Evidence map›Paper›PMID 24106693›Full record

ArticleBioMed research international2013

Cloud infrastructures for in silico drug discovery: economic and practical aspects.

Daniele D'Agostino, Andrea Clematis, Alfonso Quarati, Daniele Cesini, Federica Chiappori, Luciano Milanesi, Ivan Merelli

Abstract read
In one paragraph

Article in BioMed research international, 2013. 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
  2. Molecular Docking: Shifting Paradigms in Drug Discovery.International journal of molecular sciences · 2019
    Review
  3. Review
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.

Daniele D'AgostinoInstitute of Applied Mathematics and Information Technologies, National Research Council of Italy, via de Marini 6, 16149 Genoa, Italy.
Andrea Clematis
Alfonso Quarati
Daniele Cesini
Federica Chiappori
Luciano Milanesi
Ivan Merelli

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cloud computing opens new perspectives for small-medium biotechnology laboratories that need to perform bioinformatics analysis in a flexible and effective way. This seems particularly true for hybrid clouds that couple the scalability offered by general-purpose public clouds with the greater control and ad hoc customizations supplied by the private ones. A hybrid cloud broker, acting as an intermediary between users and public providers, can support customers in the selection of the most suitable offers, optionally adding the provisioning of dedicated services with higher levels of quality. This paper analyses some economic and practical aspects of exploiting cloud computing in a real research scenario for the in silico drug discovery in terms of requirements, costs, and computational load based on the number of expected users. In particular, our work is aimed at supporting both the researchers and the cloud broker delivering an IaaS cloud infrastructure for biotechnology laboratories exposing different levels of nonfunctional requirements.

Indexed as

Computer SimulationComputing MethodologiesDrug DiscoveryBiotechnologyHumans

Identifiers

PMID24106693
PMCPMC3782806

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.