Jon Akutagawa

613 total citations
12 papers, 432 citations indexed

About

Jon Akutagawa is a scholar working on Hematology, Molecular Biology and Genetics. According to data from OpenAlex, Jon Akutagawa has authored 12 papers receiving a total of 432 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Hematology, 7 papers in Molecular Biology and 5 papers in Genetics. Recurrent topics in Jon Akutagawa's work include Acute Myeloid Leukemia Research (7 papers), Chronic Lymphocytic Leukemia Research (3 papers) and Chronic Myeloid Leukemia Treatments (3 papers). Jon Akutagawa is often cited by papers focused on Acute Myeloid Leukemia Research (7 papers), Chronic Lymphocytic Leukemia Research (3 papers) and Chronic Myeloid Leukemia Treatments (3 papers). Jon Akutagawa collaborates with scholars based in United States, Sweden and Argentina. Jon Akutagawa's co-authors include Benjamin S. Braun, Kevin Shannon, Jennifer Lauchle, Tiffany Chang, Mignon L. Loh, Jin Xu, Scott C. Kogan, Matthew F. Gorman, Wan Xing Hong and Natalya Lyubynska and has published in prestigious journals such as Journal of Clinical Investigation, Nature Communications and Blood.

In The Last Decade

Jon Akutagawa

12 papers receiving 422 citations

Peers

Jon Akutagawa

MB

HEMAT

GENET

ONCOL

PHEOH

Gregor von Levetzow United States

Michelle Y. Doral United States

Thelma R. Tennant United States

Oreste Villani Italy

Berna Beverloo Netherlands

Doan Le Canada

Marian Stevens‐Kroef Netherlands

M Flactif France

Cathy Quelen France

Sonya H.L. Lam Canada

Gregor von Levetzow United States

Jon Akutagawa

212 ×0.9

MB

132 ×0.6

HEMAT

88 ×0.7

GENET

75 ×0.8

ONCOL

120 ×1.9

PHEOH

Citations per year, relative to Jon Akutagawa Jon Akutagawa (= 1×) peers Gregor von Levetzow

Countries citing papers authored by Jon Akutagawa

Since Specialization

Citations

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

Fields of papers citing papers by Jon Akutagawa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jon Akutagawa

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

All Works

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12 of 12 papers shown

1.

Díaz-Flores, Ernesto, Kyle Beckman, Kara L. Davis, et al.. (2019). Bcl-2 Is a Therapeutic Target for Hypodiploid B-Lineage Acute Lymphoblastic Leukemia. Cancer Research. 79(9). 2339–2351. 49 indexed citations

2.

Stieglitz, Elliot, Tali Mazor, Adam B. Olshen, et al.. (2017). Genome-wide DNA methylation is predictive of outcome in juvenile myelomonocytic leukemia. Nature Communications. 8(1). 2127–2127. 60 indexed citations

3.

Akutagawa, Jon, Teng Huang, Tiffany Chang, et al.. (2016). Targeting the PI3K/Akt pathway in murine MDS/MPN driven by hyperactive Ras. Leukemia. 30(6). 1335–1343. 28 indexed citations

4.

Díaz-Flores, Ernesto, Kyle Beckman, Kara L. Davis, et al.. (2016). BCL-2, a Therapeutic Target for High Risk Hypodiploid B-Cell Acute Lymphoblastic Leukemia. Blood. 128(22). 280–280. 5 indexed citations

5.

Akutagawa, Jon, et al.. (2015). Negative Feedback By Dusp6 Modulates Myeloproliferation Induced By Oncogenic Nras. Blood. 126(23). 1256–1256. 1 indexed citations

6.

Stieglitz, Elliot, Camille Troup, John Haliburton, et al.. (2014). Subclonal mutations in SETBP1 confer a poor prognosis in juvenile myelomonocytic leukemia. Blood. 125(3). 516–524. 48 indexed citations

7.

Stieglitz, Elliot, Camille Troup, Eric D. Chow, et al.. (2014). Subclonal Mutations in SETBP1 Predict Relapse in Juvenile Myelomonocytic Leukemia. Blood. 124(21). 410–410. 1 indexed citations

8.

Díaz-Flores, Ernesto, Hana L. Goldschmidt, Philippe Depeille, et al.. (2013). PLC-γ and PI3K Link Cytokines to ERK Activation in Hematopoietic Cells with Normal and OncogenicKras. Science Signaling. 6(304). ra105–ra105. 14 indexed citations

9.

Chang, Tiffany, Jin Xu, Jon Akutagawa, et al.. (2012). Sustained MEK inhibition abrogates myeloproliferative disease in Nf1 mutant mice. Journal of Clinical Investigation. 123(1). 335–339. 101 indexed citations

10.

Akutagawa, Jon, Monique Dail, Lori S. Friedman, et al.. (2012). The PI3K Inhibitor GDC-0941 Attenuates Disease in a KrasG12D Mouse Model of CMML and JMML.. Blood. 120(21). 2862–2862. 1 indexed citations

11.

Lyubynska, Natalya, Matthew F. Gorman, Jennifer Lauchle, et al.. (2011). A MEK Inhibitor Abrogates Myeloproliferative Disease in Kras Mutant Mice. Science Translational Medicine. 3(76). 76ra27–76ra27. 71 indexed citations

12.

Stéphan, Jean-Philippe, Pamela Chan, Chien Lee, et al.. (2008). Anti-CD22-MCC-DM1 and MC-MMAF Conjugates: Impact of Assay Format on Pharmacokinetic Parameters Determination. Bioconjugate Chemistry. 19(8). 1673–1683. 53 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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