Julia Liang
Impact in
- Biological Psychiatry top 10%
- Tryptophan and brain disorders
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- Computational Drug Discovery Methods
Papers in
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- RNA and protein synthesis mechanisms 5
- Protein Structure and Dynamics 3
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- Computational Drug Discovery Methods 14
- Co-authors
- Tom C. Karagiannis (34 shared papers)Andrew Hung (33 shared papers)Eleni Pitsillou (29 shared papers)Katherine Ververis (7 shared papers)Ken Ng (4 shared papers)Kah Wai Lim (1 shared paper)Nancy B. Ray (1 shared paper)Dimitrios Boskou (1 shared paper)
In The Last Decade
Julia Liang
35 papers receiving 608 citations
Peers
Comparison fields: 5 of 90
- Biological Psychiatry 53
- Computational Theory and Mathematics 188
- Behavioral Neuroscience 31
- Infectious Diseases 134
- Biochemistry 33
Countries citing papers authored by Julia Liang
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
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-authors
The 25 scholars most cited alongside Julia Liang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 142 | |
| 2 | 2020 | 64 | |
| 3 | 2018 | 52 | |
| 4 | 2020 | 50 | |
| 5 | 2020 | 44 | |
| 6 | 2020 | 39 | |
| 7 | 2021 | 31 | |
| 8 | 2022 | 18 | |
| 9 | 2020 | 18 | |
| 10 | 2024 | 15 | |
| 11 | 2022 | 13 | |
| 12 | 2021 | 10 | |
| 13 | 2021 | 10 | |
| 14 | 2022 | 10 | |
| 15 | 2021 | 10 | |
| 16 | 2021 | 9 | |
| 17 | 2021 | 8 | |
| 18 | 2023 | 7 | |
| 19 | 2024 | 7 | |
| 20 | 2017 | 6 |
About Julia Liang
Julia Liang is a scholar working on Molecular Biology, Computational Theory and Mathematics, Infectious Diseases, Pharmacology and Organic Chemistry, having authored 37 papers that have together received 615 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (14 papers), SARS-CoV-2 and COVID-19 Research (10 papers), RNA and protein synthesis mechanisms (5 papers), Phytochemicals and Antioxidant Activities (3 papers), Inflammatory mediators and NSAID effects (3 papers), Protein Structure and Dynamics (3 papers), Hormonal Regulation and Hypertension (3 papers) and Tryptophan and brain disorders (3 papers). The work is most often cited by research in Biological Psychiatry (53 citations), Computational Theory and Mathematics (188 citations), Behavioral Neuroscience (31 citations), Infectious Diseases (134 citations) and Biochemistry (33 citations). Julia Liang has collaborated with scholars based in Australia, Hong Kong and Denmark. Frequent co-authors include Tom C. Karagiannis, Andrew Hung, Eleni Pitsillou, Katherine Ververis, Ken Ng, Kah Wai Lim, Nancy B. Ray, Dimitrios Boskou, Vı́ctor Guallar and Yixiang Xu. Their work appears in journals such as Journal of Molecular Graphics and Modelling, Molecules, Chemical Physics Letters, Computers in Biology and Medicine and Signal Transduction and Targeted Therapy.
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.