Nicolas Nalpas

1.4k total citations
38 papers, 930 citations indexed

About

Nicolas Nalpas is a scholar working on Molecular Biology, Infectious Diseases and Epidemiology. According to data from OpenAlex, Nicolas Nalpas has authored 38 papers receiving a total of 930 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 13 papers in Infectious Diseases and 12 papers in Epidemiology. Recurrent topics in Nicolas Nalpas's work include Tuberculosis Research and Epidemiology (12 papers), Mycobacterium research and diagnosis (11 papers) and RNA modifications and cancer (6 papers). Nicolas Nalpas is often cited by papers focused on Tuberculosis Research and Epidemiology (12 papers), Mycobacterium research and diagnosis (11 papers) and RNA modifications and cancer (6 papers). Nicolas Nalpas collaborates with scholars based in Ireland, Germany and United Kingdom. Nicolas Nalpas's co-authors include David E. MacHugh, John A. Browne, Stephen V. Gordon, David A. Magee, Kirsten E. McLoughlin, Boris Maček, Eamonn Gormley, Carolina N. Correia, Kate E. Killick and Ronan G. Shaughnessy and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and PLoS ONE.

In The Last Decade

Nicolas Nalpas

37 papers receiving 920 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nicolas Nalpas Ireland 18 518 294 242 214 151 38 930
Ramin M. Hakami United States 16 836 1.6× 128 0.4× 203 0.8× 333 1.6× 229 1.5× 27 1.2k
Man Teng China 19 564 1.1× 417 1.4× 211 0.9× 122 0.6× 132 0.9× 63 1.1k
Supriyo Chakraborty India 21 1.3k 2.5× 138 0.5× 379 1.6× 155 0.7× 120 0.8× 74 1.6k
Andrea R. McWhorter Australia 20 595 1.1× 130 0.4× 65 0.3× 123 0.6× 129 0.9× 57 1.3k
Guiwen Yang China 17 461 0.9× 84 0.3× 175 0.7× 101 0.5× 562 3.7× 52 1.1k
Marta Alenquer Portugal 12 526 1.0× 221 0.8× 125 0.5× 219 1.0× 136 0.9× 17 857
Po-Cheng Tang Sweden 7 572 1.1× 226 0.8× 70 0.3× 151 0.7× 154 1.0× 9 1.1k
Leilei Yang China 19 223 0.4× 236 0.8× 58 0.2× 210 1.0× 168 1.1× 55 826
Jon R. Armstrong United States 12 466 0.9× 189 0.6× 98 0.4× 139 0.6× 33 0.2× 18 1.0k
James W. Bowman United States 7 429 0.8× 429 1.5× 67 0.3× 240 1.1× 289 1.9× 8 1.0k

Countries citing papers authored by Nicolas Nalpas

Since Specialization
Citations

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

Fields of papers citing papers by Nicolas Nalpas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicolas Nalpas

