Thomas Pierrot

812 total citations · 1 hit paper
14 papers, 180 citations indexed

About

Thomas Pierrot is a scholar working on Artificial Intelligence, Molecular Biology and Computational Theory and Mathematics. According to data from OpenAlex, Thomas Pierrot has authored 14 papers receiving a total of 180 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 5 papers in Molecular Biology and 4 papers in Computational Theory and Mathematics. Recurrent topics in Thomas Pierrot's work include Reinforcement Learning in Robotics (4 papers), Machine Learning in Bioinformatics (3 papers) and Advanced Multi-Objective Optimization Algorithms (2 papers). Thomas Pierrot is often cited by papers focused on Reinforcement Learning in Robotics (4 papers), Machine Learning in Bioinformatics (3 papers) and Advanced Multi-Objective Optimization Algorithms (2 papers). Thomas Pierrot collaborates with scholars based in United Kingdom, Germany and United States. Thomas Pierrot's co-authors include Karim Beguir, Marcin J. Skwark, Guillaume Richard, Bernardo P. de Almeida, Nicolás López Carranza, Hugo Dalla-Torre, Javier Mendoza‐Revilla, Evan Trop, Christian Dallago and Hassan Sirelkhatim and has published in prestigious journals such as Bioinformatics, Nature Methods and Computers in Biology and Medicine.

In The Last Decade

Thomas Pierrot

12 papers receiving 178 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Nucleotide Transformer: building and evaluating robust foundation models for human genomics

2024 95 citations Hugo Dalla-Torre, Javier Mendoza‐Revilla et al. Nature Methods profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Thomas Pierrot United Kingdom	5	93	33	19	17	14	14	180
Karim Beguir Germany	6	96 1.0×	32 1.0×	19 1.0×	17 1.0×	14 1.0×	11	179
Nicolás López Carranza United Kingdom	5	113 1.2×	23 0.7×	19 1.0×	22 1.3×	14 1.0×	7	181
Claudine Devauchelle Germany	6	137 1.5×	47 1.4×	18 0.9×	19 1.1×	6 0.4×	8	186
Kent Shefchek United States	6	81 0.9×	36 1.1×	40 2.1×	17 1.0×	12 0.9×	9	163
Shitij Bhargava United States	3	103 1.1×	24 0.7×	17 0.9×	22 1.3×	6 0.4×	5	163
Favorisen Rosyking Lumbanraja Indonesia	7	119 1.3×	65 2.0×	16 0.8×	8 0.5×	5 0.4×	43	247
N.A. Shankaracharya India	8	80 0.9×	38 1.2×	15 0.8×	44 2.6×	5 0.4×	13	206
Mary Ann Tuli United Kingdom	6	163 1.8×	16 0.5×	17 0.9×	23 1.4×	5 0.4×	10	205
Adrian L. Hauber Germany	3	75 0.8×	15 0.5×	6 0.3×	16 0.9×	10 0.7×	5	188
Brian Kang United States	4	106 1.1×	12 0.4×	8 0.4×	16 0.9×	4 0.3×	6	164

Countries citing papers authored by Thomas Pierrot

Since Specialization

Citations

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

Fields of papers citing papers by Thomas Pierrot

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Pierrot

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

All Works

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14 of 14 papers shown

Almeida, Bernardo P. de, Hugo Dalla-Torre, Guillaume Richard, et al.. (2025). Annotating the genome at single-nucleotide resolution with DNA foundation models. Nature Methods. 22(11). 2301–2315.

Almeida, Bernardo P. de, Guillaume Richard, Hugo Dalla-Torre, et al.. (2025). A multimodal conversational agent for DNA, RNA and protein tasks. Nature Machine Intelligence. 7(6). 928–941. 7 indexed citations

Trop, Evan, et al.. (2024). Are genomic language models all you need? Exploring genomic language models on protein downstream tasks. Bioinformatics. 40(9). 2 indexed citations

Pierrot, Thomas, et al.. (2024). Multi-Objective Quality-Diversity for Crystal Structure Prediction. Proceedings of the Genetic and Evolutionary Computation Conference. 1273–1281. 2 indexed citations

Mendoza‐Revilla, Javier, Evan Trop, Maša Roller, et al.. (2024). A foundational large language model for edible plant genomes. Communications Biology. 7(1). 835–835. 34 indexed citations

Dalla-Torre, Hugo, Javier Mendoza‐Revilla, Nicolás López Carranza, et al.. (2024). Nucleotide Transformer: building and evaluating robust foundation models for human genomics. Nature Methods. 22(2). 287–297. 95 indexed citations breakdown →

Almeida, Bernardo, Maren Lang, Stefan Laurent, et al.. (2024). Multi-modal Transfer Learning between Biological Foundation Models. 78431–78450.

Beguir, Karim, Marcin J. Skwark, Yunguan Fu, et al.. (2023). Early computational detection of potential high-risk SARS-CoV-2 variants. Computers in Biology and Medicine. 155. 106618–106618. 19 indexed citations

Pierrot, Thomas, et al.. (2023). Improving the Data Efficiency of Multi-Objective Quality-Diversity through Gradient Assistance and Crowding Exploration. Proceedings of the Genetic and Evolutionary Computation Conference. 165–173. 1 indexed citations

10.

Pierrot, Thomas, et al.. (2023). The Quality-Diversity Transformer: Generating Behavior-Conditioned Trajectories with Decision Transformers. Proceedings of the Genetic and Evolutionary Computation Conference. 1221–1229. 3 indexed citations

11.

Pierrot, Thomas, et al.. (2023). Gradient-Informed Quality Diversity for the Illumination of Discrete Spaces. Proceedings of the Genetic and Evolutionary Computation Conference. 119–128. 1 indexed citations

12.

Pierrot, Thomas, Guillaume Richard, Karim Beguir, & Antoine Cully. (2022). Multi-objective quality diversity optimization. Proceedings of the Genetic and Evolutionary Computation Conference. 139–147. 13 indexed citations

13.

Pierrot, Thomas, et al.. (2021). Sample efficient Quality Diversity for neural continuous control. 1 indexed citations

14.

Pierrot, Thomas, et al.. (2019). Learning Compositional Neural Programs with Recursive Tree Search and Planning. HAL (Le Centre pour la Communication Scientifique Directe). 2 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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