Takashi Abe
- Molecular Biology top 5%
- Plant Science top 5%
- Immunology top 5%
- Ecology top 5%
- Genetics top 5%
- Co-authors
- Toshimichi IkemuraKazuya WatanabeShigehiko KanayaMakoto KinouchiYuko YamadaTaku UchiyamaMiwako NaritaNaoto Tsuchiya
- Topics
- Genomics and Phylogenetic Studies (35 papers)Machine Learning in Bioinformatics (16 papers)RNA and protein synthesis mechanisms (15 papers)
- Partner nations
- JapanUnited StatesZambia
In The Last Decade
Takashi Abe
127 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 160
- Molecular Biology 1.9k
- Plant Science 625
- Immunology 577
- Ecology 474
- Genetics 445
Countries citing papers authored by Takashi Abe
This map shows the geographic impact of Takashi Abe'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 Takashi Abe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takashi Abe more than expected).
Fields of papers citing papers by Takashi Abe
This network shows the impact of papers produced by Takashi Abe. 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 Takashi Abe. The network helps show where Takashi Abe may publish in the future.
Co-authorship network of co-authors of Takashi Abe
This figure shows the co-authorship network connecting the top 25 collaborators of Takashi Abe. A scholar is included among the top collaborators of Takashi Abe 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 Takashi Abe. Takashi Abe 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 | 2 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 8 | |
| 7 | 27 | |
| 8 | 13 | |
| 9 | 16 | |
| 10 | Interaction with SNP Allele in Multiple Loci Contributes to Human Skin Color Diversity (1) | 1 |
| 11 | A novel bioinformatics tool for phylogenetic classification of genomic sequence fragments derived from mixed genomes of uncultured environmental microbes | 13 |
| 12 | A novel bioinformatics strategy for phylogenetic study of genomic sequence fragments: Self-organizing map (SOM) of oligonucleotide frequencies | 2 |
| 13 | 87 | |
| 14 | 20 | |
| 15 | 139 | |
| 16 | 10 | |
| 17 | 6 | |
| 18 | 7 | |
| 19 | 27 | |
| 20 | 39 |
About Takashi Abe
Takashi Abe is a scholar working on Parasitology, Molecular Biology and Hematology, having authored 135 papers that have together received 3.6k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (35 papers), Machine Learning in Bioinformatics (16 papers) and RNA and protein synthesis mechanisms (15 papers). The work is most often cited by research in Immunology (577 citations), Molecular Biology (1.9k citations) and Parasitology (139 citations). Takashi Abe has collaborated with scholars based in Japan, United States and Zambia. Frequent co-authors include Toshimichi Ikemura, Kazuya Watanabe, Shigehiko Kanaya, Makoto Kinouchi, Yuko Yamada, Taku Uchiyama, Miwako Narita, Naoto Tsuchiya, Naoki Yajima and Ryuya Yamanaka. Their work appears in journals such as Journal of the American Chemical Society, Nucleic Acids Research and Nature Biotechnology.
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.