This figure shows the co-authorship network connecting the top 25 collaborators of Nicolas Nalpas. A scholar is included among the top collaborators of Nicolas Nalpas 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 Nicolas Nalpas. Nicolas Nalpas 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.
Massier, Sébastien, Nicolas Nalpas, Julie Hardouin, et al.. (2025). sRNA-mediated crosstalk between cell wall stress and galactose metabolism in Staphylococcus aureus. Nucleic Acids Research. 53(13).
2.
Jeon, Byoung Seung, Han Wang, Irina Bessarab, et al.. (2025). Toward industrial C8 production: oxygen intrusion drives renewable n -caprylate production from ethanol and acetate via intermediate metabolite production. Green Chemistry. 27(11). 2931–2949. 11 indexed citations
3.
Spät, Philipp, et al.. (2023). Deep Proteogenomics of a Photosynthetic Cyanobacterium. Journal of Proteome Research. 22(6). 1969–1983. 8 indexed citations
4.
Maček, Boris, et al.. (2023). Recent progress in quantitative phosphoproteomics. Expert Review of Proteomics. 20(12). 469–482. 10 indexed citations
5.
Franz‐Wachtel, Mirita, Tingting Wang, Karsten Krug, et al.. (2021). A TOR (target of rapamycin) and nutritional phosphoproteome of fission yeast reveals novel targets in networks conserved in humans. Open Biology. 11(4). 200405–200405. 8 indexed citations
6.
Gratani, Fabio Lino, Nicolas Nalpas, Elsa Germain, et al.. (2021). Proteome Dynamics during Antibiotic Persistence and Resuscitation. mSystems. 6(4). e0054921–e0054921. 9 indexed citations
7.
Nalpas, Nicolas, et al.. (2021). Temporal Analysis of Protein Ubiquitylation and Phosphorylation During Parkin-Dependent Mitophagy. Molecular & Cellular Proteomics. 21(2). 100191–100191. 13 indexed citations
8.
Sinnberg, Tobias, Heike Niessner, Andrea Forschner, et al.. (2021). Individualized Proteogenomics Reveals the Mutational Landscape of Melanoma Patients in Response to Immunotherapy. Cancers. 13(21). 5411–5411. 3 indexed citations
9.
McLoughlin, Kirsten E., Carolina N. Correia, John A. Browne, et al.. (2021). RNA-Seq Transcriptome Analysis of Peripheral Blood From Cattle Infected With Mycobacterium bovis Across an Experimental Time Course. Frontiers in Veterinary Science. 8. 662002–662002. 9 indexed citations
10.
Sinnberg, Tobias, et al.. (2021). Proteogenomics Reveals Perturbed Signaling Networks in Malignant Melanoma Cells Resistant to BRAF Inhibition. Molecular & Cellular Proteomics. 20. 100163–100163. 6 indexed citations
11.
Singer‐Krüger, Birgit, et al.. (2019). APEX2‐mediated proximity labeling resolves protein networks in Saccharomyces cerevisiae cells. FEBS Journal. 287(2). 325–344. 17 indexed citations
12.
13.
Ravikumar, Vaishnavi, Nicolas Nalpas, Karsten Krug, et al.. (2018). In-depth analysis of Bacillus subtilis proteome identifies new ORFs and traces the evolutionary history of modified proteins. Scientific Reports. 8(1). 17246–17246. 25 indexed citations
14.
15.
Rue-Albrecht, Kévin, Paul McGettigan, Belinda Hernández, et al.. (2016). GOexpress: an R/Bioconductor package for the identification and visualisation of robust gene ontology signatures through supervised learning of gene expression data. BMC Bioinformatics. 17(1). 126–126. 22 indexed citations
16.
Meade, Kieran G., Nicolas Nalpas, John A. Browne, et al.. (2015). Analysis of the Bovine Monocyte-Derived Macrophage Response to Mycobacterium avium Subspecies Paratuberculosis Infection Using RNA-seq. Frontiers in Immunology. 6. 23–23. 37 indexed citations
17.
Nalpas, Nicolas, David A. Magee, Kevin M. Conlon, et al.. (2015). RNA sequencing provides exquisite insight into the manipulation of the alveolar macrophage by tubercle bacilli. Scientific Reports. 5(1). 13629–13629. 32 indexed citations
18.
Magee, David A., Kevin M. Conlon, Nicolas Nalpas, et al.. (2014). Innate cytokine profiling of bovine alveolar macrophages reveals commonalities and divergence in the response to Mycobacterium bovis and Mycobacterium tuberculosis infection. Tuberculosis. 94(4). 441–450. 27 indexed citations
19.
McLoughlin, Kirsten E., Nicolas Nalpas, Kévin Rue-Albrecht, et al.. (2014). RNA-seq Transcriptional Profiling of Peripheral Blood Leukocytes from Cattle Infected with Mycobacterium bovis. Frontiers in Immunology. 5. 396–396. 45 indexed citations
20.
Killick, Kate E., David A. Magee, Stephen D. E. Park, et al.. (2014). Key Hub and Bottleneck Genes Differentiate the Macrophage Response to Virulent and Attenuated Mycobacterium bovis. Frontiers in Immunology. 5. 422–422. 17 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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