Mariko Ishibashi

1.0k total citations
36 papers, 748 citations indexed

About

Mariko Ishibashi is a scholar working on Hematology, Molecular Biology and Oncology. According to data from OpenAlex, Mariko Ishibashi has authored 36 papers receiving a total of 748 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Hematology, 16 papers in Molecular Biology and 13 papers in Oncology. Recurrent topics in Mariko Ishibashi's work include Multiple Myeloma Research and Treatments (16 papers), Protein Degradation and Inhibitors (7 papers) and Peptidase Inhibition and Analysis (7 papers). Mariko Ishibashi is often cited by papers focused on Multiple Myeloma Research and Treatments (16 papers), Protein Degradation and Inhibitors (7 papers) and Peptidase Inhibition and Analysis (7 papers). Mariko Ishibashi collaborates with scholars based in Japan, United States and South Korea. Mariko Ishibashi's co-authors include Hideto Tamura, Koiti Inokuchi, Namiko Okuyama, Mariko Esumi, Koji Tamada, Takaji Wakita, Hidemi Takahashi, Kíyoyuki Ogata, Sakae Tanosaki and Haidong Dong and has published in prestigious journals such as Blood, Hepatology and Oncogene.

In The Last Decade

Mariko Ishibashi

33 papers receiving 742 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mariko Ishibashi Japan 13 322 309 297 282 77 36 748
Narelle Woodland Australia 9 276 0.9× 323 1.0× 165 0.6× 466 1.7× 39 0.5× 14 799
M. Brandely France 14 262 0.8× 164 0.5× 119 0.4× 326 1.2× 53 0.7× 36 760
Sunita Badola United States 9 233 0.7× 152 0.5× 207 0.7× 135 0.5× 65 0.8× 16 729
Edward L. Briercheck United States 11 206 0.6× 274 0.9× 241 0.8× 527 1.9× 44 0.6× 16 874
C. Gattringer Austria 12 408 1.3× 216 0.7× 342 1.2× 234 0.8× 129 1.7× 45 939
Christine‐Ivy Liacos Greece 12 91 0.3× 94 0.3× 178 0.6× 111 0.4× 76 1.0× 33 509
C Wheeler United States 12 343 1.1× 203 0.7× 209 0.7× 47 0.2× 67 0.9× 23 686
Minish Jain United States 14 459 1.4× 61 0.2× 258 0.9× 275 1.0× 41 0.5× 68 828
Paul M. Sondel United States 17 421 1.3× 237 0.8× 184 0.6× 767 2.7× 44 0.6× 41 1.1k
JF Rossi France 13 473 1.5× 461 1.5× 292 1.0× 319 1.1× 113 1.5× 22 927

Countries citing papers authored by Mariko Ishibashi

Since Specialization
Citations

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

Fields of papers citing papers by Mariko Ishibashi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mariko Ishibashi

