Ilya V. Pyko

855 total citations
9 papers, 686 citations indexed

About

Ilya V. Pyko is a scholar working on Molecular Biology, Pathology and Forensic Medicine and Cellular and Molecular Neuroscience. According to data from OpenAlex, Ilya V. Pyko has authored 9 papers receiving a total of 686 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 2 papers in Pathology and Forensic Medicine and 2 papers in Cellular and Molecular Neuroscience. Recurrent topics in Ilya V. Pyko's work include Cancer Mechanisms and Therapy (2 papers), Wnt/β-catenin signaling in development and cancer (2 papers) and MicroRNA in disease regulation (2 papers). Ilya V. Pyko is often cited by papers focused on Cancer Mechanisms and Therapy (2 papers), Wnt/β-catenin signaling in development and cancer (2 papers) and MicroRNA in disease regulation (2 papers). Ilya V. Pyko collaborates with scholars based in Japan, China and Bulgaria. Ilya V. Pyko's co-authors include Mitsutoshi Nakada, Yutaka Hayashi, Lei Teng, Jun‐ichiro Hamada, Takuya Watanabe, Daisuke Kita, Toshinari Minamoto, Takahiro Domoto, Takuya Furuta and Masahiro Uehara and has published in prestigious journals such as British Journal of Cancer, Carcinogenesis and Hippocampus.

In The Last Decade

Ilya V. Pyko

9 papers receiving 678 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ilya V. Pyko Japan	9	388	174	148	128	114	9	686
Xuejiao Liu China	20	595 1.5×	160 0.9×	213 1.4×	87 0.7×	122 1.1×	40	938
Linda Sleire Norway	10	355 0.9×	135 0.8×	198 1.3×	118 0.9×	49 0.4×	13	689
Lina Leiss Norway	11	386 1.0×	182 1.0×	196 1.3×	139 1.1×	69 0.6×	20	810
Luiz Gustavo Dubois Brazil	16	423 1.1×	308 1.8×	188 1.3×	73 0.6×	122 1.1×	20	889
Youxin Zhou China	19	595 1.5×	165 0.9×	220 1.5×	88 0.7×	99 0.9×	60	1.1k
Ignacio Niechi Chile	16	480 1.2×	174 1.0×	202 1.4×	51 0.4×	58 0.5×	29	741
Niyati Jhaveri United States	12	302 0.8×	182 1.0×	129 0.9×	66 0.5×	109 1.0×	15	636
Kui Zhai China	16	462 1.2×	163 0.9×	162 1.1×	80 0.6×	72 0.6×	30	833
Brian Golbourn Canada	14	334 0.9×	167 1.0×	125 0.8×	56 0.4×	120 1.1×	24	676
Shengping Yu China	16	444 1.1×	200 1.1×	256 1.7×	92 0.7×	47 0.4×	45	883

Countries citing papers authored by Ilya V. Pyko

Since Specialization

Citations

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

Fields of papers citing papers by Ilya V. Pyko

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ilya V. Pyko. 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 Ilya V. Pyko. The network helps show where Ilya V. Pyko may publish in the future.

Co-authorship network of co-authors of Ilya V. Pyko

This figure shows the co-authorship network connecting the top 25 collaborators of Ilya V. Pyko. A scholar is included among the top collaborators of Ilya V. Pyko 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 Ilya V. Pyko. Ilya V. Pyko 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

Nakada, Mitsutoshi, Daisuke Kita, Lei Teng, et al.. (2020). Receptor Tyrosine Kinases: Principles and Functions in Glioma Invasion. Advances in experimental medicine and biology. 1202. 151–178. 28 indexed citations

Domoto, Takahiro, Ilya V. Pyko, Takuya Furuta, et al.. (2016). Glycogen synthase kinase‐3β is a pivotal mediator of cancer invasion and resistance to therapy. Cancer Science. 107(10). 1363–1372. 132 indexed citations

Domoto, Takahiro, Takuya Furuta, Hemragul Sabit, et al.. (2014). Glycogen Synthase Kinase 3β Sustains Invasion of Glioblastoma via the Focal Adhesion Kinase, Rac1, and c-Jun N-Terminal Kinase-Mediated Pathway. Molecular Cancer Therapeutics. 14(2). 564–574. 41 indexed citations

Pyko, Ilya V., Mitsutoshi Nakada, Hemragul Sabit, et al.. (2013). Glycogen synthase kinase 3β inhibition sensitizes human glioblastoma cells to temozolomide by affecting O 6 -methylguanine DNA methyltransferase promoter methylation via c-Myc signaling. Carcinogenesis. 34(10). 2206–2217. 63 indexed citations

Nakada, Mitsutoshi, Daisuke Kita, Lei Teng, et al.. (2012). Receptor Tyrosine Kinases: Principles and Functions in Glioma Invasion. Advances in experimental medicine and biology. 986. 143–170. 46 indexed citations

Teng, Lei, et al.. (2011). Silencing of ferrochelatase enhances 5-aminolevulinic acid-based fluorescence and photodynamic therapy efficacy. British Journal of Cancer. 104(5). 798–807. 139 indexed citations

Nakada, Mitsutoshi, Daisuke Kita, Takuya Watanabe, et al.. (2011). Aberrant Signaling Pathways in Glioma. Cancers. 3(3). 3242–3278. 181 indexed citations

Hisha, Hiroko, Yasushi Adachi, Susumu Ikehara, et al.. (2010). Bone marrow-derived stromal cells can express neuronal markers by DHA/GPR40 signaling.. PubMed. 4(3). 119–29. 12 indexed citations

Pyko, Ilya V., et al.. (2009). Expression of fatty acid‐binding proteins in adult hippocampal neurogenic niche of postischemic monkeys. Hippocampus. 21(2). 162–171. 44 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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