Ting Li

105 total papers · 1.8k total citations
72 papers, 1.2k citations indexed

About

Ting Li is a scholar working on Cognitive Neuroscience, Molecular Biology and Computational Theory and Mathematics. According to data from OpenAlex, Ting Li has authored 72 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Cognitive Neuroscience, 19 papers in Molecular Biology and 16 papers in Computational Theory and Mathematics. Recurrent topics in Ting Li's work include Functional Brain Connectivity Studies (18 papers), Computational Drug Discovery Methods (14 papers) and Neural dynamics and brain function (10 papers). Ting Li is often cited by papers focused on Functional Brain Connectivity Studies (18 papers), Computational Drug Discovery Methods (14 papers) and Neural dynamics and brain function (10 papers). Ting Li collaborates with scholars based in China, United States and United Kingdom. Ting Li's co-authors include Weida Tong, Ruth Roberts, Sue Wharton, Shraddha Thakkar, Li Wang, Chunliang Feng, Zhichao Liu, Pengfei Xu, Zhichao Liu and Leihong Wu and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and NeuroImage.

In The Last Decade

Ting Li

67 papers receiving 1.2k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Ting Li	321	241	229	134	129	72	1.2k
Fredrik Jeppsson	70 0.2×	230 1.0×	176 0.8×	10 0.1×	114 0.9×	51	1.1k
Martin Vališ	113 0.4×	42 0.2×	266 1.2×	36 0.3×	50 0.4×	47	1.3k
Dakun Lai	339 1.1×	87 0.4×	247 1.1×	41 0.3×	128 1.0×	80	1.4k
Lisa E. Williams	574 1.8×	59 0.2×	156 0.7×	14 0.1×	273 2.1×	34	1.3k
John O’Gorman	53 0.2×	85 0.4×	185 0.8×	14 0.1×	62 0.5×	49	1.3k
Hiroki Tanaka	239 0.7×	17 0.1×	70 0.3×	27 0.2×	138 1.1×	102	1.0k
Xiaoyue Zhao	289 0.9×	22 0.1×	709 3.1×	44 0.3×	53 0.4×	43	1.4k
Michael Jablonski	85 0.3×	45 0.2×	123 0.5×	234 1.7×	114 0.9×	37	1.2k
Tal Golan	372 1.2×	19 0.1×	147 0.6×	22 0.2×	66 0.5×	37	1.1k
Andrew P. Owens	167 0.5×	48 0.2×	403 1.8×	16 0.1×	73 0.6×	51	1.5k

Countries citing papers authored by Ting Li

Since Specialization

Citations

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

Fields of papers citing papers by Ting Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ting Li

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

All Works

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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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