Wallace Chan

611 total citations
17 papers, 379 citations indexed

About

Wallace Chan is a scholar working on Computational Theory and Mathematics, Molecular Biology and Pharmacology. According to data from OpenAlex, Wallace Chan has authored 17 papers receiving a total of 379 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computational Theory and Mathematics, 11 papers in Molecular Biology and 6 papers in Pharmacology. Recurrent topics in Wallace Chan's work include Computational Drug Discovery Methods (14 papers), Receptor Mechanisms and Signaling (7 papers) and Cholinesterase and Neurodegenerative Diseases (6 papers). Wallace Chan is often cited by papers focused on Computational Drug Discovery Methods (14 papers), Receptor Mechanisms and Signaling (7 papers) and Cholinesterase and Neurodegenerative Diseases (6 papers). Wallace Chan collaborates with scholars based in United States, Hong Kong and China. Wallace Chan's co-authors include Yang Zhang, Roy C.Y. Choi, Karl Wah Keung Tsim, Vicky P. Chen, Ka Wing Leung, Junguk Hur, Jeffrey Brender, Arzucan Özgür, Hongjiu Zhang and Jianyi Yang and has published in prestigious journals such as Journal of Biological Chemistry, Bioinformatics and Journal of Molecular Biology.

In The Last Decade

Wallace Chan

17 papers receiving 373 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Wallace Chan United States	11	263	207	94	50	37	17	379
Maozi Chen United States	10	228 0.9×	100 0.5×	106 1.1×	102 2.0×	12 0.3×	17	391
Trung Ngoc Nguyen Germany	8	224 0.9×	117 0.6×	40 0.4×	50 1.0×	23 0.6×	18	359
Chase M. Webb United States	3	315 1.2×	217 1.0×	50 0.5×	52 1.0×	61 1.6×	4	450
Pietro Delre Italy	12	173 0.7×	145 0.7×	65 0.7×	113 2.3×	37 1.0×	33	452
Shuoyan Tan China	8	227 0.9×	179 0.9×	34 0.4×	13 0.3×	50 1.4×	19	343
Hiroaki Yabuuchi Japan	6	248 0.9×	193 0.9×	57 0.6×	31 0.6×	18 0.5×	9	323
Ji Young Lee United States	11	375 1.4×	86 0.4×	26 0.3×	113 2.3×	43 1.2×	22	499
Andreas Luttens Sweden	7	275 1.0×	204 1.0×	39 0.4×	30 0.6×	49 1.3×	7	414
Elissa A. Fink United States	4	224 0.9×	179 0.9×	37 0.4×	23 0.5×	43 1.2×	4	347
Antonius P. A. Janssen Netherlands	10	141 0.5×	68 0.3×	76 0.8×	22 0.4×	22 0.6×	24	267

Countries citing papers authored by Wallace Chan

Since Specialization

Citations

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

Fields of papers citing papers by Wallace Chan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wallace Chan

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

All Works

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17 of 17 papers shown

Chan, Wallace, Heather A. Carlson, & John R. Traynor. (2023). Application of Mixed-Solvent Molecular Dynamics Simulations for Prediction of Allosteric Sites on G Protein–Coupled Receptors. Molecular Pharmacology. 103(5). 274–285. 6 indexed citations

Chan, Wallace, et al.. (2022). In silico analysis of SARS-CoV-2 proteins as targets for clinically available drugs. Scientific Reports. 12(1). 5320–5320. 19 indexed citations

Chan, Wallace, et al.. (2022). Computational Identification of Possible Allosteric Sites and Modulators of the SARS-CoV-2 Main Protease. Journal of Chemical Information and Modeling. 62(3). 618–626. 13 indexed citations

Liu, Yingtong, Junguk Hur, Wallace Chan, et al.. (2021). Ontological modeling and analysis of experimentally or clinically verified drugs against coronavirus infection. Scientific Data. 8(1). 16–16. 12 indexed citations

Chan, Wallace, et al.. (2021). Mixed‐solvent molecular dynamics simulation‐based discovery of a putative allosteric site on regulator of G protein signaling 4. Journal of Computational Chemistry. 42(30). 2170–2180. 9 indexed citations

Chan, Wallace & Yang Zhang. (2020). Virtual Screening of Human Class-A GPCRs Using Ligand Profiles Built on Multiple Ligand–Receptor Interactions. Journal of Molecular Biology. 432(17). 4872–4890. 20 indexed citations

Chan, Wallace, Heather A. Carlson, & John R. Traynor. (2020). Cosolvent Molecular Dynamics Simulation‐Based Discovery of Potential Allosteric Sites on Regulator of G Protein Signaling 4. The FASEB Journal. 34(S1). 1–1. 2 indexed citations

Wu, Jiansheng, Yi Sun, Wallace Chan, et al.. (2020). Homologous G Protein-Coupled Receptors Boost the Modeling and Interpretation of Bioactivities of Ligand Molecules. Journal of Chemical Information and Modeling. 60(3). 1865–1875. 8 indexed citations

Wu, Jiansheng, Ben Liu, Wallace Chan, et al.. (2019). Precise modelling and interpretation of bioactivities of ligands targeting G protein-coupled receptors. Bioinformatics. 35(14). i324–i332. 13 indexed citations

10.

Wu, Jiansheng, Qiuming Zhang, Weijian Wu, et al.. (2018). WDL-RF: predicting bioactivities of ligand molecules acting with G protein-coupled receptors by combining weighted deep learning and random forest. Bioinformatics. 34(13). 2271–2282. 37 indexed citations

11.

Chan, Wallace, Hongjiu Zhang, Jianyi Yang, et al.. (2015). GLASS: a comprehensive database for experimentally validated GPCR-ligand associations. Bioinformatics. 31(18). 3035–3042. 101 indexed citations

12.

Chan, Wallace, et al.. (2012). N-linked glycosylation of proline-rich membrane anchor (PRiMA) is not required for assembly and trafficking of globular tetrameric acetylcholinesterase. Neuroscience Letters. 523(1). 71–75. 6 indexed citations

13.

Chen, Vicky P., Roy C.Y. Choi, Wallace Chan, et al.. (2011). The Assembly of Proline-rich Membrane Anchor (PRiMA)-linked Acetylcholinesterase Enzyme. Journal of Biological Chemistry. 286(38). 32948–32961. 43 indexed citations

14.

Chen, Vicky P., Wallace Chan, Ka Wing Leung, et al.. (2011). Molecular Assembly and Biosynthesis of Acetylcholinesterase in Brain and Muscle: the Roles of t-peptide, FHB Domain, and N-linked Glycosylation. Frontiers in Molecular Neuroscience. 4. 36–36. 23 indexed citations

15.

Chen, Vicky P., Heidi Q. Xie, Wallace Chan, et al.. (2010). The PRiMA-linked Cholinesterase Tetramers Are Assembled from Homodimers. Journal of Biological Chemistry. 285(35). 27265–27278. 20 indexed citations

16.

Xie, Heidi Q., Liang Dong, Ka Wing Leung, et al.. (2010). Targeting Acetylcholinesterase to Membrane Rafts. Journal of Biological Chemistry. 285(15). 11537–11546. 44 indexed citations

17.

Chen, Vicky P., Heidi Q. Xie, Wallace Chan, et al.. (2010). An induction effect of heat shock on the transcript of globular acetylcholinesterase in NG108-15 cells. Chemico-Biological Interactions. 187(1-3). 106–109. 3 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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