Tomoya Maeda

38 total papers · 683 total citations
28 papers, 463 citations indexed

About

Tomoya Maeda is a scholar working on Molecular Biology, Genetics and Biomedical Engineering. According to data from OpenAlex, Tomoya Maeda has authored 28 papers receiving a total of 463 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 15 papers in Genetics and 4 papers in Biomedical Engineering. Recurrent topics in Tomoya Maeda's work include Microbial Metabolic Engineering and Bioproduction (14 papers), Bacterial Genetics and Biotechnology (9 papers) and Evolution and Genetic Dynamics (8 papers). Tomoya Maeda is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (14 papers), Bacterial Genetics and Biotechnology (9 papers) and Evolution and Genetic Dynamics (8 papers). Tomoya Maeda collaborates with scholars based in Japan, Germany and France. Tomoya Maeda's co-authors include Chikara Furusawa, Takaaki Horinouchi, Masaaki Wachi, Takashi Hirasawa, Hazuki Kotani, Gerd M. Seibold, Jung-Won Youn, Reinhard Krämer, Kay Marin and Volker F. Wendisch and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Applied and Environmental Microbiology.

In The Last Decade

Tomoya Maeda

25 papers receiving 459 citations

Author Peers

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

Author						Papers	Cites
Tomoya Maeda	350	139	98	48	37	28	463
Ok Bin Kim	295 0.8×	142 1.0×	62 0.6×	38 0.8×	65 1.8×	27	480
Inseong Jo	314 0.9×	94 0.7×	63 0.6×	58 1.2×	45 1.2×	40	518
Dandan Wang	331 0.9×	95 0.7×	51 0.5×	30 0.6×	39 1.1×	30	484
Preeti Verma	200 0.6×	86 0.6×	90 0.9×	17 0.4×	21 0.6×	42	454
Sook‐Kyung Kim	318 0.9×	130 0.9×	48 0.5×	31 0.6×	45 1.2×	32	513
V. Samuel Raj	327 0.9×	101 0.7×	47 0.5×	38 0.8×	49 1.3×	31	503
Nadine A. Solomon	302 0.9×	62 0.4×	103 1.1×	21 0.4×	36 1.0×	14	447
María Teresa Pellicer Jordá	282 0.8×	110 0.8×	30 0.3×	38 0.8×	39 1.1×	29	429
Qiu Meng	276 0.8×	77 0.6×	37 0.4×	44 0.9×	39 1.1×	30	437
Dawei Wei	198 0.6×	92 0.7×	38 0.4×	132 2.8×	40 1.1×	26	505

Countries citing papers authored by Tomoya Maeda

Since Specialization

Citations

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

Fields of papers citing papers by Tomoya Maeda

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tomoya Maeda

This figure shows the co-authorship network connecting the top 25 collaborators of Tomoya Maeda. A scholar is included among the top collaborators of Tomoya Maeda 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 Tomoya Maeda. Tomoya Maeda 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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