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Study Type: simulation/modelling Subject: Mathematics

1 to 10 of 11 Results

Data and codes from "Estimating the optimal age for infant measles vaccination" Oct 8, 2024 Goult, Elizabeth; Barrero Guevara, Laura Andrea; Briga, Michael; Domenech de Cellès, Matthieu, 2024, "Data and codes from "Estimating the optimal age for infant measles vaccination"", https://doi.org/10.17617/3.50X626, Edmond, V1 Data and R codes associated with the manuscript "Estimating the optimal age for infant measles vaccination".
High-resolution global ultrafine particle concentrations through a machine learning model and Earth observations Jul 24, 2024 Georgiades, Pantelis; Pozzer, Andrea, 2024, "High-resolution global ultrafine particle concentrations through a machine learning model and Earth observations", https://doi.org/10.17617/3.YK9I4B, Edmond, V1 Atmospheric pollution is a major concern due to its well-documented and detrimental impacts on human health, with millions of excess deaths attributed to it annually. Particulate matter (PM), comprising airborne pollutants in the form of solid and liquid particles suspended in th...
Code for "Characterizing the interactions between influenza and respiratory syncytial viruses and their implications for disease control" Jul 16, 2024 Kramer, Sarah C, 2022, "Code for "Characterizing the interactions between influenza and respiratory syncytial viruses and their implications for disease control"", https://doi.org/10.17617/3.TBOPCK, Edmond, V3 Code to infer the strength and duration of interactions between flu and RSV
Data and R codes from "Pertussis vaccines, epidemiology and evolution" May 15, 2024 Domenech de Celles, Matthieu; Rohani, Pejman, 2024, "Data and R codes from "Pertussis vaccines, epidemiology and evolution"", https://doi.org/10.17617/3.A1KMUB, Edmond, V1 Data and R codes from the review article, "Pertussis vaccines, epidemiology and evolution", published in Nature Reviews Microbiology.
A data-driven estimation of the ribosome drop-off rate in S. cerevisiae reveals a correlation with the genes length. Mar 26, 2024 Awad, Sherine; Valleriani, Angelo; Chiarugi, Davide, 2024, "A data-driven estimation of the ribosome drop-off rate in S. cerevisiae reveals a correlation with the genes length.", https://doi.org/10.17617/3.H7OPIB, Edmond, V1 Ribofilio is a software package that estimates the drop-off rate of ribosomes. It is a python package that takes as a required input the reference genome and the footprint. If the mRNA reads are available, this can be used as an optional parameter for normalization. The tool uses...
Data and codes from "Delineating the seasonality of varicella and its association with climate in the tropical country of Colombia" Aug 28, 2023 Barrero Guevara, Laura Andrea; Goult, Elizabeth; Dayanne Rodriguez; Luis Jorge Hernandez; Kaufer, Benedikt B.; Kurth, Tobias; Domenech de Cellès, Matthieu, 2023, "Data and codes from "Delineating the seasonality of varicella and its association with climate in the tropical country of Colombia"", https://doi.org/10.17617/3.ZCMEKJ, Edmond, V1 Data and R codes associated with the manuscript "Delineating the seasonality of varicella and its association with climate in the tropical country of Colombia"
Supplementary material for "Efficient global sensitivity analysis of kinetic Monte Carlo simulations using Cramérs von Mises distance" Aug 24, 2023 Matera, Sebastian, 2023, "Supplementary material for "Efficient global sensitivity analysis of kinetic Monte Carlo simulations using Cramérs von Mises distance"", https://doi.org/10.17617/3.EPRBFA, Edmond, V1 A complementary simple toy problem and sample code and datasets of 1p-kMC simulation results used for the manuscript. For details see the README.me file
Real and Synthetic data for Hypergraph Benchmarking (processed for the Hy-MMSBM generative model) Jan 11, 2023 Ruggeri, Nicolo, 2023, "Real and Synthetic data for Hypergraph Benchmarking (processed for the Hy-MMSBM generative model)", https://doi.org/10.17617/3.HRW0OE, Edmond, V2 This dataset contains the preprocessed real hypergraph data utilized in the experiments for "Generalized inference of mesoscale structures in higher-order networks", Ruggeri N., Contisciani M., Battiston F., De Bacco C. and synthetic hypergraph data generated for experiments in t...
Data and R codes from "Immunological heterogeneity informs estimation of the durability of vaccine protection" Apr 25, 2022 Domenech de Cellès, Matthieu; Wong, Anabelle; Barrero Guevara, Laura Andrea; Rohani, Pejman, 2022, "Data and R codes from "Immunological heterogeneity informs estimation of the durability of vaccine protection"", https://doi.org/10.17617/3.AWRHE8, Edmond, V1 Data and R codes from the research article "Immunological heterogeneity informs estimation of the durability of vaccine protection", published in the Journal of the Royal Society Interface.
Codes from: "The pitfalls of inferring virus-virus interactions from co-detection prevalence data: Application to influenza and SARS-CoV-2" Dec 6, 2021 Domenech de Cellès, Matthieu; Goult, Elizabeth; Casalegno, Jean-Sébastien; Kramer, Sarah C., 2021, "Codes from: "The pitfalls of inferring virus-virus interactions from co-detection prevalence data: Application to influenza and SARS-CoV-2"", https://doi.org/10.17617/3.8k, Edmond, V1 R codes to reproduce the results presented in the paper "The pitfalls of inferring virus-virus interactions from co-detection prevalence data: Application to influenza and SARS-CoV-2"

Data and codes from "Estimating the optimal age for infant measles vaccination"

Oct 8, 2024

Goult, Elizabeth; Barrero Guevara, Laura Andrea; Briga, Michael; Domenech de Cellès, Matthieu, 2024, "Data and codes from "Estimating the optimal age for infant measles vaccination"", https://doi.org/10.17617/3.50X626, Edmond, V1

Data and R codes associated with the manuscript "Estimating the optimal age for infant measles vaccination".

