M Waterman
Impact in
- Artificial Intelligence top 10%
- Algorithms and Data Compression
Papers in
-
- Genomics and Phylogenetic Studies 6
- Machine Learning in Bioinformatics 3
- Fractal and DNA sequence analysis 2
- RNA and protein synthesis mechanisms 1
- Glycosylation and Glycoproteins Research 1
-
- Algorithms and Data Compression 6
- Co-authors
- Jerrold R. Griggs (1 shared paper)Michael Schöniger (1 shared paper)T. Šlezak (1 shared paper)David J. Galas (1 shared paper)A.V. Carrano (1 shared paper)Elbert Branscomb (1 shared paper)Fritz Schweiger (1 shared paper)Assaf Shechter (2 shared papers)
- Journals
- Bulletin of Mathematical Biology (7 papers)Insect Molecular Biology (2 papers)Journal of Number Theory (1 paper)Genomics (1 paper)Philosophical Transactions of the Royal Society B Biological Sciences (1 paper)
- Partner nations
- United StatesAustriaIsrael
In The Last Decade
M Waterman
12 papers receiving 425 citations
Peers
Comparison fields: 5 of 76
- Discrete Mathematics and Combinatorics 18
- Artificial Intelligence 169
- Molecular Biology 310
- Computational Theory and Mathematics 63
- Computer Graphics and Computer-Aided Design 10
Countries citing papers authored by M Waterman
This map shows the geographic impact of M Waterman'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 M Waterman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M Waterman more than expected).
Fields of papers citing papers by M Waterman
This network shows the impact of papers produced by M Waterman. 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 M Waterman. The network helps show where M Waterman may publish in the future.
Co-authors
The 13 scholars most cited alongside M Waterman, 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 | 1984 | 153 | |
| 2 | 1984 | 55 | |
| 3 | 1990 | 53 | |
| 4 | 1986 | 52 | |
| 5 | 2007 | 36 | |
| 6 | 1992 | 28 | |
| 7 | 1994 | 25 | |
| 8 | 1984 | 24 | |
| 9 | 1994 | 22 | |
| 10 | 1973 | 16 | |
| 11 | 1992 | 3 | |
| 12 | 2007 | 1 |
About M Waterman
M Waterman is a scholar working on Molecular Biology, Artificial Intelligence, Geometry and Topology, Immunology and Discrete Mathematics and Combinatorics, having authored 12 papers that have together received 468 indexed citations. Recurring topics across this work include Algorithms and Data Compression (6 papers), Genomics and Phylogenetic Studies (6 papers), Machine Learning in Bioinformatics (3 papers), Invertebrate Immune Response Mechanisms (2 papers), Fractal and DNA sequence analysis (2 papers), RNA and protein synthesis mechanisms (1 paper), Glycosylation and Glycoproteins Research (1 paper) and Aquaculture disease management and microbiota (1 paper). The work is most often cited by research in Discrete Mathematics and Combinatorics (18 citations), Artificial Intelligence (169 citations), Molecular Biology (310 citations), Computational Theory and Mathematics (63 citations) and Computer Graphics and Computer-Aided Design (10 citations). M Waterman has collaborated with scholars based in United States, Austria and Israel. Frequent co-authors include Jerrold R. Griggs, Michael Schöniger, T. Šlezak, David J. Galas, A.V. Carrano, Elbert Branscomb, Fritz Schweiger, Assaf Shechter, Chantal Dauphin‐Villemant and Vered Chalifa‐Caspi. Their work appears in journals such as Bulletin of Mathematical Biology, Insect Molecular Biology, Journal of Number Theory, Genomics and Philosophical Transactions of the Royal Society B Biological 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.