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

All Works

20 of 20 papers shown
1.
Takyu, Sodai, Hideaki Tashima, M. Takahashi, et al.. (2025). A whole gamma imaging prototype for higher quantitative imaging of 89Zr-labeled antibodies in a tumor mouse model. Physics in Medicine and Biology. 70(2). 25012–25012. 1 indexed citations
2.
Sasaki, F, Mariko Ishibashi, Yoko Kawamoto, et al.. (2025). Inflammatory cytokine interleukin-18 prevents murine miscarriage by inducing appropriate inflammation. Scientific Reports. 15(1). 30765–30765.
3.
Sasaki, F, Minjung Cho, So Hee Dho, et al.. (2024). Gelsolin alleviates rheumatoid arthritis by negatively regulating NLRP3 inflammasome activation. Cell Death and Differentiation. 31(12). 1679–1694. 10 indexed citations
4.
Ishibashi, Mariko, Hiroshi Handa, Makoto Sasaki, et al.. (2023). The levels of serum soluble CD86 are correlated with the expression of CD86 variant 3 gene and are prognostic indicators in patients with myeloma. Experimental Hematology. 121. 38–47.e2. 2 indexed citations
5.
Ishibashi, Mariko, et al.. (2023). Current and Future PET Imaging for Multiple Myeloma. Life. 13(8). 1701–1701. 5 indexed citations
6.
7.
Ishibashi, Mariko, Junichi Yamamoto, Takumi Ito, et al.. (2021). Durvalumab Combined with Immunomodulatory Drugs (IMiD) Overcomes Suppression of Antitumor Responses due to IMiD-induced PD-L1 Upregulation on Myeloma Cells. Molecular Cancer Therapeutics. 20(7). 1283–1294. 1 indexed citations
8.
Ishibashi, Mariko, Atsushi Tatsuguchi, Takehito Igarashi, et al.. (2021). Clinicopathologic Characteristics and <i>A20</i> Mutation in Primary Thyroid Lymphoma. Journal of Nippon Medical School. 89(3). 301–308. 4 indexed citations
9.
Ishibashi, Mariko, Rimpei Morita, & Hideto Tamura. (2021). Immune Functions of Signaling Lymphocytic Activation Molecule Family Molecules in Multiple Myeloma. Cancers. 13(2). 279–279. 20 indexed citations
10.
Ishibashi, Mariko, et al.. (2020). The SLAMF3 rs509749 polymorphism correlates with malignant potential in multiple myeloma. Experimental Hematology. 90. 72–79. 3 indexed citations
11.
Ishibashi, Mariko, Hiromi Yamaguchi, Masahiko Sugitani, et al.. (2017). Contradictory intrahepatic immune responses activated in high-load hepatitis C virus livers compared with low-load livers. Archives of Virology. 163(4). 855–865. 1 indexed citations
12.
Ishibashi, Mariko, Hideto Tamura, Namiko Okuyama, et al.. (2016). Myeloma Drug Resistance Induced by Binding of Myeloma B7-H1 (PD-L1) to PD-1. Cancer Immunology Research. 4(9). 779–788. 78 indexed citations
13.
14.
Ishibashi, Mariko, et al.. (2014). CLEC4M-positive and CD81-negative Huh7 cells are not susceptible to JFH-1 HCVcc infection but mediate transinfection. Archives of Virology. 159(11). 2949–2955. 3 indexed citations
15.
Yamaguchi, Hiromi, Mariko Ishibashi, Kiyoshi Hasegawa, et al.. (2013). β-Glucuronidase is a suitable internal control gene for mRNA quantitation in pathophysiological and non-pathological livers. Experimental and Molecular Pathology. 95(2). 131–135. 12 indexed citations
16.
Ishibashi, Mariko, Hideto Tamura, & Kíyoyuki Ogata. (2011). Disease progression mechanism in myelodysplastic syndromes: Insight into the role of the microenvironment. Leukemia Research. 35(11). 1449–1452. 15 indexed citations
17.
Ishibashi, Mariko, Takaji Wakita, & Mariko Esumi. (2010). 2′,5′-Oligoadenylate synthetase-like gene highly induced by hepatitis C virus infection in human liver is inhibitory to viral replication in vitro. Biochemical and Biophysical Research Communications. 392(3). 397–402. 44 indexed citations
18.
Nakayama, Naomi, Kentaro Nakayama, Sabina Yeasmin, et al.. (2008). KRAS or BRAF mutation status is a useful predictor of sensitivity to MEK inhibition in ovarian cancer. British Journal of Cancer. 99(12). 2020–2028. 86 indexed citations
19.
Yeasmin, Sabina, Kentaro Nakayama, Mariko Ishibashi, et al.. (2008). Therapy-related myelodysplasia and acute myeloid leukemia following paclitaxel- and carboplatin-based chemotherapy in an ovarian cancer patient: a case report and literature review. International Journal of Gynecological Cancer. 18(6). 1371–1376. 20 indexed citations
20.
Morita, Noriko, et al.. (2002). Nationwide Description of Live Japanese Births by Day of the Week, Hour, and Location.. Journal of Epidemiology. 12(4). 330–335. 3 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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