Darryl Shibata

21.4k citations
188 papers · 15.8k indexed · 6 hit papers · h-index 55

Impact in

Papers in

Darryl Shibata

185 papers receiving 15.3k citations

Hit Papers

A Big Bang model of human colorectal tumor growth 2015 · 666 citations
666198820262000201350010001.5k2.0k

Peers

Darryl Shibata
Comparison fields: 5 of 161
  • Pathology and Forensic Medicine 6.6k
  • Cancer Research 4.8k
  • Oncology 7.4k
  • Molecular Biology 6.2k
  • Genetics 1.8k
Replace James R. Eshleman with:
James R. Eshleman United States
Michael R. Speicher Germany
Thea D. Tlsty United States
Chih Long Liu United States
Claudio Doglioni Italy
Julie Teruya‐Feldstein United States
Manuel Perucho United States
Andreas Jung Germany
Michael D. McLellan United States
Christopher A. Miller United States
Darryl Shibata relative to James R. Eshleman United States James R. Eshleman's profile →
Citations per field
00.5×1.5×
James R. Eshleman · 1×
Citations per year

Countries citing papers authored by Darryl Shibata

Since Specialization
Citations

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

Fields of papers citing papers by Darryl Shibata

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Darryl Shibata, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Darryl Shibata Line = papers co-authored together Darryl Shibata links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20252
2 20242
3 20223
4 202227
5 20181
6 201618
7 201511
8 201250
9
Variable Clonal Repopulation Dynamics Influence Chemotherapy Response in Colorectal Cancer
Hit paper breakdown →
2012557
10 20127
11 201044
12 200811
13 200777
14 20076
15 200669
16 200639
17 200483
18 199950
19 199518
20 19945

About Darryl Shibata

Darryl Shibata is a scholar working on Cancer Research, Pathology and Forensic Medicine, Oncology, Genetics and Molecular Biology, having authored 188 papers that have together received 15.8k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (82 papers), Genetic factors in colorectal cancer (72 papers), Epigenetics and DNA Methylation (35 papers), Viral-associated cancers and disorders (25 papers), Lymphoma Diagnosis and Treatment (25 papers), Colorectal Cancer Screening and Detection (14 papers), Colorectal Cancer Treatments and Studies (14 papers) and Cancer Cells and Metastasis (12 papers). The work is most often cited by research in Pathology and Forensic Medicine (6.6k citations), Cancer Research (4.8k citations), Oncology (7.4k citations), Molecular Biology (6.2k citations) and Genetics (1.8k citations). Darryl Shibata has collaborated with scholars based in United States, United Kingdom and Finland. Frequent co-authors include Manuel Perucho, Norman Arnheim, Miguel A. Peinado, Sergei Malkhosyan, Yurij Ionov, Martin Wj, Simon Tavaré, Kathleen Forrester, John J. Martin and Concepción Almoguera. Their work appears in journals such as Proceedings of the National Academy of Sciences, Blood, American Journal Of Pathology, Cancer Research and Carcinogenesis.

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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