Yali V. Zhang

1.2k total citations
11 papers, 827 citations indexed

About

Yali V. Zhang is a scholar working on Cellular and Molecular Neuroscience, Nutrition and Dietetics and Insect Science. According to data from OpenAlex, Yali V. Zhang has authored 11 papers receiving a total of 827 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cellular and Molecular Neuroscience, 4 papers in Nutrition and Dietetics and 4 papers in Insect Science. Recurrent topics in Yali V. Zhang's work include Neurobiology and Insect Physiology Research (9 papers), Insect Utilization and Effects (4 papers) and Biochemical Analysis and Sensing Techniques (4 papers). Yali V. Zhang is often cited by papers focused on Neurobiology and Insect Physiology Research (9 papers), Insect Utilization and Effects (4 papers) and Biochemical Analysis and Sensing Techniques (4 papers). Yali V. Zhang collaborates with scholars based in United States, China and Japan. Yali V. Zhang's co-authors include Craig Montell, Emily R. Liman, Jinfei D Ni, Wei L. Shen, J. Mack, Ting‐Wei Mi, Christopher M. Lee, Peihua Jiang, Chanyi Lu and Robert F. Margolskee and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Yali V. Zhang

11 papers receiving 822 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yali V. Zhang United States	8	541	333	248	238	190	11	827
Yong Taek Jeong South Korea	10	411 0.8×	147 0.4×	218 0.9×	89 0.4×	149 0.8×	24	533
Alexander A. Nikonov United States	13	356 0.7×	174 0.5×	157 0.6×	279 1.2×	98 0.5×	19	570
Elaine C. Chang United States	10	888 1.6×	117 0.4×	362 1.5×	298 1.3×	292 1.5×	11	1.1k
Aakanksha Singhvi United States	11	439 0.8×	122 0.4×	153 0.6×	97 0.4×	138 0.7×	22	744
Klemens F. Störtkuhl Germany	10	632 1.2×	63 0.2×	355 1.4×	211 0.9×	234 1.2×	11	715
Alexandre Widmer Canada	5	630 1.2×	67 0.2×	256 1.0×	151 0.6×	398 2.1×	6	736
Patricia Widmayer Germany	15	333 0.6×	528 1.6×	37 0.1×	496 2.1×	76 0.4×	23	934
Lina Ni United States	10	721 1.3×	74 0.2×	280 1.1×	163 0.7×	295 1.6×	17	934
Kirill Ukhanov United States	13	370 0.7×	168 0.5×	47 0.2×	286 1.2×	124 0.7×	32	587
George Gomez United States	15	295 0.5×	235 0.7×	130 0.5×	395 1.7×	78 0.4×	34	666

Countries citing papers authored by Yali V. Zhang

Since Specialization

Citations

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

Fields of papers citing papers by Yali V. Zhang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yali V. Zhang

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

All Works

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11 of 11 papers shown

Mi, Ting‐Wei, et al.. (2025). Harnessing Insect Chemosensory and Mechanosensory Receptors Involved in Feeding for Precision Pest Management. Life. 15(1). 110–110. 1 indexed citations

Mi, Ting‐Wei, J. Mack, Zhao‐Qian Teng, et al.. (2023). Alkaline taste sensation through the alkaliphile chloride channel in Drosophila. Nature Metabolism. 5(3). 466–480. 12 indexed citations

Lu, Chanyi, Xiaoli Lin, Minliang Zhou, et al.. (2022). RNF43/ZNRF3 negatively regulates taste tissue homeostasis and positively regulates dorsal lingual epithelial tissue homeostasis. Stem Cell Reports. 17(2). 369–383. 10 indexed citations

Lin, Xiaoli, Chanyi Lu, Weiwei Lei, et al.. (2021). Up-regulation of gasdermin C in mouse small intestine is associated with lytic cell death in enterocytes in worm-induced type 2 immunity. Proceedings of the National Academy of Sciences. 118(30). 48 indexed citations

Mack, J. & Yali V. Zhang. (2021). A Rapid Food-Preference Assay in <em>Drosophila</em>. Journal of Visualized Experiments. 2 indexed citations

Mi, Ting‐Wei, J. Mack, Christopher M. Lee, & Yali V. Zhang. (2021). Molecular and cellular basis of acid taste sensation in Drosophila. Nature Communications. 12(1). 3730–3730. 37 indexed citations

Mack, J. & Yali V. Zhang. (2021). A Rapid Food-Preference Assay in <em>Drosophila</em>. Journal of Visualized Experiments. 1 indexed citations

Zhang, Yali V., et al.. (2016). The Basis of Food Texture Sensation in Drosophila. Neuron. 91(4). 863–877. 86 indexed citations

Liman, Emily R., Yali V. Zhang, & Craig Montell. (2014). Peripheral Coding of Taste. Neuron. 81(5). 984–1000. 315 indexed citations

10.

Zhang, Yali V., et al.. (2013). Food experience–induced taste desensitization modulated by the Drosophila TRPL channel. Nature Neuroscience. 16(10). 1468–1476. 72 indexed citations

11.

Zhang, Yali V., Jinfei D Ni, & Craig Montell. (2013). The Molecular Basis for Attractive Salt-Taste Coding in Drosophila. Science. 340(6138). 1334–1338. 243 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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