Pablo Meyer

3.6k total citations
51 papers, 1.7k citations indexed

About

Pablo Meyer is a scholar working on Molecular Biology, Genetics and Biomedical Engineering. According to data from OpenAlex, Pablo Meyer has authored 51 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 7 papers in Genetics and 7 papers in Biomedical Engineering. Recurrent topics in Pablo Meyer's work include Bioinformatics and Genomic Networks (12 papers), Gene expression and cancer classification (8 papers) and Gene Regulatory Network Analysis (6 papers). Pablo Meyer is often cited by papers focused on Bioinformatics and Genomic Networks (12 papers), Gene expression and cancer classification (8 papers) and Gene Regulatory Network Analysis (6 papers). Pablo Meyer collaborates with scholars based in United States, Germany and Switzerland. Pablo Meyer's co-authors include Alexey Khodjakov, Michel Bornens, Matthieu Piel, Conly L. Rieder, Michael W. Young, Lino Sáez, Gustavo Stolovitzky, Jonathan Dworkin, Raquel Norel and Julio Sáez-Rodríguez and has published in prestigious journals such as Science, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Pablo Meyer

48 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pablo Meyer United States 20 814 354 237 224 207 51 1.7k
Marten Postma Netherlands 26 1.5k 1.8× 627 1.8× 291 1.2× 446 2.0× 267 1.3× 61 2.9k
Christopher D. Wood Mexico 23 1.1k 1.4× 108 0.3× 257 1.1× 216 1.0× 270 1.3× 51 2.4k
Jessica Severin Japan 17 2.0k 2.5× 214 0.6× 81 0.3× 296 1.3× 661 3.2× 25 2.8k
Rachel B. Brem United States 32 3.4k 4.2× 260 0.7× 148 0.6× 785 3.5× 1.8k 8.7× 72 5.1k
Eran Eden Israel 13 3.6k 4.4× 272 0.8× 149 0.6× 231 1.0× 684 3.3× 25 4.9k
Michel Bagnat United States 33 2.3k 2.8× 1.4k 3.9× 130 0.5× 281 1.3× 261 1.3× 54 3.3k
Nicolas Bertin United States 14 2.6k 3.2× 209 0.6× 49 0.2× 152 0.7× 247 1.2× 23 3.1k
Nathan Blow United States 24 835 1.0× 75 0.2× 281 1.2× 47 0.2× 108 0.5× 54 1.5k
Liran Carmel Israel 31 1.7k 2.1× 81 0.2× 304 1.3× 298 1.3× 574 2.8× 70 3.0k
Anish Kejariwal United States 7 2.4k 3.0× 255 0.7× 57 0.2× 299 1.3× 1.0k 4.9× 7 3.9k

Countries citing papers authored by Pablo Meyer

Since Specialization
Citations

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

Fields of papers citing papers by Pablo Meyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pablo Meyer

This figure shows the co-authorship network connecting the top 25 collaborators of Pablo Meyer. A scholar is included among the top collaborators of Pablo Meyer 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 Pablo Meyer. Pablo Meyer 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.
Dhurandhar, Amit, Hongyang Li, Guillermo Cecchi, & Pablo Meyer. (2023). Expansive linguistic representations to predict interpretable odor mixture discriminability. Chemical Senses. 48. 1 indexed citations
2.
Li, Hongyang, Richard C. Gerkin, Alyssa J. Bakke, et al.. (2023). Text-based predictions of COVID-19 diagnosis from self-reported chemosensory descriptions. SHILAP Revista de lepidopterología. 3(1). 104–104. 9 indexed citations
3.
4.
Dey, Sanjoy Kumer, Prithwish Chakraborty, Bum Chul Kwon, et al.. (2022). Human-centered explainability for life sciences, healthcare, and medical informatics. Patterns. 3(5). 100493–100493. 21 indexed citations
5.
Walsh‐Messinger, Julie, et al.. (2021). Impairments in odour detection and hedonic ratings of unpleasant smells in asymptomatic university students as SARS‐Cov‐2 emerged locally. European Journal of Neuroscience. 54(6). 6256–6266. 2 indexed citations
6.
Meyer, Pablo & Julio Sáez-Rodríguez. (2021). Advances in systems biology modeling: 10 years of crowdsourcing DREAM challenges. Cell Systems. 12(6). 636–653. 20 indexed citations
7.
SANTOS, LETÍCIA VITÓRIA DA SILVA, Robert Vogel, Jerry E. Chipuk, et al.. (2019). Mitochondrial origins of fractional control in regulated cell death. Nature Communications. 10(1). 1313–1313. 33 indexed citations
8.
Dayrell, Roberta L. C., André Jardim Arruda, Simon Pierce, et al.. (2018). Ontogenetic shifts in plant ecological strategies. Functional Ecology. 32(12). 2730–2741. 105 indexed citations
9.
Dhurandhar, Amit, et al.. (2018). Predicting natural language descriptions of mono-molecular odorants. Nature Communications. 9(1). 4979–4979. 33 indexed citations
10.
Kim, Sung‐Cheol, Navneet Dogra, Benjamin H. Wunsch, et al.. (2017). On-Chip Liquid Biopsy: Progress in Isolation of Exosomes for Early Diagnosis of Cancer. Biophysical Journal. 112(3). 461a–461a. 2 indexed citations
11.
Gerkin, Richard C., Yuanfang Guan, Amit Dhurandhar, et al.. (2017). Predicting human olfactory perception from chemical features of odor molecules. Science. 355(6327). 820–826. 212 indexed citations
12.
Sáez-Rodríguez, Julio, James C. Costello, Stephen Friend, et al.. (2016). Crowdsourcing biomedical research: leveraging communities as innovation engines. Nature Reviews Genetics. 17(8). 470–486. 90 indexed citations
13.
Gifford, Stacey M. & Pablo Meyer. (2015). Enzyme function is regulated by its localization. Computational Biology and Chemistry. 59. 113–122. 6 indexed citations
14.
Karr, Jonathan R., Jeremy Zucker, Andreas Raue, et al.. (2015). Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models. PLoS Computational Biology. 11(5). e1004096–e1004096. 51 indexed citations
15.
Meyer, Pablo, Guillermo Cecchi, & Gustavo Stolovitzky. (2014). Spatial localization of the first and last enzymes effectively connects active metabolic pathways in bacteria. BMC Systems Biology. 8(1). 131–131. 9 indexed citations
16.
Meyer, Pablo, Thomas Cokelaer, Deepak Chandran, et al.. (2014). Network topology and parameter estimation: from experimental design methods to gene regulatory network kinetics using a community based approach. BMC Systems Biology. 8(1). 13–13. 44 indexed citations
17.
Saberi, Saeed, et al.. (2014). Localization of aggregating proteins in bacteria depends on the rate of addition. Frontiers in Microbiology. 5. 418–418. 11 indexed citations
18.
Poussin, Carine, Carole Mathis, Leonidas G. Alexopoulos, et al.. (2014). The species translation challenge—A systems biology perspective on human and rat bronchial epithelial cells. Scientific Data. 1(1). 140009–140009. 38 indexed citations
19.
Sáez, Lino, Pablo Meyer, & Michael W. Young. (2007). A PER/TIM/DBT Interval Timer forDrosophila's Circadian Clock. Cold Spring Harbor Symposia on Quantitative Biology. 72(1). 69–74. 19 indexed citations
20.
Meyer, Pablo, Lino Sáez, & Michael W. Young. (2006). PER-TIM Interactions in Living Drosophila Cells: An Interval Timer for the Circadian Clock. Science. 311(5758). 226–229. 138 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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