Jack Schonbrun

1.3k total citations
8 papers, 1.1k citations indexed

About

Jack Schonbrun is a scholar working on Molecular Biology, Materials Chemistry and Spectroscopy. According to data from OpenAlex, Jack Schonbrun has authored 8 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Materials Chemistry and 2 papers in Spectroscopy. Recurrent topics in Jack Schonbrun's work include Protein Structure and Dynamics (7 papers), Enzyme Structure and Function (5 papers) and RNA and protein synthesis mechanisms (3 papers). Jack Schonbrun is often cited by papers focused on Protein Structure and Dynamics (7 papers), Enzyme Structure and Function (5 papers) and RNA and protein synthesis mechanisms (3 papers). Jack Schonbrun collaborates with scholars based in United States. Jack Schonbrun's co-authors include David Baker, Vladimir Yarov‐Yarovoy, Patrick Barth, Dylan Chivian, William J. Wedemeyer, Lars Malmström, David E. Kim, Carol A. Rohl, Philip Bradley and Jens Meiler and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Molecular Cell and Proteins Structure Function and Bioinformatics.

In The Last Decade

Jack Schonbrun

8 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jack Schonbrun United States	8	894	270	116	105	91	8	1.1k
Julia M. Shifman Israel	22	1.3k 1.4×	261 1.0×	93 0.8×	74 0.7×	34 0.4×	49	1.6k
David Pantoja‐Uceda Spain	21	947 1.1×	171 0.6×	45 0.4×	89 0.8×	109 1.2×	62	1.2k
Hope C. Taylor United States	10	564 0.6×	227 0.8×	40 0.3×	130 1.2×	64 0.7×	11	758
Thomas R. Hynes United States	15	1.0k 1.2×	173 0.6×	115 1.0×	27 0.3×	52 0.6×	23	1.3k
Stefan Henrich Germany	13	793 0.9×	131 0.5×	202 1.7×	67 0.6×	33 0.4×	20	1.3k
Jean Paul Olivier Canada	8	1.3k 1.4×	180 0.7×	307 2.6×	52 0.5×	75 0.8×	11	1.5k
András Aszódi Austria	15	694 0.8×	194 0.7×	51 0.4×	54 0.5×	32 0.4×	28	950
María L. Galisteo United States	11	846 0.9×	147 0.5×	66 0.6×	106 1.0×	21 0.2×	12	1.1k
Nurit Haspel United States	16	842 0.9×	261 1.0×	62 0.5×	17 0.2×	55 0.6×	65	1.0k
Yoshihiro Kobashigawa Japan	19	794 0.9×	213 0.8×	30 0.3×	32 0.3×	122 1.3×	53	1.1k

Countries citing papers authored by Jack Schonbrun

Since Specialization

Citations

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

Fields of papers citing papers by Jack Schonbrun

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jack Schonbrun

This figure shows the co-authorship network connecting the top 25 collaborators of Jack Schonbrun. A scholar is included among the top collaborators of Jack Schonbrun 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 Jack Schonbrun. Jack Schonbrun 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.

Zhu, Jieqing, Bing Luo, Patrick Barth, et al.. (2009). The Structure of a Receptor with Two Associating Transmembrane Domains on the Cell Surface: Integrin αIIbβ3. Molecular Cell. 34(2). 234–249. 122 indexed citations

2.

Barth, Patrick, Jack Schonbrun, & David Baker. (2007). Toward high-resolution prediction and design of transmembrane helical protein structures. Proceedings of the National Academy of Sciences. 104(40). 15682–15687. 181 indexed citations

3.

Chivian, Dylan, David E. Kim, Lars Malmström, et al.. (2005). Prediction of CASP6 structures using automated robetta protocols. Proteins Structure Function and Bioinformatics. 61(S7). 157–166. 116 indexed citations

4.

Bradley, Philip, Lars Malmström, Bin Qian, et al.. (2005). Free modeling with Rosetta in CASP6. Proteins Structure Function and Bioinformatics. 61(S7). 128–134. 110 indexed citations

5.

Yarov‐Yarovoy, Vladimir, Jack Schonbrun, & David Baker. (2005). Multipass membrane protein structure prediction using Rosetta. Proteins Structure Function and Bioinformatics. 62(4). 1010–1025. 264 indexed citations

6.

Schonbrun, Jack & Ken A. Dill. (2003). Fast protein folding kinetics. Proceedings of the National Academy of Sciences. 100(22). 12678–12682. 46 indexed citations

7.

Bradley, Philip, Dylan Chivian, Jens Meiler, et al.. (2003). Rosetta predictions in CASP5: Successes, failures, and prospects for complete automation. Proteins Structure Function and Bioinformatics. 53(S6). 457–468. 134 indexed citations

8.

Schonbrun, Jack, William J. Wedemeyer, & David Baker. (2002). Protein structure prediction in 2002. Current Opinion in Structural Biology. 12(3). 348–354. 78 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