Asuka Ota

406 total citations
9 papers, 321 citations indexed

About

Asuka Ota is a scholar working on Molecular Biology, Cell Biology and Surgery. According to data from OpenAlex, Asuka Ota has authored 9 papers receiving a total of 321 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 4 papers in Cell Biology and 3 papers in Surgery. Recurrent topics in Asuka Ota's work include Endoplasmic Reticulum Stress and Disease (3 papers), Pancreatic function and diabetes (3 papers) and Gene Regulatory Network Analysis (2 papers). Asuka Ota is often cited by papers focused on Endoplasmic Reticulum Stress and Disease (3 papers), Pancreatic function and diabetes (3 papers) and Gene Regulatory Network Analysis (2 papers). Asuka Ota collaborates with scholars based in United States and China. Asuka Ota's co-authors include Yibin Wang, Kyle M. Kovary, Robert Ahrends, Mary N. Teruel, Susan Vahebi, Peipei Ping, Chad M. Warren, R. John Solaro, Pieter P. de Tombe and Byung Ouk Park and has published in prestigious journals such as Science, Journal of Biological Chemistry and PLoS ONE.

In The Last Decade

Asuka Ota

9 papers receiving 319 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Asuka Ota United States	8	224	86	61	38	38	9	321
Alice Vallentin United States	9	284 1.3×	74 0.9×	93 1.5×	67 1.8×	44 1.2×	9	428
Juniper K. Pennypacker United States	10	283 1.3×	33 0.4×	36 0.6×	24 0.6×	66 1.7×	10	399
Hyun Sub Hwang United States	11	267 1.2×	37 0.4×	54 0.9×	16 0.4×	60 1.6×	18	415
Xuejun Jiang China	11	144 0.6×	130 1.5×	51 0.8×	34 0.9×	24 0.6×	31	328
Oscar E. Reyes Gaido United States	5	196 0.9×	85 1.0×	20 0.3×	12 0.3×	20 0.5×	7	279
Sarah Gora Canada	7	249 1.1×	27 0.3×	52 0.9×	35 0.9×	29 0.8×	11	341
Sarah L. Wynia‐Smith United States	11	222 1.0×	55 0.6×	18 0.3×	41 1.1×	63 1.7×	18	359
Kai‐Ting Huang United States	7	257 1.1×	23 0.3×	50 0.8×	46 1.2×	59 1.6×	12	355
Mikiko Kishi Japan	10	275 1.2×	19 0.2×	81 1.3×	19 0.5×	42 1.1×	26	415
Huang Tigang China	8	182 0.8×	83 1.0×	208 3.4×	11 0.3×	27 0.7×	13	388

Countries citing papers authored by Asuka Ota

Since Specialization

Citations

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

Fields of papers citing papers by Asuka Ota

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Asuka Ota

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

All Works

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9 of 9 papers shown

1.

Ota, Asuka, Kyle M. Kovary, Robert Ahrends, et al.. (2015). Using SRM-MS to quantify nuclear protein abundance differences between adipose tissue depots of insulin-resistant mice. Journal of Lipid Research. 56(5). 1068–1078. 11 indexed citations

2.

Ren, Shuxun, Gang Lü, Asuka Ota, et al.. (2014). IRE1 Phosphatase PP2Ce Regulates Adaptive ER Stress Response in the Postpartum Mammary Gland. PLoS ONE. 9(11). e111606–e111606. 15 indexed citations

3.

Teruel, Mary N., Robert Ahrends, Asuka Ota, Kyle M. Kovary, & Byung Ouk Park. (2014). Controlling low rates of terminal cell differentiation through noise and ultra‐high feedback (981.1). The FASEB Journal. 28(S1). 1 indexed citations

4.

Ahrends, Robert, Asuka Ota, Kyle M. Kovary, et al.. (2014). Controlling low rates of cell differentiation through noise and ultrahigh feedback. Science. 344(6190). 1384–1389. 68 indexed citations

5.

Lü, Gang, Asuka Ota, Shuxun Ren, et al.. (2013). PPM1l encodes an inositol requiring-protein 1 (IRE1) specific phosphatase that regulates the functional outcome of the ER stress response. Molecular Metabolism. 2(4). 405–416. 28 indexed citations

6.

Ota, Asuka & Yibin Wang. (2011). Cdc37/Hsp90 Protein-mediated Regulation of IRE1α Protein Activity in Endoplasmic Reticulum Stress Response and Insulin Synthesis in INS-1 Cells. Journal of Biological Chemistry. 287(9). 6266–6274. 34 indexed citations

7.

Ota, Asuka, Jun Zhang, Peipei Ping, Jiahuai Han, & Yibin Wang. (2010). Specific Regulation of Noncanonical p38α Activation by Hsp90-Cdc37 Chaperone Complex in Cardiomyocyte. Circulation Research. 106(8). 1404–1412. 47 indexed citations

8.

Vahebi, Susan, Asuka Ota, Manxiang Li, et al.. (2007). p38-MAPK Induced Dephosphorylation of α-Tropomyosin Is Associated With Depression of Myocardial Sarcomeric Tension and ATPase Activity. Circulation Research. 100(3). 408–415. 81 indexed citations

9.

Ota, Asuka, William Foster, Bin Zhang, et al.. (2005). Distinct gene expression profiles in adult mouse heart following targeted MAP kinase activation. Physiological Genomics. 25(1). 50–59. 36 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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