Ron Shigeta

590 total citations
10 papers, 434 citations indexed

About

Ron Shigeta is a scholar working on Molecular Biology, Infectious Diseases and Cellular and Molecular Neuroscience. According to data from OpenAlex, Ron Shigeta has authored 10 papers receiving a total of 434 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 1 paper in Infectious Diseases and 1 paper in Cellular and Molecular Neuroscience. Recurrent topics in Ron Shigeta's work include Gene expression and cancer classification (2 papers), Machine Learning in Bioinformatics (2 papers) and RNA and protein synthesis mechanisms (2 papers). Ron Shigeta is often cited by papers focused on Gene expression and cancer classification (2 papers), Machine Learning in Bioinformatics (2 papers) and RNA and protein synthesis mechanisms (2 papers). Ron Shigeta collaborates with scholars based in United States, Sweden and Singapore. Ron Shigeta's co-authors include Michael Ristow, Young‐In Chi, Steven E. Shoelson, Sirano Dhe‐Paganon, Clarence E. Schutt, Hans E. M. Christensen, Uno Lindberg, Nam‐Hai Chua, Melissa Cline and David Kulp and has published in prestigious journals such as Journal of Biological Chemistry, Bioinformatics and Structure.

In The Last Decade

Ron Shigeta

10 papers receiving 418 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ron Shigeta United States	6	325	141	78	53	35	10	434
G Payne United States	10	466 1.4×	199 1.4×	28 0.4×	22 0.4×	20 0.6×	12	660
Martin Linke Germany	11	275 0.8×	106 0.8×	59 0.8×	23 0.4×	12 0.3×	14	450
G. Martinez United States	7	463 1.4×	67 0.5×	42 0.5×	26 0.5×	13 0.4×	10	625
Valerio Marino Italy	13	452 1.4×	130 0.9×	98 1.3×	12 0.2×	2 0.1×	45	593
Bradford O. Fanger United States	11	315 1.0×	65 0.5×	41 0.5×	28 0.5×	4 0.1×	18	462
Thomas Lauber Germany	9	250 0.8×	68 0.5×	37 0.5×	38 0.7×	1 0.0×	15	508
Ryuji Tanimura Japan	15	519 1.6×	77 0.5×	41 0.5×	15 0.3×	20 0.6×	32	669
Christopher C. Beltzner United States	7	489 1.5×	77 0.5×	529 6.8×	29 0.5×	4 0.1×	8	793
Anna Y. Kornilova United States	9	332 1.0×	66 0.5×	94 1.2×	9 0.2×	11 0.3×	12	557
Rogier A. Smits Netherlands	17	508 1.6×	102 0.7×	4 0.1×	58 1.1×	10 0.3×	24	973

Countries citing papers authored by Ron Shigeta

Since Specialization

Citations

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

Fields of papers citing papers by Ron Shigeta

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ron Shigeta

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

All Works

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10 of 10 papers shown

1.

Kuwabara, Chikako, Kenji Matsumoto, Ron Shigeta, et al.. (2025). Simultaneous site-directed mutagenesis for soybean ß-amyrin synthase genes via DNA-free CRISPR/Cas9 system using a single gRNA. Plant Cell Reports. 44(2). 40–40. 1 indexed citations

2.

Shigeta, Ron, et al.. (2013). Statistical models for predicting liver toxicity from genomic data. 1(2). 144–149. 5 indexed citations

3.

Cheng, Jill, Adam Tracy, Earl Hubbell, et al.. (2004). NetAffx Gene Ontology Mining Tool: a visual approach for microarray data analysis. Bioinformatics. 20(9). 1462–1463. 66 indexed citations

4.

Shigeta, Ron, et al.. (2003). GPCR-GRAPA-LIB—a refined library of hidden Markov Modelsfor annotating GPCRs. Bioinformatics. 19(5). 667–668. 4 indexed citations

5.

Cline, Melissa, et al.. (2003). THE EFFECTS OF ALTERNATIVE SPLICING ON TRANSMEMBRANE PROTEINS IN THE MOUSE GENOME. PubMed. 17–28. 25 indexed citations

6.

Liu, Guoying, Ann E. Loraine, Ron Shigeta, et al.. (2002). NetAffx. 147–150. 5 indexed citations

7.

Dhe‐Paganon, Sirano, Ron Shigeta, Young‐In Chi, Michael Ristow, & Steven E. Shoelson. (2000). Crystal Structure of Human Frataxin. Journal of Biological Chemistry. 275(40). 30753–30756. 181 indexed citations

8.

Christensen, Hans E. M., et al.. (1997). The crystal structure of a major allergen from plants. Structure. 5(1). 19–32. 108 indexed citations

9.

Shigeta, Ron, Kaya Forest, Lei Yan, Daniel Kahne, & Clarence E. Schutt. (1994). Isomorphous binding of mercury-substituted thiosaccharides to pertussis toxin crystals yields crystallographic phases. Acta Crystallographica Section D Biological Crystallography. 50(1). 71–74. 5 indexed citations

10.

Blackburn, Ninian J., et al.. (1990). Characterization of a carbon monoxide complex of reduced dopamine beta-hydroxylase. Evidence for inequivalence of the Cu(I) centers.. Journal of Biological Chemistry. 265(26). 15383–15386. 34 indexed citations

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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