Song‐Hai Shi

7.5k total citations · 2 hit papers
56 papers, 5.6k citations indexed

About

Song‐Hai Shi is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Developmental Neuroscience. According to data from OpenAlex, Song‐Hai Shi has authored 56 papers receiving a total of 5.6k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Cellular and Molecular Neuroscience, 29 papers in Molecular Biology and 25 papers in Developmental Neuroscience. Recurrent topics in Song‐Hai Shi's work include Neuroscience and Neuropharmacology Research (26 papers), Neurogenesis and neuroplasticity mechanisms (25 papers) and Axon Guidance and Neuronal Signaling (13 papers). Song‐Hai Shi is often cited by papers focused on Neuroscience and Neuropharmacology Research (26 papers), Neurogenesis and neuroplasticity mechanisms (25 papers) and Axon Guidance and Neuronal Signaling (13 papers). Song‐Hai Shi collaborates with scholars based in United States, China and United Kingdom. Song‐Hai Shi's co-authors include Roberto Malinow, Yasunori Hayashi, Lily Yeh Jan, Yuh Nung Jan, José A. Esteban, Shahid Zaman, Ronald S. Petralia, Karel Svoboda, Robert J. Wenthold and Ronald S. Bultje and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Song‐Hai Shi

56 papers receiving 5.5k citations

Hit Papers

Rapid Spine Delivery and Redistribution of AMPA Receptors... 1999 2026 2008 2017 1999 2001 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Song‐Hai Shi United States 32 3.3k 3.3k 1.2k 1.1k 1.1k 56 5.6k
Guillermina López‐Bendito Spain 36 3.4k 1.0× 2.0k 0.6× 1.6k 1.3× 1.1k 1.0× 773 0.7× 66 5.0k
Constanze I. Seidenbecher Germany 41 2.6k 0.8× 2.3k 0.7× 541 0.4× 1.1k 1.0× 1.6k 1.4× 91 5.4k
Joseph J. LoTurco United States 41 2.5k 0.7× 2.9k 0.9× 1.7k 1.4× 1.0k 0.9× 601 0.6× 91 6.3k
Takuji Iwasato Japan 34 2.4k 0.7× 1.8k 0.5× 832 0.7× 820 0.7× 506 0.5× 65 4.1k
María E. Rubio United States 36 2.9k 0.9× 2.9k 0.9× 1.3k 1.1× 853 0.8× 431 0.4× 73 5.5k
Simon Hippenmeyer Austria 32 1.3k 0.4× 2.6k 0.8× 1.1k 0.9× 537 0.5× 609 0.6× 66 4.4k
Denis Jabaudon Switzerland 32 1.9k 0.6× 2.0k 0.6× 1.0k 0.8× 811 0.7× 287 0.3× 66 4.0k
Deanna L. Benson United States 40 3.5k 1.1× 2.7k 0.8× 788 0.6× 683 0.6× 1.1k 1.0× 96 5.3k
Andrés Buonanno United States 45 3.1k 0.9× 4.3k 1.3× 507 0.4× 697 0.6× 604 0.6× 95 6.5k
Goichi Miyoshi United States 24 2.3k 0.7× 1.9k 0.6× 1.3k 1.1× 1.1k 1.0× 243 0.2× 29 4.1k

Countries citing papers authored by Song‐Hai Shi

Since Specialization
Citations

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

Fields of papers citing papers by Song‐Hai Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Song‐Hai Shi. 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 Song‐Hai Shi. The network helps show where Song‐Hai Shi may publish in the future.

