Jared Sagendorf

748 total citations
11 papers, 342 citations indexed

About

Jared Sagendorf is a scholar working on Molecular Biology, Materials Chemistry and Information Systems and Management. According to data from OpenAlex, Jared Sagendorf has authored 11 papers receiving a total of 342 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 3 papers in Materials Chemistry and 1 paper in Information Systems and Management. Recurrent topics in Jared Sagendorf's work include Protein Structure and Dynamics (6 papers), RNA and protein synthesis mechanisms (5 papers) and Genomics and Chromatin Dynamics (5 papers). Jared Sagendorf is often cited by papers focused on Protein Structure and Dynamics (6 papers), RNA and protein synthesis mechanisms (5 papers) and Genomics and Chromatin Dynamics (5 papers). Jared Sagendorf collaborates with scholars based in United States, United Kingdom and China. Jared Sagendorf's co-authors include Remo Rohs, Helen M. Berman, Tsu-Pei Chiu, Alberto Pérez, Marco Pasi, Ying Jiang, Damien West, Yong Wang, Kang L. Wang and Xiao Wei and has published in prestigious journals such as Nucleic Acids Research, Nano Letters and Journal of Molecular Biology.

In The Last Decade

Jared Sagendorf

11 papers receiving 340 citations

Peers

Jared Sagendorf

MB

MC

GENET

EEE

PS

Yongmoon Jeon South Korea

Alexander Settle United States

Kathy Y. Wei United States

Robert K. Louder United States

Ottilie von Loeffelholz France

Jamie LeBarron United States

Danijela Dukovski United States

Kodai Machida Japan

Marek Havrila Czechia

Yongmoon Jeon South Korea

Jared Sagendorf

281 ×1.0

MB

25 ×0.4

MC

26 ×0.6

GENET

14 ×0.6

EEE

15 ×0.6

PS

Citations per year, relative to Jared Sagendorf Jared Sagendorf (= 1×) peers Yongmoon Jeon

Countries citing papers authored by Jared Sagendorf

Since Specialization

Citations

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

Fields of papers citing papers by Jared Sagendorf

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jared Sagendorf

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

All Works

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11 of 11 papers shown

1.

Vallat, Brinda, Benjamin Webb, Arthur O. Zalevsky, et al.. (2025). PDB-IHM: A System for Deposition, Curation, Validation, and Dissemination of Integrative Structures. Journal of Molecular Biology. 437(15). 168963–168963. 3 indexed citations

2.

Sagendorf, Jared, et al.. (2024). Structure-based prediction of protein-nucleic acid binding using graph neural networks. Biophysical Reviews. 16(3). 297–314. 10 indexed citations

3.

Sagendorf, Jared, et al.. (2024). Geometric deep learning of protein–DNA binding specificity. Nature Methods. 21(9). 1674–1683. 22 indexed citations

4.

Sagendorf, Jared, et al.. (2024). DNAproDB: an updated database for the automated and interactive analysis of protein–DNA complexes. Nucleic Acids Research. 53(D1). D396–D402. 9 indexed citations

5.

Lei, Xiao, Jun Zhao, Jared Sagendorf, et al.. (2020). Crystal Structures of Ternary Complexes of MEF2 and NKX2–5 Bound to DNA Reveal a Disease Related Protein–Protein Interaction Interface. Journal of Molecular Biology. 432(19). 5499–5508. 2 indexed citations

6.

Sagendorf, Jared, et al.. (2019). DNAproDB: an expanded database and web-based tool for structural analysis of DNA–protein complexes. Nucleic Acids Research. 48(D1). D277–D287. 57 indexed citations

7.

Jiang, Yining, et al.. (2018). Experimental maps of DNA structure at nucleotide resolution distinguish intrinsic from protein-induced DNA deformations. Nucleic Acids Research. 46(5). 2636–2647. 19 indexed citations

8.

Sagendorf, Jared, et al.. (2017). Expanding the repertoire of DNA shape features for genome-scale studies of transcription factor binding. Nucleic Acids Research. 45(22). 12877–12887. 73 indexed citations

9.

Sagendorf, Jared, Helen M. Berman, & Remo Rohs. (2017). DNAproDB: an interactive tool for structural analysis of DNA–protein complexes. Nucleic Acids Research. 45(W1). W89–W97. 59 indexed citations

10.

Li, Jun, Ana Carolina Dantas Machado, Ming Guo, et al.. (2017). Structure of the Forkhead Domain of FOXA2 Bound to a Complete DNA Consensus Site. Biochemistry. 56(29). 3745–3753. 38 indexed citations

11.

Jiang, Ying, Yong Wang, Jared Sagendorf, et al.. (2013). Direct Atom-by-Atom Chemical Identification of Nanostructures and Defects of Topological Insulators. Nano Letters. 13(6). 2851–2856. 50 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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