Raymond Lo
- Molecular Biology top 2%
- Ecology top 2%
- Genetics top 5%
- Epidemiology top 5%
- Immunology top 5%
- Co-authors
- Fiona S. L. BrinkmanMatthew R. LairdGeoffrey L. WinsorMartin EsterJames WagnerLeonard J. FosterS. Cenk ŞahinalpNancy Yu
- Topics
- Genomics and Phylogenetic Studies (7 papers)Machine Learning in Bioinformatics (3 papers)Bacterial Genetics and Biotechnology (3 papers)
- Partner nations
- CanadaIrelandUnited States
In The Last Decade
Raymond Lo
16 papers receiving 4.5k citations
Hit Papers
Peers
Comparison fields: 5 of 143
- Molecular Biology 2.9k
- Ecology 779
- Genetics 667
- Epidemiology 557
- Immunology 512
Countries citing papers authored by Raymond Lo
This map shows the geographic impact of Raymond Lo'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 Raymond Lo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raymond Lo more than expected).
Fields of papers citing papers by Raymond Lo
This network shows the impact of papers produced by Raymond Lo. 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 Raymond Lo. The network helps show where Raymond Lo may publish in the future.
Co-authorship network of co-authors of Raymond Lo
This figure shows the co-authorship network connecting the top 25 collaborators of Raymond Lo. A scholar is included among the top collaborators of Raymond Lo 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 Raymond Lo. Raymond Lo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 23 | |
| 3 | 27 | |
| 4 | 9 | |
| 5 | 103 | |
| 6 | 57 | |
| 7 | 239 | |
| 8 | Enhanced annotations and features for comparing thousands ofPseudomonasgenomes in the Pseudomonas genome databasebreakdown → | 762 |
| 9 | 1 | |
| 10 | InnateDB: systems biology of innate immunity and beyond—recent updates and continuing curationbreakdown → | 858 |
| 11 | 82 | |
| 12 | 62 | |
| 13 | PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotesbreakdown → | 1935 |
| 14 | 203 | |
| 15 | 73 | |
| 16 | 34 | |
| 17 | 123 |
About Raymond Lo
Raymond Lo is a scholar working on Environmental Chemistry, Immunology and Molecular Biology, having authored 17 papers that have together received 4.6k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (7 papers), Machine Learning in Bioinformatics (3 papers) and Bacterial Genetics and Biotechnology (3 papers). The work is most often cited by research in Molecular Medicine (434 citations), Endocrinology (417 citations) and Microbiology (402 citations). Raymond Lo has collaborated with scholars based in Canada, Ireland and United States. Frequent co-authors include Fiona S. L. Brinkman, Matthew R. Laird, Geoffrey L. Winsor, Martin Ester, James Wagner, Leonard J. Foster, S. Cenk Şahinalp, Nancy Yu, Phuong Dao and Gabor Melli. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and Journal of Cell Science.
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.