Ulka Vijapurkar

563 total citations
9 papers, 418 citations indexed

About

Ulka Vijapurkar is a scholar working on Molecular Biology, Oncology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Ulka Vijapurkar has authored 9 papers receiving a total of 418 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 4 papers in Oncology and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Ulka Vijapurkar's work include HER2/EGFR in Cancer Research (3 papers), Protein Kinase Regulation and GTPase Signaling (2 papers) and Cell Adhesion Molecules Research (2 papers). Ulka Vijapurkar is often cited by papers focused on HER2/EGFR in Cancer Research (3 papers), Protein Kinase Regulation and GTPase Signaling (2 papers) and Cell Adhesion Molecules Research (2 papers). Ulka Vijapurkar collaborates with scholars based in United States, France and Singapore. Ulka Vijapurkar's co-authors include John G. Koland, Steven H. Green, Marlan R. Hansen, Nathan J. Hellyer, Hong‐Hee Kim, Kunrong Cheng, H. Jeffrey Lawrence, Corey Largman, Wei Wang and Ronald Herbst and has published in prestigious journals such as Journal of Biological Chemistry, Blood and Molecular and Cellular Biology.

In The Last Decade

Ulka Vijapurkar

9 papers receiving 412 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ulka Vijapurkar United States	7	265	158	69	59	54	9	418
William M. Schopperle United States	9	359 1.4×	70 0.4×	27 0.4×	20 0.3×	111 2.1×	15	488
Gaël Manès France	16	493 1.9×	29 0.2×	41 0.6×	18 0.3×	111 2.1×	30	587
Ilya Leskov United States	8	406 1.5×	103 0.7×	56 0.8×	11 0.2×	196 3.6×	18	638
Seung‐Ryul Kim South Korea	8	369 1.4×	42 0.3×	15 0.2×	12 0.2×	59 1.1×	14	550
Olaf Hardt Germany	12	319 1.2×	250 1.6×	64 0.9×	7 0.1×	46 0.9×	33	616
Hilary J. Gower United Kingdom	9	535 2.0×	58 0.4×	51 0.7×	14 0.2×	195 3.6×	13	751
B.F.D. Ghrist United States	9	317 1.2×	85 0.5×	103 1.5×	5 0.1×	175 3.2×	12	659
Mariateresa Pizzo Italy	15	610 2.3×	23 0.1×	44 0.6×	24 0.4×	51 0.9×	20	737
Breann L. Wolfe United States	5	411 1.6×	54 0.3×	21 0.3×	8 0.1×	119 2.2×	6	654

Countries citing papers authored by Ulka Vijapurkar

Since Specialization

Citations

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

Fields of papers citing papers by Ulka Vijapurkar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ulka Vijapurkar

This figure shows the co-authorship network connecting the top 25 collaborators of Ulka Vijapurkar. A scholar is included among the top collaborators of Ulka Vijapurkar 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 Ulka Vijapurkar. Ulka Vijapurkar 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

Gnad, Florian, Jeffrey J. Wallin, Kyle A. Edgar, et al.. (2016). Quantitative phosphoproteomic analysis of the PI3K‐regulated signaling network. PROTEOMICS. 16(14). 1992–1997. 4 indexed citations

Vijapurkar, Ulka, Liliane Robillard, Michael Degtyarev, et al.. (2012). mTOR kinase inhibitor potentiates apoptosis of PI3K and MEK inhibitors in diagnostically defined subpopulations. Cancer Letters. 326(2). 168–175. 6 indexed citations

Vijapurkar, Ulka, Wei Wang, & Ronald Herbst. (2007). Potentiation of Kinesin Spindle Protein Inhibitor–Induced Cell Death by Modulation of Mitochondrial and Death Receptor Apoptotic Pathways. Cancer Research. 67(1). 237–245. 30 indexed citations

Vijapurkar, Ulka, Neal Fischbach, Wei-Fang Shen, et al.. (2004). Protein Kinase C-Mediated Phosphorylation of the Leukemia-Associated HOXA9 Protein Impairs Its DNA Binding Ability and Induces Myeloid Differentiation. Molecular and Cellular Biology. 24(9). 3827–3837. 39 indexed citations

Dorsam, Sheri T., Glenn Dorsam, Mika K. Derynck, et al.. (2003). The transcriptome of the leukemogenic homeoprotein HOXA9 in human hematopoietic cells. Blood. 103(5). 1676–1684. 72 indexed citations

Vijapurkar, Ulka, et al.. (2003). Roles of mitogen-activated protein kinase and phosphoinositide 3′-kinase in ErbB2/ErbB3 coreceptor-mediated heregulin signaling☆. Experimental Cell Research. 284(2). 289–300. 44 indexed citations

Hansen, Marlan R., Ulka Vijapurkar, John G. Koland, & Steven H. Green. (2001). Reciprocal signaling between spiral ganglion neurons and Schwann cells involves neuregulin and neurotrophins. Hearing Research. 161(1-2). 87–98. 94 indexed citations

Vijapurkar, Ulka, Kunrong Cheng, & John G. Koland. (1998). Mutation of a Shc Binding Site Tyrosine Residue in ErbB3/HER3 Blocks Heregulin-dependent Activation of Mitogen-activated Protein Kinase. Journal of Biological Chemistry. 273(33). 20996–21002. 43 indexed citations

Kim, Hong‐Hee, et al.. (1998). Signal transduction by epidermal growth factor and heregulin via the kinase-deficient ErbB3 protein. Biochemical Journal. 334(1). 189–195. 86 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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