Evidence map›Paper›PMID 36368948›Full record

ArticleBMC bioinformatics2022

DIAMIN: a software library for the distributed analysis of large-scale molecular interaction networks.

Lorenzo Di Rocco, Umberto Ferraro Petrillo, Simona E Rombo

Abstract read
In one paragraph

Article in BMC bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Lorenzo Di RoccoDepartment of Statistics, University of Rome La Sapienza, Rome, Italy.
Umberto Ferraro PetrilloDepartment of Statistics, University of Rome La Sapienza, Rome, Italy. umberto.ferraro@uniroma1.it.
Simona E RomboDepartment of Mathematics and Computer Science, University of Palermo, Palermo, Italy. simona.rombo@unipa.it.ORCID http://orcid.org/0000-0003-3833-835X

Funding

GNCS 2022 E55F 22000270001)PRIN MIUR 2017WR7SHH
6 · The paper itself

Abstract

backgroundHuge amounts of molecular interaction data are continuously produced and stored in public databases. Although many bioinformatics tools have been proposed in the literature for their analysis, based on their modeling through different types of biological networks, several problems still remain unsolved when the problem turns on a large scale.

resultsWe propose DIAMIN, that is, a high-level software library to facilitate the development of applications for the efficient analysis of large-scale molecular interaction networks. DIAMIN relies on distributed computing, and it is implemented in Java upon the framework Apache Spark. It delivers a set of functionalities implementing different tasks on an abstract representation of very large graphs, providing a built-in support for methods and algorithms commonly used to analyze these networks. DIAMIN has been tested on data retrieved from two of the most used molecular interactions databases, resulting to be highly efficient and scalable. As shown by different provided examples, DIAMIN can be exploited by users without any distributed programming experience, in order to perform various types of data analysis, and to implement new algorithms based on its primitives.

conclusionsThe proposed DIAMIN has been proved to be successful in allowing users to solve specific biological problems that can be modeled relying on biological networks, by using its functionalities. The software is freely available and this will hopefully allow its rapid diffusion through the scientific community, to solve both specific data analysis and more complex tasks.

Indexed as

Computational BiologySoftwareAlgorithmsDatabases, FactualGene LibraryBig data analyticsBiological networksLarge scale networksMolecular interactions

Identifiers

PMID36368948
PMCPMC9652854

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LicenceCC BY
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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.