Jared R. Auclair

1.5k total citations
34 papers, 794 citations indexed

About

Jared R. Auclair is a scholar working on Molecular Biology, Immunology and Infectious Diseases. According to data from OpenAlex, Jared R. Auclair has authored 34 papers receiving a total of 794 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 6 papers in Immunology and 5 papers in Infectious Diseases. Recurrent topics in Jared R. Auclair's work include Protein purification and stability (7 papers), Biosimilars and Bioanalytical Methods (6 papers) and Viral Infectious Diseases and Gene Expression in Insects (5 papers). Jared R. Auclair is often cited by papers focused on Protein purification and stability (7 papers), Biosimilars and Bioanalytical Methods (6 papers) and Viral Infectious Diseases and Gene Expression in Insects (5 papers). Jared R. Auclair collaborates with scholars based in United States, Mexico and Canada. Jared R. Auclair's co-authors include Jeffrey N. Agar, Dagmar Ringe, Gregory A. Petsko, Mark Cookson, Quyen Q. Hoang, B.N. Webb, Wei Wang, Johnathan Chittuluru, Shulin Ju and Alice Kaganovich and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Jared R. Auclair

27 papers receiving 787 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jared R. Auclair United States 12 408 312 217 125 71 34 794
Jordi Pujols Spain 15 286 0.7× 546 1.8× 310 1.4× 96 0.8× 66 0.9× 22 980
Diana Olschewski Germany 13 217 0.5× 682 2.2× 144 0.7× 108 0.9× 84 1.2× 13 941
Mark A. Breidenbach United States 11 372 0.9× 329 1.1× 45 0.2× 183 1.5× 99 1.4× 11 738
Agata Rekas Australia 16 184 0.5× 871 2.8× 312 1.4× 111 0.9× 195 2.7× 30 1.3k
Liangzhong Lim Singapore 20 362 0.9× 832 2.7× 84 0.4× 62 0.5× 120 1.7× 39 1.2k
Jobin Varkey United States 17 491 1.2× 566 1.8× 386 1.8× 176 1.4× 241 3.4× 23 1.1k
Donald E. Spratt United States 17 144 0.4× 814 2.6× 219 1.0× 78 0.6× 122 1.7× 43 1.1k
Benedetta Bolognesi Spain 19 145 0.4× 982 3.1× 467 2.2× 59 0.5× 103 1.5× 31 1.3k
Janice E. Kranz United States 11 218 0.5× 841 2.7× 45 0.2× 84 0.7× 114 1.6× 14 1.1k

Countries citing papers authored by Jared R. Auclair

Since Specialization
Citations

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

Fields of papers citing papers by Jared R. Auclair

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jared R. Auclair. 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 Jared R. Auclair. The network helps show where Jared R. Auclair may publish in the future.

Co-authorship network of co-authors of Jared R. Auclair

This figure shows the co-authorship network connecting the top 25 collaborators of Jared R. Auclair. A scholar is included among the top collaborators of Jared R. Auclair 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 Jared R. Auclair. Jared R. Auclair 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.
Auclair, Jared R., et al.. (2025). Regulating the AI-enabled ecosystem for human therapeutics. Communications Medicine. 5(1). 181–181. 9 indexed citations
2.
Iyer, Shankar, et al.. (2025). Immunogenicity risk mitigation of therapeutic proteins with translational immunogenicity, analytical characterization, and regulatory insight. Journal of Pharmaceutical Sciences. 114(11). 103870–103870.
3.
Amin, Jakal, Jaime L. Schneider, Jared R. Auclair, et al.. (2025). Mass spectrometry methods and mathematical PK/PD model for decision tree-guided covalent drug development. Nature Communications. 16(1). 1777–1777. 1 indexed citations
4.
Auclair, Jared R., et al.. (2025). Reimagining drug regulation in the age of AI: a framework for the AI-enabled Ecosystem for Therapeutics. Frontiers in Medicine. 12. 1679611–1679611.
5.
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7.
Baker, Peter, et al.. (2023). Evaluation of a Pilot: Inspection Facilitation and Collaboration Using a Mixed Reality Device. Therapeutic Innovation & Regulatory Science. 58(1). 11–15. 3 indexed citations
8.
Auclair, Jared R. & Anurag S. Rathore. (2023). Analytical Methods to Determine the Stability of Biopharmaceutical Products. LCGC North America. 23–27. 2 indexed citations
9.
Rathore, Anurag S., Jared R. Auclair, & Sunil Kumar. (2023). Intact Mass Analysis–Based Multi-Attribute Methods (iMAMs) for Characterization of Biopharmaceuticals. LCGC North America. 138–142,149.
10.
Auclair, Jared R., et al.. (2022). Performance of the TaqMan COVID-19 Pooling Kit for detection of SARS-CoV-2 in asymptomatic and symptomatic populations. PLoS ONE. 17(6). e0269798–e0269798. 1 indexed citations
11.
Auclair, Jared R. & Anurag S. Rathore. (2022). Analytical Characterization of Host Cell Proteins (HCPs). LCGC North America. 493–495. 2 indexed citations
12.
Auclair, Jared R. & Anurag S. Rathore. (2021). The Multi-Attribute Method (MAM) for the Characterization of Biopharmaceuticals. LCGC North America. 28–32. 5 indexed citations
13.
Ábel, György, et al.. (2021). Two-Stage Hierarchical Group Testing Strategy to Increase SARS-CoV-2 Testing Capacity at an Institution of Higher Education. Journal of Molecular Diagnostics. 23(12). 1691–1698. 3 indexed citations
14.
Chanin, Rachael B., Kourtney P. Nickerson, Alejandro Llanos‐Chea, et al.. (2019). Shigella flexneri Adherence Factor Expression in In Vivo -Like Conditions. mSphere. 4(6). 25 indexed citations
15.
Auclair, Jared R.. (2018). Regulatory Convergence for Biologics through Capacity Building and Training. Trends in biotechnology. 37(1). 5–9. 7 indexed citations
16.
Salisbury, Joseph P., Ruxandra F. Sîrbulescu, Benjamin M. Moran, et al.. (2015). The central nervous system transcriptome of the weakly electric brown ghost knifefish (Apteronotus leptorhynchus): de novo assembly, annotation, and proteomics validation. BMC Genomics. 16(1). 166–166. 15 indexed citations
17.
Rotunno, Melissa, et al.. (2014). Identification of a Misfolded Region in Superoxide Dismutase 1 That Is Exposed in Amyotrophic Lateral Sclerosis. Journal of Biological Chemistry. 289(41). 28527–28538. 27 indexed citations
18.
Auclair, Jared R., Joseph P. Salisbury, Joshua L. Johnson, et al.. (2014). Artifacts to avoid while taking advantage of top‐down mass spectrometry based detection of protein S‐thiolation. PROTEOMICS. 14(10). 1152–1157. 16 indexed citations
19.
Auclair, Jared R., Mohan Somasundaran, Karin M. Green, et al.. (2012). Mass Spectrometry Tools for Analysis of Intermolecular Interactions. Methods in molecular biology. 896. 387–398. 3 indexed citations
20.
Auclair, Jared R., Karin M. Green, Shivender M.D. Shandilya, et al.. (2007). Mass spectrometry analysis of HIV‐1 Vif reveals an increase in ordered structure upon oligomerization in regions necessary for viral infectivity. Proteins Structure Function and Bioinformatics. 69(2). 270–284. 39 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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