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Giuseppe Agapito
Researcher at Magna Græcia University
Publications - 88
Citations - 974
Giuseppe Agapito is an academic researcher from Magna Græcia University. The author has contributed to research in topics: Association rule learning & Computer science. The author has an hindex of 15, co-authored 69 publications receiving 621 citations.
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Visualization of protein interaction networks: problems and solutions
TL;DR: A current trend is the deployment of open, extensible visualization tools (e.g. Cytoscape), that may be incrementally enriched by the interactomics community with novel and more powerful functions for PIN analysis, through the development of plug-ins.
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DMET™ (Drug Metabolism Enzymes and Transporters): a pharmacogenomic platform for precision medicine.
Mariamena Arbitrio,Maria Teresa Di Martino,Francesca Scionti,Giuseppe Agapito,Pietro Hiram Guzzi,Mario Cannataro,Mario Cannataro,Pierfrancesco Tassone,Pierosandro Tagliaferri +8 more
TL;DR: This review focuses on the potentiality, reliability and limitations of the DMET™ (Drug Metabolism Enzymes and Transporters) Plus as pharmacogenomic drug metabolism multi-gene panel platform for selecting biomarkers in the final aim to optimize drugs use and characterize the individual genetic background.
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DMET-Analyzer: automatic analysis of Affymetrix DMET Data
Pietro Hiram Guzzi,Giuseppe Agapito,Maria Teresa Di Martino,Mariamena Arbitrio,Pierfrancesco Tassone,Pierosandro Tagliaferri,Mario Cannataro +6 more
TL;DR: DMET Analyzer is a novel tool able to automatically analyse data produced by the DMET-platform in case-control association studies, and may avoid wasting time in the manual execution of multiple statistical tests avoiding possible errors and reducing the amount of time needed for a whole experiment.
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DIETOS: A dietary recommender system for chronic diseases monitoring and management.
Giuseppe Agapito,Mariadelina Simeoni,Barbara Calabrese,Ilaria Carè,Theodora Lamprinoudi,Pietro Hiram Guzzi,Arturo Pujia,Giorgio Fuiano,Mario Cannataro +8 more
TL;DR: DIETOS is a novel food recommender system for healthy people and individuals affected by diet-related chronic diseases, allowing to determine a medical-controlled user's health profile and to perform a fine-grained recommendation that is better adapted to each user health status.
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DMET-Miner
TL;DR: DMET-Miner extends the DMET-Analyzer tool with data mining capabilities and correlates the presence of a set of allelic variants with the conditions of patient's samples by exploiting association rules, to face the high number of frequent itemsets generated when considering large clinical studies based on DMET data.