Evidence map›Paper›PMID 25050327›Full record

ArticleBioMed research international2014

On designing multicore-aware simulators for systems biology endowed with OnLine statistics.

Marco Aldinucci, Cristina Calcagno, Mario Coppo, Ferruccio Damiani, Maurizio Drocco, Eva Sciacca, Salvatore Spinella, Massimo Torquati, Angelo Troina

Abstract read
In one paragraph

Article in BioMed research international, 2014. 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

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

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

9 authors.

Marco AldinucciDepartment of Computer Science, University of Torino, 10149 Torino, Italy.ORCID 0000-0001-8788-0829
Cristina CalcagnoDepartment of Computer Science, University of Torino, 10149 Torino, Italy ; Department of Life Sciences and Systems Biology, University of Torino, 10123 Torino, Italy.
Mario CoppoDepartment of Computer Science, University of Torino, 10149 Torino, Italy.
Ferruccio DamianiDepartment of Computer Science, University of Torino, 10149 Torino, Italy.ORCID 0000-0001-8109-1706
Maurizio DroccoDepartment of Computer Science, University of Torino, 10149 Torino, Italy.ORCID 0000-0001-6500-7607
Eva SciaccaDepartment of Computer Science, University of Torino, 10149 Torino, Italy.ORCID 0000-0002-5574-2787
Salvatore SpinellaDepartment of Computer Science, University of Torino, 10149 Torino, Italy.ORCID 0000-0002-1541-0083
Massimo TorquatiDepartment of Computer Science, University of Pisa, 56127 Pisa, Italy.ORCID 0000-0001-6323-3459
Angelo TroinaDepartment of Computer Science, University of Torino, 10149 Torino, Italy.ORCID 0000-0002-0049-4237

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The paper arguments are on enabling methodologies for the design of a fully parallel, online, interactive tool aiming to support the bioinformatics scientists .In particular, the features of these methodologies, supported by the FastFlow parallel programming framework, are shown on a simulation tool to perform the modeling, the tuning, and the sensitivity analysis of stochastic biological models. A stochastic simulation needs thousands of independent simulation trajectories turning into big data that should be analysed by statistic and data mining tools. In the considered approach the two stages are pipelined in such a way that the simulation stage streams out the partial results of all simulation trajectories to the analysis stage that immediately produces a partial result. The simulation-analysis workflow is validated for performance and effectiveness of the online analysis in capturing biological systems behavior on a multicore platform and representative proof-of-concept biological systems. The exploited methodologies include pattern-based parallel programming and data streaming that provide key features to the software designers such as performance portability and efficient in-memory (big) data management and movement. Two paradigmatic classes of biological systems exhibiting multistable and oscillatory behavior are used as a testbed.

Indexed as

Computer SimulationSoftware DesignStatistics as TopicBacteriophage lambdaCytosolFungal ProteinsModels, BiologicalNeurosporaOnline SystemsSystems BiologyUser-Computer InterfaceFungal Proteins

Identifiers

PMID25050327
PMCPMC4090576

What OpenQuestion holds

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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.