BioSystems Modelling Group

@misc{medica,

title = {MEDICA: Modelling and vErification of alkaptonuria and multiple sclerosis Driven by biomedICAl data},

url = {https://biomedinfo.di.unipi.it/medica-project/},

year  = {2023},

date = {2023-09-29},

urldate = {2023-09-29},

abstract = {Abstract: The goal of this project is to bridge the gap between data, models and validation, integrating the data-driven and model-driven research directions, so that to develop next generation modelling and analysis approaches for biomedical investigations.  We are tackling open research questions for Multiple Sclerosis (MS) and Alkaptonuria (AKU), for which we have world-leading experts in our consortium.},

howpublished = {PRIN 2022 Project},

keywords = {},

pubstate = {published},

tppubtype = {misc}

}

@misc{PreMed2,

title = {PreMed2},

year  = {2020},

date = {2020-12-29},

abstract = {The main purpose of this project is to identify the population of subjects at risk of developing type 2 diabetes based on eating habits (using validated questionnaires), physical activity (using wearable devices) and metabolic profile.



The BioSystems Modeling group is involved in data analysis with the application of systems biology approaches.



},

howpublished = {Funder: Regione Toscana, Bando Salute},

keywords = {},

pubstate = {published},

tppubtype = {misc}

}

@misc{PRA_2020,

title = {Metodi Informatici Integrati per la Biomedica},

year  = {2020},

date = {2020-12-29},

abstract = {This project aims at integrating different computer methodologies that contribute to interdisciplinary research in bioinformatics and, in particular, to its applications in the biomedical field. This in order to experiment the co-existence of algorithmic, modeling, and machine learning methods in the analysis of biomedical data and, at the same time, to refine the synergy of the many research groups that have been active in the Department of Computer Science for decades.},

howpublished = {PRA – Progetti di Ricerca di Ateneo (Institutional Research Grants) - Project no. PRA_2020-2021_26 },

keywords = {},

pubstate = {published},

tppubtype = {misc}

}