Andrea Manconi
- Co-authors
- Giuliano ArmanoLuciano MilanesiAlessandro OrroMatteo GnocchiJessica ZampolliPatrizia Di GennaroAntonino NatalelloDiletta Ami
- Topics
- Machine Learning in Bioinformatics (4 papers)Genomics and Phylogenetic Studies (4 papers)Web Data Mining and Analysis (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
- Partner nations
- ItalyUnited States
In The Last Decade
Andrea Manconi
25 papers receiving 227 citations
Peers
Comparison fields: 5 of 94
- Molecular Biology 74
- Pollution 59
- Artificial Intelligence 44
- Biomaterials 29
- Plant Science 22
Countries citing papers authored by Andrea Manconi
This map shows the geographic impact of Andrea Manconi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Andrea Manconi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrea Manconi more than expected).
Fields of papers citing papers by Andrea Manconi
This network shows the impact of papers produced by Andrea Manconi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Andrea Manconi. The network helps show where Andrea Manconi may publish in the future.
Co-authorship network of co-authors of Andrea Manconi
This figure shows the co-authorship network connecting the top 25 collaborators of Andrea Manconi. A scholar is included among the top collaborators of Andrea Manconi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Andrea Manconi. Andrea Manconi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 8 | |
| 3 | 4 | |
| 4 | 2 | |
| 5 | 2 | |
| 6 | 11 | |
| 7 | 25 | |
| 8 | 54 | |
| 9 | 9 | |
| 10 | Automated detection of lunar rockfalls using a Faster Region-based Convolutional Neural Network | 1 |
| 11 | 29 | |
| 12 | 6 | |
| 13 | 6 | |
| 14 | 4 | |
| 15 | 11 | |
| 16 | 2 | |
| 17 | 1 | |
| 18 | A MultiAgent System for Personalized Press Reviews | 1 |
| 19 | PACMAS: A Personalized, Adaptive, and Cooperative MultiAgent System Architecture | 3 |
| 20 | Text Categorization Using a Personalized, Adaptive, and Cooperative MultiAgent System | 1 |
About Andrea Manconi
Andrea Manconi is a scholar working on Artificial Intelligence, Information Systems and Management and Information Systems, having authored 25 papers that have together received 229 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (4 papers), Genomics and Phylogenetic Studies (4 papers) and Web Data Mining and Analysis (3 papers). The work is most often cited by research in Health Informatics (8 citations), Pollution (59 citations) and Industrial and Manufacturing Engineering (19 citations). Andrea Manconi has collaborated with scholars based in Italy and United States. Frequent co-authors include Giuliano Armano, Luciano Milanesi, Alessandro Orro, Matteo Gnocchi, Jessica Zampolli, Patrizia Di Gennaro, Antonino Natalello, Diletta Ami, Andrea Loddo and Cecilia Di Ruberto. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.