Co-authorship network of co-authors of Song‐Hai Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Song‐Hai Shi. A scholar is included among the top collaborators of Song‐Hai Shi 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 Song‐Hai Shi. Song‐Hai Shi 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, Bingqian, Jingjing Guo, Jiesi Feng, et al.. (2023). Plug-and-play fiber-optic sensors based on engineered cells for neurochemical monitoring at high specificity in freely moving animals. Science Advances. 9(22). eadg0218–eadg0218. 17 indexed citations
2.
Wang, Xiaoxiao, Si Zhang, Pingping Dong, et al.. (2021). MRCKβ links Dasm1 to actin rearrangements to promote dendrite development. Journal of Biological Chemistry. 296. 100730–100730. 3 indexed citations
3.
Yang, Jiajun, et al.. (2021). Centrosome regulation and function in mammalian cortical neurogenesis. Current Opinion in Neurobiology. 69. 256–266. 9 indexed citations
4.
Shao, Wei, Jiajun Yang, Ming He, et al.. (2020). Centrosome anchoring regulates progenitor properties and cortical formation. Nature. 580(7801). 106–112. 68 indexed citations
5.
Yang, Lin, et al.. (2020). Behavior and lineage progression of neural progenitors in the mammalian cortex. Current Opinion in Neurobiology. 66. 144–157. 34 indexed citations
6.
Shen, Zhongfu, et al.. (2018). Progressive divisions of multipotent neural progenitors generate late-born chandelier cells in the neocortex. Nature Communications. 9(1). 4595–4595. 12 indexed citations
7.
Sudarov, Anamaria, Xin‐Jun Zhang, Eve LoCastro, et al.. (2017). Mature Hippocampal Neurons Require LIS1 for Synaptic Integrity: Implications for Cognition. Biological Psychiatry. 83(6). 518–529. 11 indexed citations
8.
Zhang, Xin‐Jun, et al.. (2016). Vascular Influence on Ventral Telencephalic Progenitors and Neocortical Interneuron Production. Developmental Cell. 36(6). 624–638. 63 indexed citations
9.
Insolera, Ryan, Hisham Bazzi, Wei Shao, Kathryn V. Anderson, & Song‐Hai Shi. (2014). Cortical neurogenesis in the absence of centrioles. Nature Neuroscience. 17(11). 1528–1535. 140 indexed citations
10.
Gao, Peng, Maria Pia Postiglione, Teresa G. Krieger, et al.. (2014). Deterministic Progenitor Behavior and Unitary Production of Neurons in the Neocortex. Cell. 159(4). 775–788. 306 indexed citations
11.
Xu, Huatai, Zhi Han, Peng Gao, et al.. (2014). Distinct Lineage-Dependent Structural and Functional Organization of the Hippocampus. Cell. 157(7). 1552–1564. 57 indexed citations
12.
Wei, Shi, et al.. (2014). Clonal origins of neocortical interneurons. Current Opinion in Neurobiology. 26. 125–131. 8 indexed citations
13.
Piao, Jinghua, Lei Niu, Yosif Ganat, et al.. (2013). Specification of Functional Cranial Placode Derivatives from Human Pluripotent Stem Cells. Cell Reports. 5(5). 1387–1402. 79 indexed citations
14.
Chen, Jia, Hang Shi, Michelle Wei, et al.. (2012). Regulation of Microtubule Stability and Organization by Mammalian Par3 in Specifying Neuronal Polarity. Developmental Cell. 24(1). 26–40. 65 indexed citations
15.
Li, Ye, Hui Lü, Pei‐Lin Cheng, et al.. (2012). Clonally related visual cortical neurons show similar stimulus feature selectivity. Nature. 486(7401). 118–121. 173 indexed citations
16.
Viotti, Manuel, Lei Niu, Song‐Hai Shi, & Anna‐Katerina Hadjantonakis. (2012). Role of the Gut Endoderm in Relaying Left-Right Patterning in Mice. PLoS Biology. 10(3). e1001276–e1001276. 45 indexed citations
17.
Maroof, Asif, et al.. (2010). Prospective Isolation of Cortical Interneuron Precursors from Mouse Embryonic Stem Cells. Journal of Neuroscience. 30(13). 4667–4675. 71 indexed citations
18.
Insolera, Ryan, et al.. (2010). Par proteins and neuronal polarity. Developmental Neurobiology. 71(6). 483–494. 29 indexed citations
19.
Shi, Song‐Hai, Jernej Ule, Matteo Ruggiu, et al.. (2005). Common Molecular Pathways Mediate Long-Term Potentiation of Synaptic Excitation and Slow Synaptic Inhibition. Cell. 123(1). 105–118. 127 indexed citations
20.
Shi, Song‐Hai, Tong Cheng, Lily Yeh Jan, & Yuh Nung Jan. (2004). APC and GSK-3β Are Involved in mPar3 Targeting to the Nascent Axon and Establishment of Neuronal Polarity. Current Biology. 14(22). 2025–2032. 211 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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