H. Saito
- Epidemiology top 10%
- Cell Biology top 5%
- Molecular Biology
- Plant Science
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Hideyo YamaguchiKoichi MakimuraKatsuhisa UchidaAtsuhiko HasegawaTakashi MochizukiYoshiko TamuraRyo HanazawaMitsuru Matsumoto
- Topics
- Bacteriophages and microbial interactions (6 papers)RNA and protein synthesis mechanisms (6 papers)Optical measurement and interference techniques (4 papers)
- Cited by
- Cell BiologyEpidemiologyDermatology
- Partner nations
- Japan
In The Last Decade
H. Saito
25 papers receiving 697 citations
Peers
Comparison fields: 5 of 104
- Epidemiology 382
- Cell Biology 330
- Molecular Biology 164
- Plant Science 103
- Computer Vision and Pattern Recognition 68
Countries citing papers authored by H. Saito
This map shows the geographic impact of H. Saito'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 H. Saito with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites H. Saito more than expected).
Fields of papers citing papers by H. Saito
This network shows the impact of papers produced by H. Saito. 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 H. Saito. The network helps show where H. Saito may publish in the future.
Co-authorship network of co-authors of H. Saito
This figure shows the co-authorship network connecting the top 25 collaborators of H. Saito. A scholar is included among the top collaborators of H. Saito 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 H. Saito. H. Saito 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 | 1 | |
| 3 | 3 | |
| 4 | 214 | |
| 5 | 58 | |
| 6 | Effects of stem cell factor (SCF) on human marrow neutrophil, neutrophil/macrophage mixed, macrophage and eosinophil progenitor cell growth. | 11 |
| 7 | 2 | |
| 8 | Remission induction of acute promyelocytic leukemia by all-trans-retinoic acid: molecular evidence of restoration of normal hematopoiesis after differentiation and subsequent extinction of leukemic clone. | 30 |
| 9 | 2 | |
| 10 | 2 | |
| 11 | 1 | |
| 12 | 9 | |
| 13 | 6 | |
| 14 | 1 | |
| 15 | 1 | |
| 16 | 15 | |
| 17 | 24 | |
| 18 | 62 | |
| 19 | 9 | |
| 20 | 1 |
About H. Saito
H. Saito is a scholar working on Ecology, Biotechnology and Computer Vision and Pattern Recognition, having authored 27 papers that have together received 754 indexed citations. Recurring topics across this work include Bacteriophages and microbial interactions (6 papers), RNA and protein synthesis mechanisms (6 papers) and Optical measurement and interference techniques (4 papers). The work is most often cited by research in Cell Biology (330 citations), Epidemiology (382 citations) and Dermatology (40 citations). H. Saito has collaborated with scholars based in Japan. Frequent co-authors include Hideyo Yamaguchi, Koichi Makimura, Katsuhisa Uchida, Atsuhiko Hasegawa, Takashi Mochizuki, Yoshiko Tamura, Ryo Hanazawa, Mitsuru Matsumoto, Yōnosuke Ikeda and Yoshimasa Sakakibara. Their work appears in journals such as Blood, Journal of Clinical Microbiology and Journal of Pharmacology and Experimental Therapeutics.
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.