Jaime Prilusky

6.9k total citations · 4 hit papers
40 papers, 5.0k citations indexed

About

Jaime Prilusky is a scholar working on Molecular Biology, Materials Chemistry and Spectroscopy. According to data from OpenAlex, Jaime Prilusky has authored 40 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Molecular Biology, 13 papers in Materials Chemistry and 8 papers in Spectroscopy. Recurrent topics in Jaime Prilusky's work include Protein Structure and Dynamics (15 papers), Enzyme Structure and Function (13 papers) and Genomics and Phylogenetic Studies (8 papers). Jaime Prilusky is often cited by papers focused on Protein Structure and Dynamics (15 papers), Enzyme Structure and Function (13 papers) and Genomics and Phylogenetic Studies (8 papers). Jaime Prilusky collaborates with scholars based in Israel, United States and United Kingdom. Jaime Prilusky's co-authors include Joel L. Sussman, Enrique E. Abola, Israel Silman, Marvin Edelman, V. M. Sobolev, Anatoly Sorokin, N. O. Manning, Clifford E. Felder, J. Beckmann and Orna Man and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Molecular Cell.

In The Last Decade

Jaime Prilusky

40 papers receiving 5.0k citations

Hit Papers

align trajectories

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.

FoldIndex(C): a simple tool to predict whether a given protein sequence is intrinsically unfolded

2005 765 citations Jaime Prilusky, Clifford E. Felder et al. Computer applications in the biosciences profile →
Automated analysis of interatomic contacts in proteins.

1999 693 citations Jaime Prilusky, Enrique E. Abola et al. Bioinformatics profile →
Protein Data Bank (PDB): Database of Three-Dimensional Structural Information of Biological Macromolecules

1998 596 citations Joel L. Sussman, Dawei Lin et al. Acta Crystallographica Section D Biological Crystallography profile →
Automated Structure- and Sequence-Based Design of Proteins for High Bacterial Expression and Stability

2016 411 citations Moshe Goldsmith, Yacov Ashani et al. Molecular Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jaime Prilusky Israel	25	3.9k	859	438	420	357	40	5.0k
Cyril Dominguez United Kingdom	19	4.0k 1.0×	561 0.7×	406 0.9×	304 0.7×	301 0.8×	34	4.6k
Narayanaswamy Srinivasan India	38	3.7k 0.9×	942 1.1×	328 0.7×	429 1.0×	247 0.7×	232	5.1k
Francisco Melo Chile	26	4.0k 1.0×	963 1.1×	501 1.1×	260 0.6×	271 0.8×	70	5.5k
João Rodrigues Netherlands	24	3.6k 0.9×	490 0.6×	567 1.3×	472 1.1×	288 0.8×	42	4.8k
Orly Dym Israel	36	4.1k 1.0×	1.1k 1.3×	297 0.7×	205 0.5×	293 0.8×	76	5.4k
Milton T. Stubbs Germany	41	3.4k 0.9×	511 0.6×	424 1.0×	363 0.9×	607 1.7×	117	5.6k
Ting Ran China	19	4.1k 1.0×	706 0.8×	653 1.5×	227 0.5×	376 1.1×	60	5.7k
Hahnbeom Park United States	29	5.0k 1.3×	1.2k 1.4×	654 1.5×	447 1.1×	267 0.7×	49	6.1k
Robbie P. Joosten Netherlands	23	3.2k 0.8×	1.2k 1.4×	377 0.9×	247 0.6×	272 0.8×	50	4.1k
Benjamin Webb United States	19	5.2k 1.3×	875 1.0×	722 1.6×	495 1.2×	463 1.3×	28	7.1k

Countries citing papers authored by Jaime Prilusky

Since Specialization

Citations

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

Fields of papers citing papers by Jaime Prilusky

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jaime Prilusky

This figure shows the co-authorship network connecting the top 25 collaborators of Jaime Prilusky. A scholar is included among the top collaborators of Jaime Prilusky 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 Jaime Prilusky. Jaime Prilusky 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:

20 of 20 papers shown

Lindner, J, Bareket Dassa, Gil Stelzer, et al.. (2025). UTAP2: an enhanced user-friendly transcriptome and epigenome analysis pipeline. BMC Bioinformatics. 26(1). 79–79. 2 indexed citations

Dey, Sucharita, Jaime Prilusky, & Emmanuel D. Levy. (2022). QSalignWeb: A Server to Predict and Analyze Protein Quaternary Structure. Frontiers in Molecular Biosciences. 8. 787510–787510. 3 indexed citations

Maksimainen, Mirko M., Neil Smith, Ekaterina Biterova, et al.. (2021). IceBear: an intuitive and versatile web application for research-data tracking from crystallization experiment to PDB deposition. Acta Crystallographica Section D Structural Biology. 77(2). 151–163. 17 indexed citations

