curated by:
huma shireen [2018-08-27]
Lina Ma [2017-06-02]
Shixiang Sun [2017-03-24]