James C. Sacchettini
- Molecular Biology top 0.1%
- Infectious Diseases top 0.1%
- Epidemiology top 0.5%
- Materials Chemistry top 1%
- Oncology top 1%
- Co-authors
- Thomas R. IoergerJeffrey I. GordonLi‐Wei HungRalf W. Grosse‐KunstlevePaul D. AdamsThomas C. TerwilligerRandy J. ReadNicholas K. Sauter
- Topics
- Tuberculosis Research and Epidemiology (103 papers)Enzyme Structure and Function (72 papers)Biochemical and Molecular Research (65 papers)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
James C. Sacchettini
288 papers receiving 23.1k citations
Hit Papers
Peers
Comparison fields: 5 of 170
- Molecular Biology 14.9k
- Infectious Diseases 5.5k
- Epidemiology 4.1k
- Materials Chemistry 2.9k
- Oncology 2.4k
Countries citing papers authored by James C. Sacchettini
This map shows the geographic impact of James C. Sacchettini'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 James C. Sacchettini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James C. Sacchettini more than expected).
Fields of papers citing papers by James C. Sacchettini
This network shows the impact of papers produced by James C. Sacchettini. 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 James C. Sacchettini. The network helps show where James C. Sacchettini may publish in the future.
Co-authorship network of co-authors of James C. Sacchettini
This figure shows the co-authorship network connecting the top 25 collaborators of James C. Sacchettini. A scholar is included among the top collaborators of James C. Sacchettini 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 James C. Sacchettini. James C. Sacchettini is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 5 | |
| 3 | 4 | |
| 4 | 56 | |
| 5 | 48 | |
| 6 | 124 | |
| 7 | 6 | |
| 8 | 22 | |
| 9 | 64 | |
| 10 | 24 | |
| 11 | 32 | |
| 12 | 51 | |
| 13 | 3 | |
| 14 | 157 | |
| 15 | 116 | |
| 16 | TEXTAL™: automated crystallographic protein structure determination | 1 |
| 17 | 39 | |
| 18 | TEXTAL TM : Artificial Intelligence Techniques for Automated Protein Structure Determination. | 5 |
| 19 | 307 | |
| 20 | Evolutionary relationships and functional conservation among vertebrate Max-associated proteins: the zebra fish homolog of Mxi1. | 25 |
About James C. Sacchettini
James C. Sacchettini is a scholar working on Infectious Diseases, Molecular Medicine and Molecular Biology, having authored 292 papers that have together received 23.4k indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (103 papers), Enzyme Structure and Function (72 papers) and Biochemical and Molecular Research (65 papers). The work is most often cited by research in Infectious Diseases (5.5k citations), Molecular Medicine (1.1k citations) and Molecular Biology (14.9k citations). James C. Sacchettini has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Thomas R. Ioerger, Jeffrey I. Gordon, Li‐Wei Hung, Ralf W. Grosse‐Kunstleve, Paul D. Adams, Thomas C. Terwilliger, Randy J. Read, Nicholas K. Sauter, Nigel W. Moriarty and Airlie J. McCoy. Their work appears in journals such as Science, Cell and Proceedings of the National Academy of Sciences.
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.