Can Liu

21 total papers · 639 total citations
14 papers, 427 citations indexed

About

Can Liu is a scholar working on Cellular and Molecular Neuroscience, Biomaterials and Pathology and Forensic Medicine. According to data from OpenAlex, Can Liu has authored 14 papers receiving a total of 427 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Cellular and Molecular Neuroscience, 3 papers in Biomaterials and 2 papers in Pathology and Forensic Medicine. Recurrent topics in Can Liu's work include Nerve injury and regeneration (5 papers), Neuroscience and Neuropharmacology Research (4 papers) and Electrospun Nanofibers in Biomedical Applications (3 papers). Can Liu is often cited by papers focused on Nerve injury and regeneration (5 papers), Neuroscience and Neuropharmacology Research (4 papers) and Electrospun Nanofibers in Biomedical Applications (3 papers). Can Liu collaborates with scholars based in China, United Kingdom and Japan. Can Liu's co-authors include Chengyun Ning, Lei Zhou, Lei Fan, Pengfei Guan, Yian Luo, Huiquan Wen, Guoxin Tan, Shihuan Wang, Dafu Chen and Limin Rong and has published in prestigious journals such as Nature Communications, NeuroImage and Journal of Affective Disorders.

In The Last Decade

Can Liu

13 papers receiving 425 citations

Author Peers

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

Author						Papers	Cites
Can Liu	179	137	97	74	73	14	427
Agnes E. Haggerty	257 1.4×	91 0.7×	120 1.2×	138 1.9×	185 2.5×	15	466
Christine Mouffle	227 1.3×	49 0.4×	50 0.5×	82 1.1×	199 2.7×	12	485
Penghui Fan	154 0.9×	138 1.0×	98 1.0×	35 0.5×	21 0.3×	32	428
Vincent Pertici	80 0.4×	110 0.8×	121 1.2×	65 0.9×	42 0.6×	15	401
Yousef Sadeghi	119 0.7×	43 0.3×	51 0.5×	91 1.2×	37 0.5×	29	432
Maria José Simões	194 1.1×	67 0.5×	96 1.0×	105 1.4×	39 0.5×	17	447
Sajad Hassanzadeh	84 0.5×	135 1.0×	172 1.8×	68 0.9×	55 0.8×	26	409
Courtney M. Dumont	256 1.4×	141 1.0×	80 0.8×	98 1.3×	148 2.0×	21	482
Korosh Mansoori	139 0.8×	164 1.2×	118 1.2×	107 1.4×	13 0.2×	25	412
Valerie K. Haftel	321 1.8×	211 1.5×	213 2.2×	117 1.6×	25 0.3×	7	486

Countries citing papers authored by Can Liu

Since Specialization

Citations

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

Fields of papers citing papers by Can Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Can Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Can Liu. A scholar is included among the top collaborators of Can Liu 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 Can Liu. Can Liu 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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