Julia Koehler Leman

2.9k total citations · 1 hit paper
25 papers, 1.1k citations indexed

About

Julia Koehler Leman is a scholar working on Molecular Biology, Materials Chemistry and Genetics. According to data from OpenAlex, Julia Koehler Leman has authored 25 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 6 papers in Materials Chemistry and 3 papers in Genetics. Recurrent topics in Julia Koehler Leman's work include Protein Structure and Dynamics (19 papers), RNA and protein synthesis mechanisms (8 papers) and Machine Learning in Bioinformatics (5 papers). Julia Koehler Leman is often cited by papers focused on Protein Structure and Dynamics (19 papers), RNA and protein synthesis mechanisms (8 papers) and Machine Learning in Bioinformatics (5 papers). Julia Koehler Leman collaborates with scholars based in United States, Germany and Poland. Julia Koehler Leman's co-authors include Richard Bonneau, Jeffrey J. Gray, Daniel Berenberg, Vladimir Gligorijević, Kyunghyun Cho, Tommi Vatanen, Bryn C. Taylor, Ramnik J. Xavier, I. Fisk and Rob Knight and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Nature Biotechnology.

In The Last Decade

Julia Koehler Leman

25 papers receiving 1.1k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Structure-based protein function prediction using graph convolutional networks

2021 467 citations Vladimir Gligorijević, P. Douglas Renfrew et al. Nature Communications profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Julia Koehler Leman United States	16	869	168	148	70	68	25	1.1k
Edoardo Milanetti Italy	20	592 0.7×	107 0.6×	127 0.9×	44 0.6×	103 1.5×	65	934
Gyu Rie Lee South Korea	14	748 0.9×	148 0.9×	122 0.8×	34 0.5×	99 1.5×	23	909
Rebecca F. Alford United States	6	990 1.1×	230 1.4×	124 0.8×	57 0.8×	152 2.2×	12	1.2k
Gordon Lemmon United States	12	949 1.1×	218 1.3×	165 1.1×	55 0.8×	156 2.3×	16	1.3k
Martin K. Scherer Germany	3	716 0.8×	192 1.1×	118 0.8×	108 1.5×	47 0.7×	3	856
Sebastian Bittrich United States	12	762 0.9×	162 1.0×	131 0.9×	46 0.7×	32 0.5×	23	1.1k
Coos Baakman Netherlands	7	799 0.9×	183 1.1×	93 0.6×	56 0.8×	50 0.7×	10	1.0k
Justas Dauparas United States	14	945 1.1×	193 1.1×	95 0.6×	47 0.7×	87 1.3×	20	1.2k
Alberto J. M. Martín Chile	16	1.2k 1.4×	299 1.8×	129 0.9×	76 1.1×	30 0.4×	54	1.5k
Benoît H. Dessailly United Kingdom	16	1.0k 1.2×	233 1.4×	120 0.8×	53 0.8×	68 1.0×	18	1.2k

Countries citing papers authored by Julia Koehler Leman

Since Specialization

Citations

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

Fields of papers citing papers by Julia Koehler Leman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Julia Koehler Leman. 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 Julia Koehler Leman. The network helps show where Julia Koehler Leman may publish in the future.

Co-authorship network of co-authors of Julia Koehler Leman

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

All Works

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20 of 20 papers shown

Leman, Julia Koehler, et al.. (2024). Modeling membrane geometries implicitly in Rosetta. Protein Science. 33(3). e4908–e4908. 4 indexed citations

Kuenze, Georg, et al.. (2023). Docking cholesterol to integral membrane proteins with Rosetta. PLoS Computational Biology. 19(3). e1010947–e1010947. 5 indexed citations

Hamamsy, Tymor, James T. Morton, Robert N. Blackwell, et al.. (2023). Protein remote homology detection and structural alignment using deep learning. Nature Biotechnology. 42(6). 975–985. 60 indexed citations

Leman, Julia Koehler & Richard Bonneau. (2023). Specificities of Modeling of Membrane Proteins Using Multi-Template Homology Modeling. Methods in molecular biology. 2627. 141–166. 2 indexed citations

