Murray Patterson
Impact in
- Genetics top 10%
- Genome Rearrangement Algorithms
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- Genomics and Phylogenetic Studies
- Machine Learning in Bioinformatics
- Gene expression and cancer classification
- Fractal and DNA sequence analysis
Papers in
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- Machine Learning in Bioinformatics 16
- Genomics and Phylogenetic Studies 12
- Fractal and DNA sequence analysis 8
- Gene expression and cancer classification 7
- Genetics 13
- Genome Rearrangement Algorithms 10
- Co-authors
- Sarwan Ali (22 shared papers)Nadia Pisanti (2 shared papers)Tobias Marschall (3 shared papers)Leen Stougie (1 shared paper)Leo van Iersel (1 shared paper)Alexander Schönhuth (2 shared papers)Gunnar W. Klau (2 shared papers)Gianluca Della Vedova (10 shared papers)
- Journals
- Journal of Computational Biology (8 papers)BMC Bioinformatics (6 papers)Biology (2 papers)Quantitative Biology (1 paper)Expert Systems with Applications (1 paper)
- Partner nations
- United StatesItalyCanada
In The Last Decade
Murray Patterson
43 papers receiving 530 citations
Peers
Comparison fields: 5 of 81
- Genetics 169
- Molecular Biology 316
- Cancer Research 43
- Infectious Diseases 44
- Health Informatics 3
Countries citing papers authored by Murray Patterson
This map shows the geographic impact of Murray Patterson'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 Murray Patterson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Murray Patterson more than expected).
Fields of papers citing papers by Murray Patterson
This network shows the impact of papers produced by Murray Patterson. 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 Murray Patterson. The network helps show where Murray Patterson may publish in the future.
Co-authors
The 25 scholars most cited alongside Murray Patterson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 229 | |
| 2 | 2019 | 27 | |
| 3 | 2021 | 25 | |
| 4 | 2017 | 23 | |
| 5 | 2022 | 23 | |
| 6 | 2020 | 20 | |
| 7 | 2022 | 20 | |
| 8 | 2012 | 16 | |
| 9 | 2013 | 16 | |
| 10 | 2023 | 13 | |
| 11 | 2020 | 9 | |
| 12 | 2022 | 9 | |
| 13 | 2023 | 8 | |
| 14 | 2021 | 8 | |
| 15 | 2016 | 8 | |
| 16 | 2011 | 8 | |
| 17 | 2021 | 7 | |
| 18 | 2018 | 6 | |
| 19 | 2009 | 6 | |
| 20 | 2023 | 5 |
About Murray Patterson
Murray Patterson is a scholar working on Molecular Biology, Genetics, Artificial Intelligence, Infectious Diseases and Cancer Research, having authored 46 papers that have together received 536 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (16 papers), Genomics and Phylogenetic Studies (12 papers), Genome Rearrangement Algorithms (10 papers), Fractal and DNA sequence analysis (8 papers), Gene expression and cancer classification (7 papers), Algorithms and Data Compression (7 papers), SARS-CoV-2 and COVID-19 Research (7 papers) and Cancer Genomics and Diagnostics (6 papers). The work is most often cited by research in Genetics (169 citations), Molecular Biology (316 citations), Cancer Research (43 citations), Infectious Diseases (44 citations) and Health Informatics (3 citations). Murray Patterson has collaborated with scholars based in United States, Italy and Canada. Frequent co-authors include Sarwan Ali, Nadia Pisanti, Tobias Marschall, Leen Stougie, Leo van Iersel, Alexander Schönhuth, Gunnar W. Klau, Gianluca Della Vedova, Ján Maňuch and Paola Bonizzoni. Their work appears in journals such as Journal of Computational Biology, BMC Bioinformatics, Biology, Quantitative Biology and Expert Systems with Applications.
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.