Daniel A. Charlebois

658 total citations
38 papers, 378 citations indexed

About

Daniel A. Charlebois is a scholar working on Molecular Biology, Artificial Intelligence and Genetics. According to data from OpenAlex, Daniel A. Charlebois has authored 38 papers receiving a total of 378 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 15 papers in Artificial Intelligence and 10 papers in Genetics. Recurrent topics in Daniel A. Charlebois's work include Gene Regulatory Network Analysis (16 papers), AI-based Problem Solving and Planning (11 papers) and Evolution and Genetic Dynamics (10 papers). Daniel A. Charlebois is often cited by papers focused on Gene Regulatory Network Analysis (16 papers), AI-based Problem Solving and Planning (11 papers) and Evolution and Genetic Dynamics (10 papers). Daniel A. Charlebois collaborates with scholars based in Canada, United States and Russia. Daniel A. Charlebois's co-authors include Gábor Balázsi, Mads Kærn, Nezar Abdennur, Dmitry Nevozhay, D.G. Goodenough, Joseph Cohen, Mariola Szenk, Stan Matwin, Kevin Hauser and Shamanth A. Shankarnarayan and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Physical Review Letters.

In The Last Decade

Daniel A. Charlebois

33 papers receiving 371 citations

Peers

Daniel A. Charlebois

GENET

David Murrugarra United States

Eugene van Someren Netherlands

Susanne Toepfer Germany

Mihai Glont United Kingdom

Lucian P. Smith United States

Rainer Opgen-Rhein Germany

Paola Vera‐Licona United States

Laurent Tournier France

Zhenhua Yu China

David Murrugarra United States

Daniel A. Charlebois

284 ×1.1

54 ×0.5

GENET

16 ×0.5

26 ×1.0

12 ×0.5

Citations per year, relative to Daniel A. Charlebois Daniel A. Charlebois (= 1×) peers David Murrugarra

Countries citing papers authored by Daniel A. Charlebois

Since Specialization

Citations

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

Fields of papers citing papers by Daniel A. Charlebois

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel A. Charlebois. 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 Daniel A. Charlebois. The network helps show where Daniel A. Charlebois may publish in the future.

Co-authorship network of co-authors of Daniel A. Charlebois

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

All Works

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20 of 20 papers shown

Charlebois, Daniel A., et al.. (2024). Fitness effects of a demography-dispersal trade-off in expanding Saccharomyces cerevisiae mats. Physical Biology. 21(2). 26001–26001.

Shankarnarayan, Shamanth A. & Daniel A. Charlebois. (2023). Machine learning to identify clinically relevant Candida yeast species. Medical Mycology. 62(1). 7 indexed citations

Shankarnarayan, Shamanth A., et al.. (2023). Identification and Elimination of Antifungal Tolerance in Candida auris. Biomedicines. 11(3). 898–898. 9 indexed citations

Charlebois, Daniel A.. (2023). Quantitative systems-based prediction of antimicrobial resistance evolution. npj Systems Biology and Applications. 9(1). 40–40. 5 indexed citations

Charlebois, Daniel A., et al.. (2022). Non-genetic resistance facilitates survival while hindering the evolution of drug resistance due to intraspecific competition. Physical Biology. 19(6). 66002–66002. 6 indexed citations

Charlebois, Daniel A., et al.. (2021). Lattice-based Monte Carlo simulation of the effects of nutrient concentration and magnetic field exposure on yeast colony growth and morphology. In Silico Biology. 14(3-4). 53–69. 1 indexed citations

Charlebois, Daniel A., et al.. (2019). Role of network-mediated stochasticity in mammalian drug resistance. Nature Communications. 10(1). 2766–2766. 67 indexed citations

Charlebois, Daniel A., et al.. (2018). Multiscale effects of heating and cooling on genes and gene networks. Proceedings of the National Academy of Sciences. 115(45). E10797–E10806. 41 indexed citations

Charlebois, Daniel A. & Gábor Balázsi. (2018). Modeling cell population dynamics. In Silico Biology. 13(1-2). 21–39. 46 indexed citations

10.

Charlebois, Daniel A., et al.. (2018). Negative Regulation Gene Circuits for Efflux Pump Control. Methods in molecular biology. 1772. 25–43. 4 indexed citations

11.

Charlebois, Daniel A.. (2015). Effect and evolution of gene expression noise on the fitness landscape. Physical Review E. 92(2). 22713–22713. 12 indexed citations

12.

Charlebois, Daniel A., Gábor Balázsi, & Mads Kærn. (2014). Coherent feedforward transcriptional regulatory motifs enhance drug resistance. Physical Review E. 89(5). 52708–52708. 30 indexed citations

13.

Charlebois, Daniel A. & Mads Kærn. (2013). An Accelerated Method for Simulating Population Dynamics. Communications in Computational Physics. 14(2). 461–476. 5 indexed citations

14.

Charlebois, Daniel A., Nezar Abdennur, & Mads Kærn. (2011). Gene Expression Noise Facilitates Adaptation and Drug Resistance Independently of Mutation. Physical Review Letters. 107(21). 218101–218101. 55 indexed citations

15.

Charlebois, Daniel A., et al.. (2010). Security Classification Using Automated Learning (SCALE): Optimizing Statistical Natural Language Processing Techniques to Assign Security Labels to Unstructured Text. 2 indexed citations

16.

Charlebois, Daniel A.. (2009). Journal club. Nature. 458(7240). 811–811. 2 indexed citations

17.

Charlebois, Daniel A., André S. Ribeiro, Antti Lehmussola, et al.. (2007). Effects of microarray noise on inference efficiency of a stochastic model of gene networks. 4(2). 15–21. 2 indexed citations

18.

Goodenough, D.G., et al.. (2003). SEIDAM: a flexible and interoperable metadata-driven system for intelligent forest monitoring. 2. 1338–1341. 1 indexed citations

19.

Goodenough, D.G., et al.. (2002). Automated forest inventory update with SEIDAM. 2. 670–673. 4 indexed citations

20.

Goodenough, D.G., et al.. (1998). An improved planner for intelligent monitoring of sustainable development of forests. 397–399 vol.1. 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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