Leman, Julia Koehler, P. Douglas Renfrew, Vladimir Gligorijević, et al.. (2023). Sequence-structure-function relationships in the microbial protein universe. Nature Communications. 14(1). 2351–2351. 44 indexed citations

Leman, Julia Koehler, et al.. (2023). Recent Advances in NMR Protein Structure Prediction with ROSETTA. International Journal of Molecular Sciences. 24(9). 7835–7835. 21 indexed citations

Gligorijević, Vladimir, P. Douglas Renfrew, Tomasz Kościółek, et al.. (2021). Structure-based protein function prediction using graph convolutional networks. Nature Communications. 12(1). 3168–3168. 467 indexed citations breakdown →

Kuenze, Georg, Richard Bonneau, Julia Koehler Leman, & Jens Meiler. (2019). Integrative Protein Modeling in RosettaNMR from Sparse Paramagnetic Restraints. Structure. 27(11). 1721–1734.e5. 24 indexed citations

Leman, Julia Koehler, Richard Bonneau, & Martin B. Ulmschneider. (2018). Statistically derived asymmetric membrane potentials from α-helical and β-barrel membrane proteins. Scientific Reports. 8(1). 4446–4446. 9 indexed citations

10.

Freedman, Holly, Michael Logan, Darren Hockman, et al.. (2017). Computational Prediction of the Heterodimeric and Higher-Order Structure of gpE1/gpE2 Envelope Glycoproteins Encoded by Hepatitis C Virus. Journal of Virology. 91(8). 25 indexed citations

11.

Leman, Julia Koehler & Richard Bonneau. (2017). A Novel Domain Assembly Routine for Creating Full-Length Models of Membrane Proteins from Known Domain Structures. Biochemistry. 57(13). 1939–1944. 5 indexed citations

12.

Leman, Julia Koehler, Sergey Lyskov, & Richard Bonneau. (2017). Computing structure-based lipid accessibility of membrane proteins with mp_lipid_acc in RosettaMP. BMC Bioinformatics. 18(1). 115–115. 19 indexed citations

13.

Leman, Julia Koehler, et al.. (2017). Comparison of NMR and crystal structures of membrane proteins and computational refinement to improve model quality. Proteins Structure Function and Bioinformatics. 86(1). 57–74. 8 indexed citations

14.

Finn, Jessica A., et al.. (2016). Improving Loop Modeling of the Antibody Complementarity-Determining Region 3 Using Knowledge-Based Restraints. PLoS ONE. 11(5). e0154811–e0154811. 17 indexed citations

15.

Leman, Julia Koehler, Benjamin K. Mueller, & Jeffrey J. Gray. (2016). Expanding the toolkit for membrane protein modeling in Rosetta. Bioinformatics. 33(5). 754–756. 27 indexed citations

16.

Leman, Julia Koehler, et al.. (2015). A survey of conformational and energetic changes in G protein signaling. SHILAP Revista de lepidopterología. 2(4). 630–648. 1 indexed citations

17.

Ulmschneider, Martin B., et al.. (2015). Peptide Folding in Translocon-Like Pores. The Journal of Membrane Biology. 248(3). 407–417. 2 indexed citations

18.

Braun, Tatjana, Julia Koehler Leman, & Oliver F. Lange. (2015). Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction. PLoS Computational Biology. 11(12). e1004661–e1004661. 15 indexed citations

19.

Pilla, Kala Bharath, Julia Koehler Leman, Gottfried Otting, & Thomas Huber. (2015). Capturing Conformational States in Proteins Using Sparse Paramagnetic NMR Data. PLoS ONE. 10(5). e0127053–e0127053. 28 indexed citations

20.

Leman, Julia Koehler, Rebecca F. Alford, & Jeffrey J. Gray. (2015). Rosetta-MPDock: A Novel Computational Tool for Protein-Protein Docking within the Membrane Bilayer. Biophysical Journal. 108(2). 250a–250a. 1 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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