Reine Note

865 total citations
9 papers, 345 citations indexed

About

Reine Note is a scholar working on Computational Theory and Mathematics, Infectious Diseases and Virology. According to data from OpenAlex, Reine Note has authored 9 papers receiving a total of 345 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computational Theory and Mathematics, 3 papers in Infectious Diseases and 2 papers in Virology. Recurrent topics in Reine Note's work include Computational Drug Discovery Methods (4 papers), HIV/AIDS drug development and treatment (3 papers) and HIV Research and Treatment (2 papers). Reine Note is often cited by papers focused on Computational Drug Discovery Methods (4 papers), HIV/AIDS drug development and treatment (3 papers) and HIV Research and Treatment (2 papers). Reine Note collaborates with scholars based in France, United States and Netherlands. Reine Note's co-authors include Lilia Fisk, Russell Naven, Nigel Greene, Anne Riu, Silvia Teissier, Christopher W. McAleer, Carlota Oleaga, Christopher J. Long, Carlos A. Carmona‐Moran and Jessica Langer and has published in prestigious journals such as Journal of Medicinal Chemistry, Antimicrobial Agents and Chemotherapy and Lab on a Chip.

In The Last Decade

Reine Note

9 papers receiving 341 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Reine Note France	7	120	106	95	82	40	9	345
Chantal Masungi Belgium	8	41 0.3×	30 0.3×	128 1.3×	38 0.5×	105 2.6×	8	503
Rebecca Racz United States	11	83 0.7×	68 0.6×	159 1.7×	8 0.1×	22 0.6×	26	349
Duc-Hung Pham United States	10	93 0.8×	24 0.2×	115 1.2×	16 0.2×	17 0.4×	18	336
Anchala Kumari India	14	94 0.8×	28 0.3×	227 2.4×	31 0.4×	30 0.8×	31	441
Mathieu Porceddu France	9	21 0.2×	93 0.9×	120 1.3×	11 0.1×	65 1.6×	11	330
KC Cheng United States	7	21 0.2×	58 0.5×	64 0.7×	43 0.5×	13 0.3×	12	268
Misha Itkin United States	5	109 0.9×	22 0.2×	96 1.0×	21 0.3×	9 0.2×	6	238
Shagun Krishna India	15	96 0.8×	17 0.2×	256 2.7×	15 0.2×	35 0.9×	28	478
Francis E. Agamah South Africa	6	126 1.1×	30 0.3×	175 1.8×	12 0.1×	28 0.7×	12	340
Iwona Wilk–Zasadna Italy	6	52 0.4×	81 0.8×	75 0.8×	66 0.8×	12 0.3×	8	345

Countries citing papers authored by Reine Note

Since Specialization

Citations

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

Fields of papers citing papers by Reine Note

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Reine Note

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

All Works

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9 of 9 papers shown

1.

Carmona‐Moran, Carlos A., Christopher W. McAleer, Christopher J. Long, et al.. (2020). Microphysiological heart–liver body-on-a-chip system with a skin mimic for evaluating topical drug delivery. Lab on a Chip. 20(4). 749–759. 66 indexed citations

2.

Dimitrov, S., et al.. (2019). In silico mechanistically-based profiling module for acute oral toxicity. Computational Toxicology. 12. 100109–100109. 5 indexed citations

3.

Ehrlich, Avner, Konstantinos Ioannidis, Muneef Ayyash, et al.. (2018). Microphysiological flux balance platform unravels the dynamics of drug induced steatosis. Lab on a Chip. 18(17). 2510–2522. 30 indexed citations

4.

Marrot, Laurent, et al.. (2010). Development of a mechanistic SAR model for the detection of phototoxic chemicals and use in an integrated testing strategy. Toxicology in Vitro. 25(1). 324–334. 23 indexed citations

5.

Greene, Nigel, et al.. (2010). Developing Structure−Activity Relationships for the Prediction of Hepatotoxicity. Chemical Research in Toxicology. 23(7). 1215–1222. 127 indexed citations

6.

Marchant, Carol A., et al.. (2009). An Expert System Approach to the Assessment of Hepatotoxic Potential. Chemistry & Biodiversity. 6(11). 2107–2114. 17 indexed citations

7.

Note, Reine, Philippe Lettéron, Gilles Peytavin, et al.. (2003). Mitochondrial and Metabolic Effects of Nucleoside Reverse Transcriptase Inhibitors (NRTIs) in Mice Receiving One of Five Single- and Three Dual-NRTI Treatments. Antimicrobial Agents and Chemotherapy. 47(11). 3384–3392. 36 indexed citations

8.

Pontikis, Renée, Reine Note, Chi Hung Nguyen, et al.. (2000). Synthesis and Evaluation of “AZT-HEPT”, “AZT-Pyridinone”, and “ddC-HEPT” Conjugates as Inhibitors of HIV Reverse Transcriptase. Journal of Medicinal Chemistry. 43(10). 1927–1939. 40 indexed citations

9.

Pontikis, Renée, et al.. (1999). “Mixed Inhibitors” of HIV-Reverse Transcriptase: Synthesis and Antiviral Activity. Nucleosides and Nucleotides. 18(4-5). 707–708. 1 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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