Literature DB >> 19339382

Taming the complexity of biological pathways through parallel computing.

Paolo Ballarini1, Rosita Guido, Tommaso Mazza, Davide Prandi.   

Abstract

Biological systems are characterised by a large number of interacting entities whose dynamics is described by a number of reaction equations. Mathematical methods for modelling biological systems are mostly based on a centralised solution approach: the modelled system is described as a whole and the solution technique, normally the integration of a system of ordinary differential equations (ODEs) or the simulation of a stochastic model, is commonly computed in a centralised fashion. In recent times, research efforts moved towards the definition of parallel/distributed algorithms as a means to tackle the complexity of biological models analysis. In this article, we present a survey on the progresses of such parallelisation efforts describing the most promising results so far obtained.

Mesh:

Year:  2009        PMID: 19339382     DOI: 10.1093/bib/bbp020

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  5 in total

1.  Multi-dimensional, mesoscopic Monte Carlo simulations of inhomogeneous reaction-drift-diffusion systems on graphics-processing units.

Authors:  Matthias Vigelius; Bernd Meyer
Journal:  PLoS One       Date:  2012-04-10       Impact factor: 3.240

2.  Fasting cycles potentiate the efficacy of gemcitabine treatment in in vitro and in vivo pancreatic cancer models.

Authors:  Martina D'Aronzo; Manlio Vinciguerra; Tommaso Mazza; Concetta Panebianco; Chiara Saracino; Stephen P Pereira; Paolo Graziano; Valerio Pazienza
Journal:  Oncotarget       Date:  2015-07-30

3.  Parameter estimation in large-scale systems biology models: a parallel and self-adaptive cooperative strategy.

Authors:  David R Penas; Patricia González; Jose A Egea; Ramón Doallo; Julio R Banga
Journal:  BMC Bioinformatics       Date:  2017-01-21       Impact factor: 3.169

4.  Snazer: the simulations and networks analyzer.

Authors:  Tommaso Mazza; Gennaro Iaccarino; Corrado Priami
Journal:  BMC Syst Biol       Date:  2010-01-07

5.  Parameter estimation of qualitative biological regulatory networks on high performance computing hardware.

Authors:  Muhammad Tariq Saeed; Jamil Ahmad; Jan Baumbach; Josch Pauling; Aamir Shafi; Rehan Zafar Paracha; Asad Hayat; Amjad Ali
Journal:  BMC Syst Biol       Date:  2018-12-29
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.