Gary Liu

20 papers receiving 583 citations

Hit Papers

AI Methods for Antimicrobial Peptides: Progress and Challenges 2025 · 20 citations
200+1+2Years since publication50100150

Peers

Gary Liu
Comparison fields: 5 of 117
  • Health Informatics 18
  • Applied Microbiology and Biotechnology 27
  • Molecular Medicine 50
  • Sensory Systems 32
  • Microbiology 38
Replace Chia‐Ru Chung with:
Chia‐Ru Chung Taiwan
Andrew M. Stern United States
Yixi Chen China
Alexandre Drouin Canada
Jeffrey M. Hubbard United States
Hongyang Li United States
Wang Gan United States
Neha Jain India
Yuxuan Hu China
Yoon Y. Hwang United States
Gary Liu relative to Chia‐Ru Chung Taiwan Chia‐Ru Chung's profile →
Citations per field
00.5×10×15×
Chia‐Ru Chung · 1×
Citations per year

Countries citing papers authored by Gary Liu

Since Specialization
Citations

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

Fields of papers citing papers by Gary Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Gary Liu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gary Liu Line = papers co-authored together Gary Liu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Deep learning-guided discovery of an antibiotic targeting Acinetobacter baumannii
Hit paper breakdown →
2023183
2 2013108
3
Generative AI for designing and validating easily synthesizable and structurally novel antibiotics
Hit paper breakdown →
202483
4 202130
5 201925
6 202223
7
AI Methods for Antimicrobial Peptides: Progress and Challenges
Hit paper breakdown →
202520
8 202019
9 201818
10 202216
11 202313
12 200112
13 202112
14 20209
15
Overlap of computation and communication on shared-memory networks-of-workstations
20017
16 20185
17 20253
18 20223
19 19983
20 20182

About Gary Liu

Gary Liu is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Sensory Systems, Pharmacology and Computational Theory and Mathematics, having authored 21 papers that have together received 594 indexed citations. Recurring topics across this work include Olfactory and Sensory Function Studies (4 papers), Computational Drug Discovery Methods (3 papers), Biochemical Analysis and Sensing Techniques (3 papers), Microbial Natural Products and Biosynthesis (3 papers), Neurobiology and Insect Physiology Research (3 papers), Antimicrobial Peptides and Activities (3 papers), Parallel Computing and Optimization Techniques (2 papers) and Biochemical and Structural Characterization (2 papers). The work is most often cited by research in Health Informatics (18 citations), Applied Microbiology and Biotechnology (27 citations), Molecular Medicine (50 citations), Sensory Systems (32 citations) and Microbiology (38 citations). Gary Liu has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include Michael Bressan, Takashi Mikawa, J Stokes, Denise B. Catacutan, Kyle Swanson, Jonathan Stokes, James Zou, Wengong Jin, Michael G. Surette and Kenneth Rachwalski. Their work appears in journals such as Nature Communications, Journal of Visualized Experiments, Journal of Hepatology, Microbial Biotechnology and Journal of Affective Disorders.

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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