Ryan Peckner

655 total citations
8 papers, 321 citations indexed

About

Ryan Peckner is a scholar working on Molecular Biology, Spectroscopy and Organic Chemistry. According to data from OpenAlex, Ryan Peckner has authored 8 papers receiving a total of 321 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Spectroscopy and 1 paper in Organic Chemistry. Recurrent topics in Ryan Peckner's work include Advanced Proteomics Techniques and Applications (4 papers), Biomedical Text Mining and Ontologies (2 papers) and Bioinformatics and Genomic Networks (2 papers). Ryan Peckner is often cited by papers focused on Advanced Proteomics Techniques and Applications (4 papers), Biomedical Text Mining and Ontologies (2 papers) and Bioinformatics and Genomic Networks (2 papers). Ryan Peckner collaborates with scholars based in United States and Türkiye. Ryan Peckner's co-authors include Steven A. Carr, Samuel A. Myers, Brian T. Kalish, Jason Wright, Feng Zhang, Jacob D. Jaffe, Alvaro Sebastian Vaca Jácome, Michael J. MacCoss, Karsten Krug and Jarrett D. Egertson and has published in prestigious journals such as Blood, Nature Methods and Molecular & Cellular Proteomics.

In The Last Decade

Ryan Peckner

7 papers receiving 315 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ryan Peckner United States	6	259	112	52	27	20	8	321
Michaella J. Levy United States	11	310 1.2×	52 0.5×	30 0.6×	27 1.0×	21 1.1×	20	389
Ulrike Leurs Denmark	11	229 0.9×	65 0.6×	14 0.3×	37 1.4×	20 1.0×	20	318
Thomas Bonk Germany	9	163 0.6×	71 0.6×	36 0.7×	8 0.3×	20 1.0×	10	276
Nattawadee Panyain United Kingdom	8	199 0.8×	29 0.3×	46 0.9×	45 1.7×	7 0.3×	11	254
Martyna Maszota‐Zieleniak Poland	10	141 0.5×	24 0.2×	47 0.9×	26 1.0×	10 0.5×	26	213
Siv Garrod United States	12	367 1.4×	37 0.3×	66 1.3×	16 0.6×	16 0.8×	12	430
Samantha Ferries United Kingdom	7	234 0.9×	65 0.6×	122 2.3×	10 0.4×	19 0.9×	8	311
Shizhong Dai United States	6	218 0.8×	25 0.2×	39 0.8×	61 2.3×	24 1.2×	7	280
Chia-Feng Tsai Taiwan	8	290 1.1×	137 1.2×	47 0.9×	9 0.3×	11 0.6×	8	388
Rigbe Weldatsadik Finland	4	206 0.8×	36 0.3×	113 2.2×	30 1.1×	24 1.2×	5	274

Countries citing papers authored by Ryan Peckner

Since Specialization

Citations

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

Fields of papers citing papers by Ryan Peckner

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ryan Peckner

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

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Manasson, Julia, Liliana M. Sanmarco, Alex Pellerin, et al.. (2024). Preclinical Polypharmacology of S-1117, a Novel Engineered Fc-Fused IgG Degrading Enzyme, for Chronic Treatment of Autoantibody-Mediated Diseases. Blood. 144(Supplement 1). 2562–2562. 3 indexed citations

2.

Babur, Özgün, Augustin Luna, Anil Korkut, et al.. (2021). Causal interactions from proteomic profiles: Molecular data meet pathway knowledge. Patterns. 2(6). 100257–100257. 41 indexed citations

3.

Jácome, Alvaro Sebastian Vaca, Ryan Peckner, Nicholas Shulman, et al.. (2020). Avant-garde: an automated data-driven DIA data curation tool. Nature Methods. 17(12). 1237–1244. 20 indexed citations

4.

Babur, Özgün, Augustin Luna, Anil Korkut, et al.. (2020). Causal Interactions from Proteomic Profiles: Molecular Data Meets Pathway Knowledge. SSRN Electronic Journal.

5.

Papanastasiou, Malvina, Katherine C. DeRuff, Besnik Bajrami, et al.. (2019). Chasing Tails: Cathepsin-L Improves Structural Analysis of Histones by HX-MS*[S]. Molecular & Cellular Proteomics. 18(10). 2089–2098. 9 indexed citations

6.

Myers, Samuel A., Ryan Peckner, Adam L. Haber, et al.. (2019). Streamlined Protocol for Deep Proteomic Profiling of FAC-sorted Cells and Its Application to Freshly Isolated Murine Immune Cells*. Molecular & Cellular Proteomics. 18(5). 995a–1009. 71 indexed citations

7.

Myers, Samuel A., Jason Wright, Ryan Peckner, et al.. (2018). Discovery of proteins associated with a predefined genomic locus via dCas9–APEX-mediated proximity labeling. Nature Methods. 15(6). 437–439. 123 indexed citations

8.

Peckner, Ryan, Samuel A. Myers, Alvaro Sebastian Vaca Jácome, et al.. (2018). Specter: linear deconvolution for targeted analysis of data-independent acquisition mass spectrometry proteomics. Nature Methods. 15(5). 371–378. 54 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.

Explore authors with similar magnitude of impact