F. de Ferra
Impact in
- Developmental Neuroscience top 10%
- Neurogenesis and neuroplasticity mechanisms
- Microbiology top 10%
- Bacterial Infections and Vaccines
Papers in
-
- Glycosylation and Glycoproteins Research 2
- Advanced biosensing and bioanalysis techniques 1
- Machine Learning in Bioinformatics 1
- Genetics 6
- Bacterial Genetics and Biotechnology 3
- Virus-based gene therapy research 3
- Co-authors
- Robert A. Lazzarini (2 shared papers)John Kamholz (1 shared paper)C Puckett (1 shared paper)Susan M. Molineaux (1 shared paper)Lynn D. Hudson (1 shared paper)Corrado Baglioni (2 shared papers)Guido Grandi (4 shared papers)Manuela Helmer‐Citterich (2 shared papers)
- Journals
- Frontiers in Genetics (2 papers)Proceedings of the National Academy of Sciences (2 papers)Molecular Microbiology (1 paper)Microbial Pathogenesis (1 paper)Applied Microbiology and Biotechnology (1 paper)
- Partner nations
- ItalyUnited StatesNetherlands
In The Last Decade
F. de Ferra
13 papers receiving 396 citations
Peers
Comparison fields: 5 of 70
- Developmental Neuroscience 64
- Microbiology 52
- Molecular Biology 263
- Endocrinology 19
- Cellular and Molecular Neuroscience 51
Countries citing papers authored by F. de Ferra
This map shows the geographic impact of F. de Ferra'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 F. de Ferra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites F. de Ferra more than expected).
Fields of papers citing papers by F. de Ferra
This network shows the impact of papers produced by F. de Ferra. 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 F. de Ferra. The network helps show where F. de Ferra may publish in the future.
Co-authors
The 20 scholars most cited alongside F. de Ferra, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 1986 | 134 | |
| 2 | 1986 | 120 | |
| 3 | 1988 | 28 | |
| 4 | 1983 | 20 | |
| 5 | 1999 | 19 | |
| 6 | 1991 | 17 | |
| 7 | 1980 | 15 | |
| 8 | 2014 | 14 | |
| 9 | 2003 | 13 | |
| 10 | 2014 | 11 | |
| 11 | 1990 | 9 | |
| 12 | 2014 | 3 | |
| 13 | Characterization of the srfA locus of Bacillus subtilis | 1993 | 1 |
About F. de Ferra
F. de Ferra is a scholar working on Molecular Biology, Genetics, Ecology, Pharmacology and Pollution, having authored 13 papers that have together received 404 indexed citations. Recurring topics across this work include Bacterial Genetics and Biotechnology (3 papers), Virus-based gene therapy research (3 papers), Bacteriophages and microbial interactions (2 papers), Glycosylation and Glycoproteins Research (2 papers), Advanced biosensing and bioanalysis techniques (1 paper), Machine Learning in Bioinformatics (1 paper), Computational Drug Discovery Methods (1 paper) and Animal Virus Infections Studies (1 paper). The work is most often cited by research in Developmental Neuroscience (64 citations), Microbiology (52 citations), Molecular Biology (263 citations), Endocrinology (19 citations) and Cellular and Molecular Neuroscience (51 citations). F. de Ferra has collaborated with scholars based in Italy, United States and Netherlands. Frequent co-authors include Robert A. Lazzarini, John Kamholz, C Puckett, Susan M. Molineaux, Lynn D. Hudson, Corrado Baglioni, Guido Grandi, Manuela Helmer‐Citterich, Antonio Palmeri and Marcella Simili. Their work appears in journals such as Frontiers in Genetics, Proceedings of the National Academy of Sciences, Molecular Microbiology, Microbial Pathogenesis and Applied Microbiology and Biotechnology.
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.