Julia Liang

43 total papers · 784 total citations
36 papers, 579 citations indexed

About

Julia Liang is a scholar working on Molecular Biology, Computational Theory and Mathematics and Infectious Diseases. According to data from OpenAlex, Julia Liang has authored 36 papers receiving a total of 579 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 14 papers in Computational Theory and Mathematics and 11 papers in Infectious Diseases. Recurrent topics in Julia Liang's work include Computational Drug Discovery Methods (14 papers), SARS-CoV-2 and COVID-19 Research (10 papers) and RNA and protein synthesis mechanisms (5 papers). Julia Liang is often cited by papers focused on Computational Drug Discovery Methods (14 papers), SARS-CoV-2 and COVID-19 Research (10 papers) and RNA and protein synthesis mechanisms (5 papers). Julia Liang collaborates with scholars based in Australia, Denmark and Hong Kong. Julia Liang's co-authors include Andrew Hung, Tom C. Karagiannis, Eleni Pitsillou, Katherine Ververis, Ken Ng, Kah Wai Lim, Nancy B. Ray, Dimitrios Boskou, Vı́ctor Guallar and Yixiang Xu and has published in prestigious journals such as Chemical Physics Letters, Molecules and Life Sciences.

In The Last Decade

Julia Liang

35 papers receiving 570 citations

Author Peers

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

Author						Papers	Cites
Julia Liang	227	191	138	84	63	36	579
Eleni Pitsillou	196 0.9×	176 0.9×	134 1.0×	61 0.7×	60 1.0×	33	509
Melina Mottin	168 0.7×	108 0.6×	116 0.8×	56 0.7×	47 0.7×	33	539
Jihye Lee	146 0.6×	117 0.6×	321 2.3×	30 0.4×	14 0.2×	18	634
Md. Sahab Uddin	153 0.7×	44 0.2×	32 0.2×	46 0.5×	40 0.6×	32	553
Zi-Lin Li	219 1.0×	20 0.1×	65 0.5×	40 0.5×	34 0.5×	47	626
Talha Jawaid	172 0.8×	40 0.2×	63 0.5×	72 0.9×	11 0.2×	66	685
Yi Sun	331 1.5×	141 0.7×	11 0.1×	32 0.4×	56 0.9×	29	603
Gilda Neves	197 0.9×	17 0.1×	50 0.4×	88 1.0×	42 0.7×	35	558
Eunice D. Farfán‐García	180 0.8×	18 0.1×	41 0.3×	108 1.3×	22 0.3×	40	638
Jian Bao	173 0.8×	21 0.1×	55 0.4×	22 0.3×	53 0.8×	25	680

Countries citing papers authored by Julia Liang

Since Specialization

Citations

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

Fields of papers citing papers by Julia Liang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Julia Liang

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