Gustavo Arango-Argoty
- Molecular Medicine top 1%
- Antibiotic Resistance in Bacteria 6
- Pollution top 2%
- Pharmaceutical and Antibiotic Environmental Impacts 6
- Clinical Biochemistry top 5%
- Bacterial Identification and Susceptibility Testing 3
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- Genomics and Phylogenetic Studies 8
- Machine Learning in Bioinformatics 4
- RNA modifications and cancer 3
- Gut microbiota and health 3
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- Cancer-related molecular mechanisms research 3
- Co-authors
- Amy PrudenPeter J. VikeslandLenwood S. HeathLiqing ZhangEmily GarnerWeidong XiaoLijun ZhangDongjuan Dai
- Partner nations
- United StatesColombiaUnited Kingdom
In The Last Decade
Gustavo Arango-Argoty
24 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 117
- Molecular Medicine 325
- Applied Microbiology and Biotechnology 73
- Pollution 412
- Clinical Biochemistry 93
- Molecular Biology 580
Countries citing papers authored by Gustavo Arango-Argoty
This map shows the geographic impact of Gustavo Arango-Argoty'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 Gustavo Arango-Argoty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gustavo Arango-Argoty more than expected).
Fields of papers citing papers by Gustavo Arango-Argoty
This network shows the impact of papers produced by Gustavo Arango-Argoty. 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 Gustavo Arango-Argoty. The network helps show where Gustavo Arango-Argoty may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gustavo Arango-Argoty, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 9 | |
| 2 | 2025 | 7 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 2 | |
| 5 | 2022 | 56 | |
| 6 | 2021 | 6 | |
| 7 | 2020 | 5 | |
| 8 | 2020 | 34 | |
| 9 | 2020 | 16 | |
| 10 | 2019 | 13 | |
| 11 | 2019 | 38 | |
| 12 | 2019 | 84 | |
| 13 | DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic databreakdown → | 2018 | 558 |
| 14 | 2017 | 47 | |
| 15 | 2016 | 55 | |
| 16 | 2015 | 19 | |
| 17 | 2014 | 3 | |
| 18 | 2012 | 3 | |
| 19 | 2012 | 111 | |
| 20 | 2011 | 2 |
About Gustavo Arango-Argoty
Gustavo Arango-Argoty is a scholar working on Molecular Medicine, Pollution and Clinical Biochemistry, having authored 25 papers that have together received 1.1k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (8 papers), Antibiotic Resistance in Bacteria (6 papers), Pharmaceutical and Antibiotic Environmental Impacts (6 papers), Machine Learning in Bioinformatics (4 papers), RNA modifications and cancer (3 papers), Bacterial Identification and Susceptibility Testing (3 papers), Cancer-related molecular mechanisms research (3 papers) and Gut microbiota and health (3 papers). The work is most often cited by research in Molecular Medicine (325 citations), Applied Microbiology and Biotechnology (73 citations) and Pollution (412 citations). Gustavo Arango-Argoty has collaborated with scholars based in United States, Colombia and United Kingdom. Frequent co-authors include Amy Pruden, Peter J. Vikesland, Lenwood S. Heath, Liqing Zhang, Emily Garner, Weidong Xiao, Lijun Zhang, Dongjuan Dai, Teresa T. Liu and Sang Woo Kim.
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.