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Giuseppe Agapito
PeerJ Editor & Author
1,205 Points

Contributions by role

Preprint Author 70
Editor 1,135

Contributions by subject area

Bioinformatics
Computational Biology
Data Mining and Machine Learning
Data Science
World Wide Web and Web Science
Artificial Intelligence
Computer Vision
Computational Linguistics
Natural Language and Speech
Text Mining
Sentiment Analysis
Social Computing
Neural Networks
Cryptocurrency
Adaptive and Self-Organizing Systems
Software Engineering
Algorithms and Analysis of Algorithms
Distributed and Parallel Computing
Graphics
Scientific Computing and Simulation

Giuseppe Agapito

PeerJ Editor & Author

Summary

Giuseppe Agapito is an associate professor and a senior research scientist in the field of Parallel and Distributed Computing, Machine Learning and Graph Theory at the University Magna Græcia, Catanzaro. His research interests focus on the study of machine learning methods that can be used to take advantage of the vast amount of data that are produced nowadays. In particular, the research focuses on the development, implementation, and application of computational intelligence techniques for addressing complex real-world problems in different domains, especially in the field of biology and omics sciences.

Giuseppe Agapito has published his research in various top-quality academic outlets, with more than 100 papers in international journals and conference proceedings. He serves as a reviewer for several scientific journals and a chair and program committee member of several national and international conferences.

Bioinformatics Computational Science Data Mining & Machine Learning Distributed & Parallel Computing Genomics Network Science & Online Social Networks

Editorial Board Member

PeerJ Computer Science

Work details

Assistant Professor

University "Magna Graecia" of Catanzaro
Law, Economics and Social Sciences
Giuseppe Agapito is an assistant professor and a senior research scientist in the field of Parallel and Distributed Computing, Machine Learning and Graph Theory at the University Magna Græcia, Catanzaro, Italy. His research interests are focused on the study of machine learning methods that can be used to take advantage of the vast amount of data that are produced nowadays. In particular, the research focuses on the development, implementation, and application of computational intelligence techniques for addressing complex real-world problems in different domains, especially in the field of biology and omics sciences.

Websites

  • Google Scholar

PeerJ Contributions

  • Preprints 2
  • Edited 7
September 29, 2017 - Version: 1
GenotypeAnalytics: a RESTFul platform to mine multiple associations between SNPs and drug response in case-control studies
Giuseppe Agapito, Pietro H Guzzi, Mario Cannataro
https://doi.org/10.7287/peerj.preprints.3299v1
July 2, 2016 - Version: 1
BioPaxCOMP: an efficient system for integrating, compressing, and querying BioPAX
Giuseppe Agapito, Andrea Greco, Mario Cannataro
https://doi.org/10.7287/peerj.preprints.2210v1

Academic Editor on

July 16, 2025
A social recommendation model based on adaptive residual graph convolution networks
Rui Chen, Kangning Pang, Qingfang Liu, Lei Zhang, Hao Wu, Cundong Tang, Pu Li
https://doi.org/10.7717/peerj-cs.3010
March 19, 2025
Graph-based deep fusion for architectural text representation
Shaoyun Hu, Qingxiong Weng
https://doi.org/10.7717/peerj-cs.2735
January 9, 2025
Prediction of sentiment polarity in restaurant reviews using an ordinal regression approach based on evolutionary XGBoost
Dana A. Al-Qudah, Ala’ M. Al-Zoubi, Alexandra I. Cristea, Juan J. Merelo-Guervós, Pedro A. Castillo, Hossam Faris
https://doi.org/10.7717/peerj-cs.2370
May 10, 2024
Deep learning in finance assessing twitter sentiment impact and prediction on stocks
Kaifeng Guo, Haoling Xie
https://doi.org/10.7717/peerj-cs.2018
May 9, 2023
Adaptive sentiment analysis using multioutput classification: a performance comparison
Taqwa Hariguna, Athapol Ruangkanjanases
https://doi.org/10.7717/peerj-cs.1378
December 13, 2022
Comprehension of polarity of articles by citation sentiment analysis using TF-IDF and ML classifiers
Musarat Karim, Malik Muhammad Saad Missen, Muhammad Umer, Alisha Fida, Ala’ Abdulmajid Eshmawi, Abdullah Mohamed, Imran Ashraf
https://doi.org/10.7717/peerj-cs.1107
September 21, 2022
An analytical study on the identification of N-linked glycosylation sites using machine learning model
Muhammad Aizaz Akmal, Muhammad Awais Hassan, Shoaib Muhammad, Khaldoon S. Khurshid, Abdullah Mohamed
https://doi.org/10.7717/peerj-cs.1069