Zaidman, Daniel, Paul Gehrtz, D. Fearon, et al.. (2021). An automatic pipeline for the design of irreversible derivatives identifies a potent SARS-CoV-2 Mpro inhibitor. Cell chemical biology. 28(12). 1795–1806.e5. 52 indexed citations

Khersonsky, Olga, Rosalie Lipsh‐Sokolik, Ziv Avizemer, et al.. (2018). Automated Design of Efficient and Functionally Diverse Enzyme Repertoires. Molecular Cell. 72(1). 178–186.e5. 192 indexed citations

Ben‐Dor, Shifra, Jaime Prilusky, Bareket Dassa, et al.. (2016). The Development of a Novel qPCR Assay-Set for Identifying Fecal Contamination Originating from Domestic Fowls and Waterfowl in Israel. Frontiers in Microbiology. 7. 145–145. 21 indexed citations

Tsvetkov, Peter, Nadav Myers, Oren Moscovitz, et al.. (2011). Thermo-resistant intrinsically disordered proteins are efficient 20S proteasome substrates. Molecular BioSystems. 8(1). 368–373. 37 indexed citations

Hodis, Eran, Jaime Prilusky, & Joel L. Sussman. (2010). Proteopedia: A collaborative, virtual 3D web‐resource for protein and biomolecule structure and function. Biochemistry and Molecular Biology Education. 38(5). 341–342. 13 indexed citations

Prilusky, Jaime, et al.. (2009). Assessment of disorder predictions in CASP8. Proteins Structure Function and Bioinformatics. 77(S9). 210–216. 105 indexed citations

10.

Frenkel‐Morgenstern, Milana, Ariel Cohen, Naama Geva‐Zatorsky, et al.. (2009). Dynamic Proteomics: a database for dynamics and localizations of endogenous fluorescently-tagged proteins in living human cells. Nucleic Acids Research. 38(suppl_1). D508–D512. 22 indexed citations

11.

Hodis, Eran, Jaime Prilusky, Eric Martz, et al.. (2008). Proteopedia- a scientific 'wiki' bridging the rift between three-dimensional structure and function of biomacromolecules. Genome biology. 9(8). R121–R121. 64 indexed citations

12.

Felder, Clifford E., et al.. (2007). A server and database for dipole moments of proteins. Nucleic Acids Research. 35(Web Server). W512–W521. 162 indexed citations

13.

Esnouf, Robert, Rebecca Hamer, Joel L. Sussman, et al.. (2006). Honing the in silico toolkit for detecting protein disorder. Acta Crystallographica Section D Biological Crystallography. 62(10). 1260–1266. 23 indexed citations

14.

Jaakola, Veli‐Pekka, Jaime Prilusky, Joel L. Sussman, & Adrian Goldman. (2005). G protein-coupled receptors show unusual patterns of intrinsic unfolding. Protein Engineering Design and Selection. 18(2). 103–110. 43 indexed citations

15.

Prilusky, Jaime, Clifford E. Felder, Tzviya Zeev‐Ben‐Mordehai, et al.. (2005). FoldIndex(C): a simple tool to predict whether a given protein sequence is intrinsically unfolded. Computer applications in the biosciences. 21(16). 3435–3438. 765 indexed citations breakdown →

16.

Prilusky, Jaime, Nathalie Ulryck, Anne Pajon, et al.. (2005). HalX: an open-source LIMS (Laboratory Information Management System) for small- to large-scale laboratories. Acta Crystallographica Section D Biological Crystallography. 61(6). 671–678. 19 indexed citations

17.

Albeck, Shira, Yigal Burstein, Orly Dym, et al.. (2005). Three-dimensional structure determination of proteins related to human health in their functional context at The Israel Structural Proteomics Center (ISPC). Acta Crystallographica Section D Biological Crystallography. 61(10). 1364–1372. 3 indexed citations

18.

Rebhan, Michael, Vered Chalifa‐Caspi, Jaime Prilusky, & Doron Lancet. (1998). GeneCards: a novel functional genomics compendium with automated data mining and query reformulation support.. Bioinformatics. 14(8). 656–664. 351 indexed citations

19.

Sussman, Joel L., Dawei Lin, Jiansheng Jiang, et al.. (1998). Protein Data Bank (PDB): Database of Three-Dimensional Structural Information of Biological Macromolecules. Acta Crystallographica Section D Biological Crystallography. 54(6). 1078–1084. 596 indexed citations breakdown →

20.

Rebhan, Michael & Jaime Prilusky. (1997). Rapid access to biomedical knowledge with GeneCards and HotMolecBase: Implications for the electrophoretic analysis of large sets of gene products. Electrophoresis. 18(15). 2774–2780. 8 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