Guang-Zhong Wang

540 total citations
9 papers, 352 citations indexed

About

Guang-Zhong Wang is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cognitive Neuroscience. According to data from OpenAlex, Guang-Zhong Wang has authored 9 papers receiving a total of 352 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 4 papers in Cellular and Molecular Neuroscience and 3 papers in Cognitive Neuroscience. Recurrent topics in Guang-Zhong Wang's work include Machine Learning in Bioinformatics (3 papers), Neural dynamics and brain function (3 papers) and Neuroscience and Neuropharmacology Research (2 papers). Guang-Zhong Wang is often cited by papers focused on Machine Learning in Bioinformatics (3 papers), Neural dynamics and brain function (3 papers) and Neuroscience and Neuropharmacology Research (2 papers). Guang-Zhong Wang collaborates with scholars based in United States, China and Australia. Guang-Zhong Wang's co-authors include Geneviève Konopka, Todd M. Preuss, Leslie Chen, Daniel H. Geschwind, Rui Luo, Jeremy Davis‐Turak, Fuying Gao, Kellen D. Winden, Michael C. Oldham and Tara Friedrich and has published in prestigious journals such as Nature Communications, Neuron and Bioinformatics.

In The Last Decade

Guang-Zhong Wang

8 papers receiving 348 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Guang-Zhong Wang United States	6	190	113	63	38	37	9	352
Nathalie Lemière France	10	164 0.9×	96 0.8×	112 1.8×	52 1.4×	36 1.0×	10	337
Ana Franco‐Villanueva United States	12	133 0.7×	65 0.6×	25 0.4×	29 0.8×	97 2.6×	23	475
BaDoi N. Phan United States	9	188 1.0×	52 0.5×	99 1.6×	28 0.7×	97 2.6×	23	351
Charles Kenworthy United States	8	158 0.8×	106 0.9×	33 0.5×	9 0.2×	32 0.9×	10	345
James W. Bogenpohl United States	10	237 1.2×	61 0.5×	142 2.3×	37 1.0×	218 5.9×	12	513
André O. White United States	11	217 1.1×	125 1.1×	68 1.1×	60 1.6×	166 4.5×	14	407
Katherine J. Sellers United Kingdom	10	138 0.7×	49 0.4×	138 2.2×	24 0.6×	85 2.3×	12	384
Efstathios B. Papachristos Netherlands	8	50 0.3×	152 1.3×	56 0.9×	32 0.8×	74 2.0×	10	340
Li Chin Wong United States	11	241 1.3×	53 0.5×	45 0.7×	23 0.6×	104 2.8×	17	443
Ariel Brewer United States	6	188 1.0×	33 0.3×	61 1.0×	37 1.0×	131 3.5×	8	314

Countries citing papers authored by Guang-Zhong Wang

Since Specialization

Citations

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

Fields of papers citing papers by Guang-Zhong Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guang-Zhong Wang. 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 Guang-Zhong Wang. The network helps show where Guang-Zhong Wang may publish in the future.

Co-authorship network of co-authors of Guang-Zhong Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Guang-Zhong Wang. A scholar is included among the top collaborators of Guang-Zhong Wang 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 Guang-Zhong Wang. Guang-Zhong Wang 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

1.

Lin, Qiaohong, Xian Du, Ying Liu, et al.. (2025). Anti-Müllerian hormone signalling sustains circadian homeostasis in zebrafish. Nature Communications. 16(1). 4359–4359.

2.

Sun, Jingjing, Shuo Yang, Xiaocui Zhang, et al.. (2020). Chromatin-Binding Protein PHF6 Regulates Activity-Dependent Transcriptional Networks to Promote Hunger Response. Cell Reports. 30(11). 3717–3728.e6. 6 indexed citations

3.

Berto, Stefano, et al.. (2017). Human Genomic Signatures of Brain Oscillations During Memory Encoding. Cerebral Cortex. 28(5). 1733–1748. 17 indexed citations

4.

Marini, Simone, et al.. (2017). Dscam1 web server: online prediction of Dscam1 self- and hetero-affinity. Bioinformatics. 33(12). 1879–1880. 1 indexed citations

5.

Wang, Guang-Zhong, T. Grant Belgard, Deng Mao, et al.. (2015). Correspondence between Resting-State Activity and Brain Gene Expression. Neuron. 88(4). 659–666. 92 indexed citations

6.

Wang, Guang-Zhong, Lei Shi, Nobuya Koike, et al.. (2015). Cycling Transcriptional Networks Optimize Energy Utilization on a Genome Scale. Cell Reports. 13(9). 1868–1880. 45 indexed citations

7.

Wang, Guang-Zhong & Geneviève Konopka. (2013). Decoding human gene expression signatures in the brain. Transcription. 4(3). 102–108. 7 indexed citations

8.

Konopka, Geneviève, Tara Friedrich, Jeremy Davis‐Turak, et al.. (2012). Human-Specific Transcriptional Networks in the Brain. Neuron. 75(4). 601–617. 182 indexed citations

9.

Wang, Guang-Zhong & Geneviève Konopka. (2012). Differential Functional Constraints on the Evolution of Postsynaptic Density Proteins in Neocortical Laminae. PLoS ONE. 7(6). e39686–e39686. 2 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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