Literature DB >> 18535084

Optimal vaccination schedules using simulated annealing.

Marzio Pennisi1, Roberto Catanuto, Francesco Pappalardo, Santo Motta.   

Abstract

SUMMARY: Since few years the problem of finding optimal solutions for drug or vaccine protocols have been tackled using system biology modeling. These approaches are usually computationally expensive. Our previous experiences in optimizing vaccine or drug protocols using genetic algorithms required the use of a high performance computing infrastructure for a couple of days. In the present article we show that by an appropriate use of a different optimization algorithm, the simulated annealing, we have been able to downsize the computational effort by a factor 10(2). The new algorithm requires computational effort that can be achieved by current generation personal computers. AVAILABILITY: Software and additional data can be found at http://www.immunomics.eu/SA/

Mesh:

Substances:

Year:  2008        PMID: 18535084     DOI: 10.1093/bioinformatics/btn260

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  8 in total

1.  Relaxation estimation of RMSD in molecular dynamics immunosimulations.

Authors:  Wolfgang Schreiner; Rudolf Karch; Bernhard Knapp; Nevena Ilieva
Journal:  Comput Math Methods Med       Date:  2012-09-16       Impact factor: 2.238

2.  Optimal vaccination schedule search using genetic algorithm over MPI technology.

Authors:  Cristiano Calonaci; Ferdinando Chiacchio; Francesco Pappalardo
Journal:  BMC Med Inform Decis Mak       Date:  2012-11-13       Impact factor: 2.796

3.  SimB16: modeling induced immune system response against B16-melanoma.

Authors:  Francesco Pappalardo; Ivan Martinez Forero; Marzio Pennisi; Asis Palazon; Ignacio Melero; Santo Motta
Journal:  PLoS One       Date:  2011-10-19       Impact factor: 3.240

4.  Agent based modeling of Treg-Teff cross regulation in relapsing-remitting multiple sclerosis.

Authors:  Marzio Pennisi; Abdul-Mateen Rajput; Luca Toldo; Francesco Pappalardo
Journal:  BMC Bioinformatics       Date:  2013-10-22       Impact factor: 3.169

5.  Optimal control of the SIR model with constrained policy, with an application to COVID-19.

Authors:  Yujia Ding; Henry Schellhorn
Journal:  Math Biosci       Date:  2021-12-16       Impact factor: 2.144

Review 6.  Cancer vaccines: state of the art of the computational modeling approaches.

Authors:  Francesco Pappalardo; Ferdinando Chiacchio; Santo Motta
Journal:  Biomed Res Int       Date:  2012-12-23       Impact factor: 3.411

7.  Mathematical modeling of the immune system recognition to mammary carcinoma antigen.

Authors:  Carlo Bianca; Ferdinando Chiacchio; Francesco Pappalardo; Marzio Pennisi
Journal:  BMC Bioinformatics       Date:  2012-12-13       Impact factor: 3.169

8.  Dealing with uncertainty in agent-based models for short-term predictions.

Authors:  Le-Minh Kieu; Nicolas Malleson; Alison Heppenstall
Journal:  R Soc Open Sci       Date:  2020-01-15       Impact factor: 2.963

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.