High-resolution global ultrafine particle concentrations through a machine learning model and Earth observations

Jul 24, 2024

Georgiades, Pantelis; Pozzer, Andrea, 2024, "High-resolution global ultrafine particle concentrations through a machine learning model and Earth observations", https://doi.org/10.17617/3.YK9I4B, Edmond, V1

Atmospheric pollution is a major concern due to its well-documented and detrimental impacts on human health, with millions of excess deaths attributed to it annually. Particulate matter (PM), comprising airborne pollutants in the form of solid and liquid particles suspended in th...

Code for "Characterizing the interactions between influenza and respiratory syncytial viruses and their implications for disease control"

Jul 16, 2024

Kramer, Sarah C, 2022, "Code for "Characterizing the interactions between influenza and respiratory syncytial viruses and their implications for disease control"", https://doi.org/10.17617/3.TBOPCK, Edmond, V3

Code to infer the strength and duration of interactions between flu and RSV

Data and R codes from "Pertussis vaccines, epidemiology and evolution"

May 15, 2024

Domenech de Celles, Matthieu; Rohani, Pejman, 2024, "Data and R codes from "Pertussis vaccines, epidemiology and evolution"", https://doi.org/10.17617/3.A1KMUB, Edmond, V1

Data and R codes from the review article, "Pertussis vaccines, epidemiology and evolution", published in Nature Reviews Microbiology.

A data-driven estimation of the ribosome drop-off rate in S. cerevisiae reveals a correlation with the genes length.

Mar 26, 2024

Awad, Sherine; Valleriani, Angelo; Chiarugi, Davide, 2024, "A data-driven estimation of the ribosome drop-off rate in S. cerevisiae reveals a correlation with the genes length.", https://doi.org/10.17617/3.H7OPIB, Edmond, V1

Ribofilio is a software package that estimates the drop-off rate of ribosomes. It is a python package that takes as a required input the reference genome and the footprint. If the mRNA reads are available, this can be used as an optional parameter for normalization. The tool uses...

Data and codes from "Delineating the seasonality of varicella and its association with climate in the tropical country of Colombia"

Aug 28, 2023

Barrero Guevara, Laura Andrea; Goult, Elizabeth; Dayanne Rodriguez; Luis Jorge Hernandez; Kaufer, Benedikt B.; Kurth, Tobias; Domenech de Cellès, Matthieu, 2023, "Data and codes from "Delineating the seasonality of varicella and its association with climate in the tropical country of Colombia"", https://doi.org/10.17617/3.ZCMEKJ, Edmond, V1

Data and R codes associated with the manuscript "Delineating the seasonality of varicella and its association with climate in the tropical country of Colombia"

Supplementary material for "Efficient global sensitivity analysis of kinetic Monte Carlo simulations using Cramérs von Mises distance"

Aug 24, 2023

Matera, Sebastian, 2023, "Supplementary material for "Efficient global sensitivity analysis of kinetic Monte Carlo simulations using Cramérs von Mises distance"", https://doi.org/10.17617/3.EPRBFA, Edmond, V1

A complementary simple toy problem and sample code and datasets of 1p-kMC simulation results used for the manuscript. For details see the README.me file

Real and Synthetic data for Hypergraph Benchmarking (processed for the Hy-MMSBM generative model)

Jan 11, 2023

Ruggeri, Nicolo, 2023, "Real and Synthetic data for Hypergraph Benchmarking (processed for the Hy-MMSBM generative model)", https://doi.org/10.17617/3.HRW0OE, Edmond, V2

This dataset contains the preprocessed real hypergraph data utilized in the experiments for "Generalized inference of mesoscale structures in higher-order networks", Ruggeri N., Contisciani M., Battiston F., De Bacco C. and synthetic hypergraph data generated for experiments in t...

Data and R codes from "Immunological heterogeneity informs estimation of the durability of vaccine protection"

Apr 25, 2022

Domenech de Cellès, Matthieu; Wong, Anabelle; Barrero Guevara, Laura Andrea; Rohani, Pejman, 2022, "Data and R codes from "Immunological heterogeneity informs estimation of the durability of vaccine protection"", https://doi.org/10.17617/3.AWRHE8, Edmond, V1

Data and R codes from the research article "Immunological heterogeneity informs estimation of the durability of vaccine protection", published in the Journal of the Royal Society Interface.

Codes from: "The pitfalls of inferring virus-virus interactions from co-detection prevalence data: Application to influenza and SARS-CoV-2"

Dec 6, 2021

Domenech de Cellès, Matthieu; Goult, Elizabeth; Casalegno, Jean-Sébastien; Kramer, Sarah C., 2021, "Codes from: "The pitfalls of inferring virus-virus interactions from co-detection prevalence data: Application to influenza and SARS-CoV-2"", https://doi.org/10.17617/3.8k, Edmond, V1

R codes to reproduce the results presented in the paper "The pitfalls of inferring virus-virus interactions from co-detection prevalence data: Application to influenza and SARS-CoV-2"

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