Vincent Blay

1.7k total citations
47 papers, 1.1k citations indexed

About

Vincent Blay is a scholar working on Molecular Biology, Computational Theory and Mathematics and Electrical and Electronic Engineering. According to data from OpenAlex, Vincent Blay has authored 47 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 13 papers in Computational Theory and Mathematics and 12 papers in Electrical and Electronic Engineering. Recurrent topics in Vincent Blay's work include Computational Drug Discovery Methods (13 papers), Electrochemical sensors and biosensors (10 papers) and Electrochemical Analysis and Applications (8 papers). Vincent Blay is often cited by papers focused on Computational Drug Discovery Methods (13 papers), Electrochemical sensors and biosensors (10 papers) and Electrochemical Analysis and Applications (8 papers). Vincent Blay collaborates with scholars based in United States, Spain and Thailand. Vincent Blay's co-authors include Sunita P. Ho, Bhairavi Tolani, Michelle R. Arkin, Piyanut Pinyou, Toshiyuki Yokoi, Liana Maria Mureşan, Melissa C. Clough, Bilge Yilmaz, Benoît Louis and Thierry Noguer and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and Renewable and Sustainable Energy Reviews.

In The Last Decade

Vincent Blay

45 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vincent Blay United States 15 313 279 260 234 204 47 1.1k
Safwat Abdel‐Azeim Saudi Arabia 23 479 1.5× 99 0.4× 214 0.8× 279 1.2× 149 0.7× 82 1.6k
Peng Gao China 23 822 2.6× 84 0.3× 256 1.0× 325 1.4× 110 0.5× 129 1.7k
Jian Jiao China 21 595 1.9× 417 1.5× 115 0.4× 257 1.1× 497 2.4× 55 1.4k
Brian Yoo United States 13 233 0.7× 47 0.2× 160 0.6× 137 0.6× 230 1.1× 18 886
Hanlu Wang China 20 950 3.0× 235 0.8× 156 0.6× 197 0.8× 151 0.7× 81 1.7k
Aiqin Li China 23 274 0.9× 192 0.7× 527 2.0× 98 0.4× 224 1.1× 97 1.7k
Yeonjoon Kim South Korea 21 532 1.7× 87 0.3× 210 0.8× 96 0.4× 287 1.4× 60 1.4k
Aditya Nandy United States 25 1.6k 5.1× 855 3.1× 231 0.9× 237 1.0× 178 0.9× 56 2.2k
Junjun Wu China 22 530 1.7× 75 0.3× 163 0.6× 439 1.9× 210 1.0× 98 1.7k

Countries citing papers authored by Vincent Blay

Since Specialization
Citations

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

Fields of papers citing papers by Vincent Blay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vincent Blay

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

All Works

20 of 20 papers shown
1.
Blay, Vincent, Keith E. J. Tyo, Linda J. Broadbelt, et al.. (2025). Merging the computational design of chimeric type I polyketide synthases with enzymatic pathways for chemical biosynthesis. Nature Communications. 16(1). 5787–5787.
2.
Sirirungruang, Sasilada, Vincent Blay, Khanh M. Vuu, et al.. (2025). A substrate-multiplexed platform for profiling enzymatic potential of plant family 1 glycosyltransferases. Nature Communications. 16(1). 6366–6366. 4 indexed citations
3.
Tittabutr, Panlada, et al.. (2025). Sensitive Detection of Nitrogen-Fixing Soil Bacteria by Impedimetric Immunosensing. ACS Omega. 10(38). 44489–44498.
4.
Janphuang, Pattanaphong, et al.. (2025). Small but Mighty: A Microfluidic Biofuel Cell-Based Biosensor for the Determination of Ethanol. Molecules. 30(3). 673–673. 1 indexed citations
5.
Sirirungruang, Sasilada, Vincent Blay, J.H. Pereira, et al.. (2024). Structural and biochemical basis for regiospecificity of the flavonoid glycosyltransferase UGT95A1. Journal of Biological Chemistry. 300(9). 107602–107602. 4 indexed citations
6.
Janphuang, Pattanaphong, et al.. (2024). Enhancing Glucose Biosensing with Graphene Oxide and Ferrocene-Modified Linear Poly(ethylenimine). Biosensors. 14(4). 161–161. 8 indexed citations
7.
Shave, Steven, Jie Dong, Douglas R. Houston, et al.. (2023). From intuition to AI: evolution of small molecule representations in drug discovery. Briefings in Bioinformatics. 25(1). 28 indexed citations
8.
Blay, Vincent, Tijana Radivojević, Jonathan Allen, Corey Hudson, & Héctor García Martín. (2022). MACAW: An Accessible Tool for Molecular Embedding and Inverse Molecular Design. Journal of Chemical Information and Modeling. 62(15). 3551–3564. 5 indexed citations
9.
Pinyou, Piyanut, et al.. (2022). Wiring Xanthine Oxidase Using an Osmium‐Complex‐Modified Polymer for Application in Biosensing.. ChemElectroChem. 9(11). 4 indexed citations
10.
Blay, Vincent, et al.. (2022). SCORCH: Improving structure-based virtual screening with machine learning classifiers, data augmentation, and uncertainty estimation. Journal of Advanced Research. 46. 135–147. 23 indexed citations
11.
Pinyou, Piyanut, et al.. (2022). A facile method for generating polypyrrole microcapsules and their application in electrochemical sensing. Microchimica Acta. 189(11). 410–410. 4 indexed citations
12.
Blay, Vincent, et al.. (2022). Combining DELs and machine learning for toxicology prediction. Drug Discovery Today. 27(11). 103351–103351. 9 indexed citations
13.
Blay, Vincent, Jie Dong, & Andrés Moyá. (2021). Machine learning study of the molecular drivers of natural product prices. Biofuels Bioproducts and Biorefining. 15(6). 1820–1834. 1 indexed citations
14.
Blay, Vincent, Irene Otero‐Muras, & D. Allen Annis. (2020). Solving the Competitive Binding Equilibria between Many Ligands: Application to High-Throughput Screening and Affinity Optimization. Analytical Chemistry. 92(18). 12630–12638. 5 indexed citations
15.
Blay, Vincent, Raquel E. Galian, Liana Maria Mureşan, et al.. (2020). Research Frontiers in Energy‐Related Materials and Applications for 2020–2030. Advanced Sustainable Systems. 4(2). 39 indexed citations
16.
Blay, Vincent, et al.. (2020). Structural and chemical heterogeneities of primary hyperoxaluria kidney stones from pediatric patients. Journal of Pediatric Urology. 17(2). 214.e1–214.e11. 6 indexed citations
17.
Blay, Vincent, Bhairavi Tolani, Sunita P. Ho, & Michelle R. Arkin. (2020). High-Throughput Screening: today’s biochemical and cell-based approaches. Drug Discovery Today. 25(10). 1807–1821. 203 indexed citations
18.
Blay, Vincent, et al.. (2019). Separation of air components and pollutants by the Earth's gravitational field. Chemosphere. 232. 453–461. 2 indexed citations
19.
Blay, Vincent, et al.. (2019). Design of drug-like hepsin inhibitors against prostate cancer and kidney stones. Acta Pharmaceutica Sinica B. 10(7). 1309–1320. 11 indexed citations
20.
Blay, Vincent, et al.. (2017). Engineering Zeolites for Catalytic Cracking to Light Olefins. ACS Catalysis. 7(10). 6542–6566. 222 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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