Chen Keasar

1.3k total citations
31 papers, 867 citations indexed

About

Chen Keasar is a scholar working on Molecular Biology, Materials Chemistry and Spectroscopy. According to data from OpenAlex, Chen Keasar has authored 31 papers receiving a total of 867 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 10 papers in Materials Chemistry and 6 papers in Spectroscopy. Recurrent topics in Chen Keasar's work include Protein Structure and Dynamics (17 papers), Enzyme Structure and Function (9 papers) and Machine Learning in Bioinformatics (8 papers). Chen Keasar is often cited by papers focused on Protein Structure and Dynamics (17 papers), Enzyme Structure and Function (9 papers) and Machine Learning in Bioinformatics (8 papers). Chen Keasar collaborates with scholars based in Israel, United States and Canada. Chen Keasar's co-authors include Michael Levitt, Ron Elber, Israel Sekler, Ofer Yifrach, Michal Hershfinkel, Ehud Ohana, Taiho Kambe, Eitan Hoch, El-ad David Amir and Nir Kalisman and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Chen Keasar

30 papers receiving 857 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chen Keasar Israel 15 600 177 129 82 72 31 867
Oleg Sitsel Germany 15 803 1.3× 106 0.6× 205 1.6× 48 0.6× 8 0.1× 23 1.4k
Conceição A.S.A. Minetti United States 20 548 0.9× 54 0.3× 58 0.4× 18 0.2× 30 0.4× 40 928
Mark J. Dufton United Kingdom 20 1.2k 2.0× 80 0.5× 31 0.2× 29 0.4× 21 0.3× 48 1.7k
Suzanne Duce United Kingdom 15 327 0.5× 74 0.4× 55 0.4× 22 0.3× 17 0.2× 37 1.1k
Patricia M. Dijkman United Kingdom 10 597 1.0× 56 0.3× 23 0.2× 26 0.3× 38 0.5× 12 886
Carey D. Waldburger United States 18 1.4k 2.3× 430 2.4× 37 0.3× 69 0.8× 24 0.3× 21 1.6k
Ansgar Philippsen Switzerland 23 1.5k 2.6× 187 1.1× 49 0.4× 233 2.8× 46 0.6× 28 2.1k
John Ingraham United States 17 1.6k 2.7× 247 1.4× 36 0.3× 18 0.2× 150 2.1× 20 2.0k
Akira R. Kinjo Japan 17 1.0k 1.7× 379 2.1× 18 0.1× 34 0.4× 142 2.0× 50 1.2k
Kevin L. Shaw United States 11 1.1k 1.8× 493 2.8× 32 0.2× 73 0.9× 58 0.8× 11 1.3k

Countries citing papers authored by Chen Keasar

Since Specialization
Citations

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

Fields of papers citing papers by Chen Keasar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chen Keasar

This figure shows the co-authorship network connecting the top 25 collaborators of Chen Keasar. A scholar is included among the top collaborators of Chen Keasar 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 Chen Keasar. Chen Keasar 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.
Keasar, Chen, et al.. (2023). Protein Design Using Physics Informed Neural Networks. Biomolecules. 13(3). 457–457. 7 indexed citations
2.
Anto, Nikhil Ponnoor, Pulak Ranjan Nath, Zuoming Sun, et al.. (2023). The Peptidyl-Prolyl cis-trans isomerase, Pin1, associates with Protein Kinase C θ via a critical Phospho-Thr-Pro motif in the V3 regulatory domain. Frontiers in Immunology. 14. 1126464–1126464.
3.
Haber, Eldad, et al.. (2022). Mimetic Neural Networks: A Unified Framework for Protein Design and Folding. SHILAP Revista de lepidopterología. 2. 715006–715006. 6 indexed citations
4.
Keasar, Chen, et al.. (2022). Estimation of model accuracy by a unique set of features and tree-based regressor. Scientific Reports. 12(1). 14074–14074. 1 indexed citations
5.
Liju, Vijayasteltar Belsamma, Nikhil Ponnoor Anto, Ilan Smoly, et al.. (2021). Unraveling the hidden role of a uORF-encoded peptide as a kinase inhibitor of PKCs. Proceedings of the National Academy of Sciences. 118(40). 30 indexed citations
6.
Keasar, Chen, et al.. (2020). Redundancy-weighting the PDB for detailed secondary structure prediction using deep-learning models. Bioinformatics. 36(12). 3733–3738. 7 indexed citations
7.
Elofsson, Arne, Keehyoung Joo, Chen Keasar, et al.. (2017). Methods for estimation of model accuracy in CASP12. Proteins Structure Function and Bioinformatics. 86(S1). 361–373. 27 indexed citations
8.
Voskoboynik, Ayelet, Aaron M. Newman, Daniel Corey, et al.. (2013). Identification of a Colonial Chordate Histocompatibility Gene. Science. 341(6144). 384–387. 59 indexed citations
9.
Schramm, Chaim A., Brett T. Hannigan, Jason E. Donald, et al.. (2012). Knowledge-Based Potential for Positioning Membrane-Associated Structures and Assessing Residue-Specific Energetic Contributions. Structure. 20(5). 924–935. 63 indexed citations
10.
Reshef, Dan, et al.. (2011). Structure‐based identification of catalytic residues. Proteins Structure Function and Bioinformatics. 79(6). 1952–1963. 8 indexed citations
11.
Kedem, Klara, et al.. (2011). A library of protein surface patches discriminates between native structures and decoys generated by structure prediction servers. BMC Structural Biology. 11(1). 20–20. 4 indexed citations
12.
Ohana, Ehud, Eitan Hoch, Chen Keasar, et al.. (2009). Identification of the Zn2+ Binding Site and Mode of Operation of a Mammalian Zn2+ Transporter. Journal of Biological Chemistry. 284(26). 17677–17686. 138 indexed citations
13.
Kalisman, Nir, et al.. (2008). Prediction of structural stability of short beta-hairpin peptides by molecular dynamics and knowledge-based potentials. BMC Structural Biology. 8(1). 27–27. 6 indexed citations
14.
Amir, El-ad David, Nir Kalisman, & Chen Keasar. (2008). Differentiable, multi‐dimensional, knowledge‐based energy terms for torsion angle probabilities and propensities. Proteins Structure Function and Bioinformatics. 72(1). 62–73. 28 indexed citations
15.
Kalisman, Nir, et al.. (2005). MESHI: a new library of Java classes for molecular modeling. Computer applications in the biosciences. 21(20). 3931–3932. 30 indexed citations
16.
Yosef, Ido, et al.. (2004). RNA Binding Activity of the Ribulose-1,5-bisphosphate Carboxylase/Oxygenase Large Subunit from Chlamydomonas reinhardtii. Journal of Biological Chemistry. 279(11). 10148–10156. 44 indexed citations
17.
Zuberek, Joanna, Magdalena Lewdorowicz, Chen Keasar, et al.. (2004). Cap-binding activity of an eIF4E homolog from Leishmania. RNA. 10(11). 1764–1775. 39 indexed citations
18.
Keasar, Chen & Michael Levitt. (2003). A Novel Approach to Decoy Set Generation: Designing a Physical Energy Function Having Local Minima with Native Structure Characteristics. Journal of Molecular Biology. 329(1). 159–174. 77 indexed citations
19.
20.
Keasar, Chen, Ron Elber, & Jeffrey Skolnick. (1997). Simultaneous and coupled energy optimization of homologous proteins: a new tool for structure prediction. PubMed. 2(4). 247–259. 15 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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