Runling Yang

2.4k total citations
23 papers, 1.7k citations indexed

About

Runling Yang is a scholar working on Cellular and Molecular Neuroscience, Genetics and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Runling Yang has authored 23 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Cellular and Molecular Neuroscience, 11 papers in Genetics and 10 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Runling Yang's work include Neurobiology and Insect Physiology Research (18 papers), Insect and Arachnid Ecology and Behavior (10 papers) and Animal Behavior and Reproduction (6 papers). Runling Yang is often cited by papers focused on Neurobiology and Insect Physiology Research (18 papers), Insect and Arachnid Ecology and Behavior (10 papers) and Animal Behavior and Reproduction (6 papers). Runling Yang collaborates with scholars based in United States, United Kingdom and Germany. Runling Yang's co-authors include Michael A. Simon, Lily Yeh Jan, Yuh Nung Jan, Helen McNeill, Ulrich Stern, Ernst Hafen, Jeffrey D. Axelrod, Dali Ma, Yang Xiang and Ruo He and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Runling Yang

23 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Runling Yang United States 18 858 604 486 381 309 23 1.7k
Takashi Koyama Denmark 24 997 1.2× 531 0.9× 446 0.9× 300 0.8× 181 0.6× 48 1.8k
Linda L. Restifo United States 25 1.4k 1.6× 954 1.6× 1.1k 2.2× 457 1.2× 180 0.6× 42 2.5k
Thomas O. Auer Switzerland 19 516 0.6× 771 1.3× 436 0.9× 194 0.5× 296 1.0× 29 1.5k
Burkhard Poeck Germany 21 917 1.1× 1.2k 2.0× 428 0.9× 235 0.6× 208 0.7× 27 2.0k
Rita Reifegerste Germany 11 775 0.9× 601 1.0× 318 0.7× 212 0.6× 218 0.7× 11 1.4k
Haojiang Luan United States 14 1.0k 1.2× 510 0.8× 365 0.8× 269 0.7× 102 0.3× 18 1.3k
W. Daniel Tracey United States 21 1.7k 2.0× 705 1.2× 481 1.0× 313 0.8× 259 0.8× 36 2.6k
Venkateswara R. Chintapalli United Kingdom 9 618 0.7× 861 1.4× 415 0.9× 162 0.4× 113 0.4× 11 1.6k
Florence Friggi‐Grelin France 9 1.5k 1.8× 327 0.5× 735 1.5× 512 1.3× 157 0.5× 9 1.8k
Rafael Fernández United States 15 1000 1.2× 940 1.6× 374 0.8× 139 0.4× 241 0.8× 26 2.3k

Countries citing papers authored by Runling Yang

Since Specialization
Citations

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

Fields of papers citing papers by Runling Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Runling Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Runling Yang. A scholar is included among the top collaborators of Runling Yang 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 Runling Yang. Runling Yang 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.
Zhou, Fangmin, A. Formozov, Federico Tenedini, et al.. (2021). A neuropeptidergic circuit gates selective escape behavior of Drosophila larvae. Current Biology. 32(1). 149–163.e8. 38 indexed citations
2.
3.
Stern, Ulrich, et al.. (2019). Learning a Spatial Task by Trial and Error in Drosophila. Current Biology. 29(15). 2517–2525.e5. 13 indexed citations
4.
Hu, Chun, Meike Petersen, Federico Tenedini, et al.. (2017). Sensory integration and neuromodulatory feedback facilitate Drosophila mechanonociceptive behavior. Nature Neuroscience. 20(8). 1085–1095. 76 indexed citations
5.
He, Ruo, et al.. (2016). High Throughput Assay to Examine Egg-Laying Preferences of Individual <em>Drosophila melanogaster</em>. Journal of Visualized Experiments. e53716–e53716. 12 indexed citations
6.
Guntur, Ananya, Pengyu Gu, Ruo He, et al.. (2016). H2O2-Sensitive Isoforms of Drosophila melanogaster TRPA1 Act in Bitter-Sensing Gustatory Neurons to Promote Avoidance of UV During Egg-Laying. Genetics. 205(2). 749–759. 23 indexed citations
7.
Gou, Bin, et al.. (2016). High Throughput Assay to Examine Egg-Laying Preferences of Individual <em>Drosophila melanogaster</em>. Journal of Visualized Experiments. 1 indexed citations
8.
Stern, Ulrich, et al.. (2015). Long-duration animal tracking in difficult lighting conditions. Scientific Reports. 5(1). 10432–10432. 7 indexed citations
9.
Yang, Runling, Ruo He, & Ulrich Stern. (2015). Behavioral and Circuit Basis of Sucrose Rejection byDrosophilaFemales in a Simple Decision-Making Task. Journal of Neuroscience. 35(4). 1396–1410. 25 indexed citations
10.
Stern, Ulrich, Ruo He, & Runling Yang. (2015). Analyzing animal behavior via classifying each video frame using convolutional neural networks. Scientific Reports. 5(1). 14351–14351. 40 indexed citations
11.
Guntur, Ananya, et al.. (2015). Drosophila TRPA1 isoforms detect UV light via photochemical production of H 2 O 2. Proceedings of the National Academy of Sciences. 112(42). E5753–61. 52 indexed citations
12.
Guntur, Ananya, et al.. (2014). Egg-Laying Demand Induces Aversion of UV Light in Drosophila Females. Current Biology. 24(23). 2797–2804. 43 indexed citations
13.
14.
Yuan, Quan, Yuanquan Song, Runling Yang, Lily Yeh Jan, & Yuh Nung Jan. (2013). Female contact modulates male aggression via a sexually dimorphic GABAergic circuit in Drosophila. Nature Neuroscience. 17(1). 81–88. 71 indexed citations
15.
Zhao, Xuesong, Runling Yang, & Michael A. Simon. (2013). The Drosophila Cadherin Fat Regulates Tissue Size and Planar Cell Polarity through Different Domains. PLoS ONE. 8(5). e62998–e62998. 17 indexed citations
16.
Yang, Runling, Sebastian Rumpf, Yang Xiang, et al.. (2009). Control of the Postmating Behavioral Switch in Drosophila Females by Internal Sensory Neurons. Neuron. 61(4). 519–526. 224 indexed citations
17.
Ma, Dali, Runling Yang, Helen McNeill, Michael A. Simon, & Jeffrey D. Axelrod. (2003). Fidelity in planar cell polarity signalling. Nature. 421(6922). 543–547. 267 indexed citations
18.
Yang, Runling, Michael A. Simon, & Helen McNeill. (1999). mirror controls planar polarity and equator formation through repression of fringe expression and through control of cell affinities. Development. 126(24). 5857–5866. 52 indexed citations
19.
McNeill, Helen, Runling Yang, Michael H. Brodsky, Josette M. Ungos, & Michael A. Simon. (1997). mirror encodes a novel PBX-class homeoprotein that functions in the definition of the dorsal-ventral border in the Drosophila eye.. Genes & Development. 11(8). 1073–1082. 153 indexed citations
20.
Stephens, Elizabeth, Jack A. Taylor, Norman Kaplan, et al.. (1994). Ethnic variation in the CYP2E1 gene: polymorphism analysis of 695 African-Americans, European-Americans and Taiwanese. Pharmacogenetics. 4(4). 185–192. 149 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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