Seiya Imoto

46 total papers · 3.7k total citations
21 papers, 2.8k citations indexed

About

Seiya Imoto is a scholar working on Molecular Biology, Artificial Intelligence and Information Systems. According to data from OpenAlex, Seiya Imoto has authored 21 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 10 papers in Artificial Intelligence and 2 papers in Information Systems. Recurrent topics in Seiya Imoto's work include Gene expression and cancer classification (17 papers), Bioinformatics and Genomic Networks (11 papers) and Gene Regulatory Network Analysis (7 papers). Seiya Imoto is often cited by papers focused on Gene expression and cancer classification (17 papers), Bioinformatics and Genomic Networks (11 papers) and Gene Regulatory Network Analysis (7 papers). Seiya Imoto collaborates with scholars based in Japan, United States and Fiji. Seiya Imoto's co-authors include Satoru Miyano, Michiel de Hoon, John P. Nolan, Alok Sharma, Vandana Sharma, Kuldip K. Paliwal, Atsushi Niida, Rui Yamaguchi, Michael Q. Zhang and Hiroyuki Aburatani and has published in prestigious journals such as Bioinformatics, British Journal of Pharmacology and BMC Bioinformatics.

In The Last Decade

Seiya Imoto

19 papers receiving 2.7k citations

Hit Papers

Open source clustering so... 2004 2026 2011 2018 2004 500 1000 1.5k 2.0k

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Seiya Imoto 1.7k 435 305 259 235 21 2.8k
Vahid Jalili 1.9k 1.1× 423 1.0× 219 0.7× 309 1.2× 228 1.0× 31 3.8k
Barry Demchak 1.6k 0.9× 260 0.6× 386 1.3× 171 0.7× 198 0.8× 22 2.6k
Benoît Gautier 1.9k 1.1× 306 0.7× 250 0.8× 310 1.2× 172 0.7× 33 3.5k
Florian Rohart 1.7k 1.0× 314 0.7× 262 0.9× 342 1.3× 161 0.7× 16 3.2k
Peter Woolf 1.7k 1.0× 522 1.2× 147 0.5× 194 0.7× 233 1.0× 41 2.8k
Adam Maciejewski 2.2k 1.3× 363 0.8× 282 0.9× 263 1.0× 277 1.2× 61 4.0k
Sonia Tarazona 2.1k 1.2× 457 1.1× 588 1.9× 336 1.3× 236 1.0× 31 3.2k
Johannes Köster 1.6k 0.9× 367 0.8× 248 0.8× 307 1.2× 134 0.6× 44 2.4k
Farrokh Mehryary 2.0k 1.2× 255 0.6× 446 1.5× 323 1.2× 353 1.5× 14 3.6k
Gregory D. Schuler 2.6k 1.5× 475 1.1× 157 0.5× 623 2.4× 192 0.8× 25 3.3k

Countries citing papers authored by Seiya Imoto

Since Specialization
Citations

This map shows the geographic impact of Seiya Imoto'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 Seiya Imoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Seiya Imoto more than expected).

Fields of papers citing papers by Seiya Imoto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seiya Imoto. 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 Seiya Imoto. The network helps show where Seiya Imoto may publish in the future.

Co-authorship network of co-authors of Seiya Imoto

This figure shows the co-authorship network connecting the top 25 collaborators of Seiya Imoto. A scholar is included among the top collaborators of Seiya Imoto 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 Seiya Imoto. Seiya Imoto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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.

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