Evidence map›Paper›PMID 32294194›Full record

ArticleDatabase : the journal of biological databases and curation2020

Integrated querying and version control of context-specific biological networks.

Tyler Cowman, Mustafa Coşkun, Ananth Grama, Mehmet Koyutürk

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Tyler CowmanDepartment of Computer and Data Sciences, Case Western Reserve University, Cleveland, OH 44106, USA.
Mustafa CoşkunDepartment of Computer Engineering, Abdullah Gül University, Kayseri 38080, Turkey.
Ananth GramaDepartment of Computer Science, Purdue University, West Lafayette, IN 47906, USA.
Mehmet KoyutürkDepartment of Computer and Data Sciences, Case Western Reserve University, Cleveland, OH 44106, USA.

Funding

Construction, Analysis, and Utilization of Co-Phosphorylation Networks to Characterize Cellular SignalingR01LM012980 · NLM · CASE WESTERN RESERVE UNIVERSITY · PI Marzieh Ayati, MARK R CHANCE · 2019 to 2026
$2.1M
Theoretical Foundations and Software Infrastructure for Biological Network DatabasesU01CA198941 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI KOYUTURK, MEHMET · 2015 to 2017
$1.4M
NCI NIH HHS U01 CA198941NLM NIH HHS R01 LM012980
6 · The paper itself

Abstract

motivationBiomolecular data stored in public databases is increasingly specialized to organisms, context/pathology and tissue type, potentially resulting in significant overhead for analyses. These networks are often specializations of generic interaction sets, presenting opportunities for reducing storage and computational cost. Therefore, it is desirable to develop effective compression and storage techniques, along with efficient algorithms and a flexible query interface capable of operating on compressed data structures. Current graph databases offer varying levels of support for network integration. However, these solutions do not provide efficient methods for the storage and querying of versioned networks.

resultsWe present VerTIoN, a framework consisting of novel data structures and associated query mechanisms for integrated querying of versioned context-specific biological networks. As a use case for our framework, we study network proximity queries in which the user can select and compose a combination of tissue-specific and generic networks. Using our compressed version tree data structure, in conjunction with state-of-the-art numerical techniques, we demonstrate real-time querying of large network databases.

conclusionOur results show that it is possible to support flexible queries defined on heterogeneous networks composed at query time while drastically reducing response time for multiple simultaneous queries. The flexibility offered by VerTIoN in composing integrated network versions opens significant new avenues for the utilization of ever increasing volume of context-specific network data in a broad range of biomedical applications. AVAILABILITY AND IMPLEMENTATION: VerTIoN is implemented as a C++ library and is available at http://compbio.case.edu/omics/software/vertion and https://github.com/tjcowman/vertion. CONTACT: tyler.cowman@case.edu.

Indexed as

Databases, FactualGene Regulatory NetworksProtein Interaction MapsAlgorithmsComputational BiologyData CurationData MiningHumansInternetUser-Computer Interface

Identifiers

PMID32294194
PMCPMC7158887

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.