Daniel Fasulo
Impact in
- Endocrinology top 10%
- Escherichia coli research studies
- Enterobacteriaceae and Cronobacter Research
-
- Antibiotic Resistance in Bacteria
Papers in
-
- Genomics and Phylogenetic Studies 6
- Bioinformatics and Genomic Networks 4
- Metabolomics and Mass Spectrometry Studies 3
- Gene expression and cancer classification 3
- Genomics and Chromatin Dynamics 2
- Genetics 3
- Genetic Mapping and Diversity in Plants and Animals 2
- Genetic Associations and Epidemiology 2
- Co-authors
- Rebecca L. Lindsey (1 shared paper)Nancy Strockbine (1 shared paper)Lori M. Gladney (1 shared paper)Aaron L. Halpern (3 shared papers)Clark Mobarry (1 shared paper)Melissa J. Caimano (1 shared paper)Joerg Graf (1 shared paper)Eric W. Jackson (1 shared paper)
- Journals
- Journal of Computational Biology (3 papers)Bioinformatics (2 papers)mBio (1 paper)BMC Bioinformatics (1 paper)BMC Cancer (1 paper)
- Partner nations
- United StatesIsraelSwitzerland
In The Last Decade
Daniel Fasulo
16 papers receiving 207 citations
Peers
Comparison fields: 5 of 70
- Endocrinology 55
- Molecular Medicine 23
- Human-Computer Interaction 12
- Spectroscopy 30
- Food Science 31
Countries citing papers authored by Daniel Fasulo
This map shows the geographic impact of Daniel Fasulo'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 Daniel Fasulo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Fasulo more than expected).
Fields of papers citing papers by Daniel Fasulo
This network shows the impact of papers produced by Daniel Fasulo. 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 Daniel Fasulo. The network helps show where Daniel Fasulo may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Fasulo, 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 | 2017 | 69 | |
| 2 | 2021 | 33 | |
| 3 | 2007 | 24 | |
| 4 | 1996 | 18 | |
| 5 | 2002 | 17 | |
| 6 | 2010 | 13 | |
| 7 | 2013 | 10 | |
| 8 | 1999 | 7 | |
| 9 | 2002 | 6 | |
| 10 | 1997 | 6 | |
| 11 | 2007 | 5 | |
| 12 | 2011 | 4 | |
| 13 | 2006 | 4 | |
| 14 | 2001 | 3 | |
| 15 | 2006 | 1 | |
| 16 | Algorithms for dna restriction mapping | 2000 | 1 |
About Daniel Fasulo
Daniel Fasulo is a scholar working on Molecular Biology, Genetics, Spectroscopy, Artificial Intelligence and Endocrinology, having authored 16 papers that have together received 221 indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (6 papers), Bioinformatics and Genomic Networks (4 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Advanced Proteomics Techniques and Applications (3 papers), Gene expression and cancer classification (3 papers), Genomics and Chromatin Dynamics (2 papers), Genetic Mapping and Diversity in Plants and Animals (2 papers) and Genetic Associations and Epidemiology (2 papers). The work is most often cited by research in Endocrinology (55 citations), Molecular Medicine (23 citations), Human-Computer Interaction (12 citations), Spectroscopy (30 citations) and Food Science (31 citations). Daniel Fasulo has collaborated with scholars based in United States, Israel and Switzerland. Frequent co-authors include Rebecca L. Lindsey, Nancy Strockbine, Lori M. Gladney, Aaron L. Halpern, Clark Mobarry, Melissa J. Caimano, Joerg Graf, Eric W. Jackson, Mark D. Driscoll and Adam Matson. Their work appears in journals such as Journal of Computational Biology, Bioinformatics, mBio, BMC Bioinformatics and BMC Cancer.
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.