Yanay Ofran

4.2k total citations
51 papers, 2.8k citations indexed

About

Yanay Ofran is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Immunology. According to data from OpenAlex, Yanay Ofran has authored 51 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Molecular Biology, 20 papers in Radiology, Nuclear Medicine and Imaging and 12 papers in Immunology. Recurrent topics in Yanay Ofran's work include Monoclonal and Polyclonal Antibodies Research (19 papers), Protein Structure and Dynamics (14 papers) and Bioinformatics and Genomic Networks (13 papers). Yanay Ofran is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (19 papers), Protein Structure and Dynamics (14 papers) and Bioinformatics and Genomic Networks (13 papers). Yanay Ofran collaborates with scholars based in Israel, United States and Australia. Yanay Ofran's co-authors include Burkhard Rost, Vered Kunik, Inbal Sela‐Culang, Bjoern Peters, Marco Punta, Venkatesh Mysore, Shahar Alon, Sharon Fischman, Avner Schlessinger and Rana Samuels and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Yanay Ofran

50 papers receiving 2.7k citations

Peers

Yanay Ofran

RNMI

IMMUN

CTM

Jeliazko R. Jeliazkov United States

Marc Graille France

Piers Nash Canada

Klaas Decanniere Belgium

William P. Russ United States

Berthold Rutz Germany

Narcís Fernández‐Fuentes United Kingdom

Kathryn R. Ely United States

Stephen L. Sazinsky United States

Stephen C. Harrison United States

Jeliazko R. Jeliazkov United States

Yanay Ofran

1.3k ×0.6

496 ×0.6

RNMI

210 ×0.5

IMMUN

137 ×0.4

CTM

239 ×0.8

Citations per year, relative to Yanay Ofran Yanay Ofran (= 1×) peers Jeliazko R. Jeliazkov

Countries citing papers authored by Yanay Ofran

Since Specialization

Citations

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

Fields of papers citing papers by Yanay Ofran

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yanay Ofran

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

Ben‐Shmuel, Aviad, Noah Joseph, Omer Levy, et al.. (2021). Targeting the actin nucleation promoting factor WASp provides a therapeutic approach for hematopoietic malignancies. Nature Communications. 12(1). 5581–5581. 13 indexed citations

Nimrod, Guy, Sharon Fischman, Mark Austin, et al.. (2018). Computational Design of Epitope-Specific Functional Antibodies. Cell Reports. 25(8). 2121–2131.e5. 53 indexed citations

Efroni, Gilat, et al.. (2016). De-novo protein function prediction using DNA binding and RNA binding proteins as a test case. Nature Communications. 7(1). 13424–13424. 18 indexed citations

Ofran, Yanay, et al.. (2015). Understanding differences between synthetic and natural antibodies can help improve antibody engineering. mAbs. 8(2). 278–287. 21 indexed citations

Feiglin, Ariel, et al.. (2014). Co-expression and co-localization of hub proteins and their partners are encoded in protein sequence. Molecular BioSystems. 10(4). 787–794. 1 indexed citations

Sela‐Culang, Inbal, Mohammed Rafii‐El‐Idrissi Benhnia, Michael H. Matho, et al.. (2014). Using a Combined Computational-Experimental Approach to Predict Antibody-Specific B Cell Epitopes. Structure. 22(4). 646–657. 60 indexed citations

Tovia‐Brodie, Oholi, et al.. (2014). Large Scale Analysis of Phenotype-Pathway Relationships Based on GWAS Results. PLoS ONE. 9(7). e100887–e100887. 11 indexed citations

Sela‐Culang, Inbal, et al.. (2013). Large‐scale analysis of somatic hypermutations in antibodies reveals which structural regions, positions and amino acids are modified to improve affinity. FEBS Journal. 281(1). 306–319. 39 indexed citations

Kunik, Vered & Yanay Ofran. (2013). The indistinguishability of epitopes from protein surface is explained by the distinct binding preferences of each of the six antigen-binding loops. Protein Engineering Design and Selection. 26(10). 599–609. 73 indexed citations

10.

Sela‐Culang, Inbal, Vered Kunik, & Yanay Ofran. (2013). The Structural Basis of Antibody-Antigen Recognition. Frontiers in Immunology. 4. 302–302. 368 indexed citations

11.

Kunik, Vered, et al.. (2012). Paratome: an online tool for systematic identification of antigen-binding regions in antibodies based on sequence or structure. Nucleic Acids Research. 40(W1). W521–W524. 108 indexed citations

12.

Kunik, Vered, Bjoern Peters, & Yanay Ofran. (2012). Structural Consensus among Antibodies Defines the Antigen Binding Site. PLoS Computational Biology. 8(2). e1002388–e1002388. 87 indexed citations

13.

Sendiña–Nadal, I., Yanay Ofran, Juan A. Almendral, et al.. (2011). Unveiling Protein Functions through the Dynamics of the Interaction Network. PLoS ONE. 6(3). e17679–e17679. 11 indexed citations

14.

Gophna, Uri & Yanay Ofran. (2010). Lateral acquisition of genes is affected by the friendliness of their products. Proceedings of the National Academy of Sciences. 108(1). 343–348. 13 indexed citations

15.

Ofran, Yanay, et al.. (2009). Large‐scale analysis of secondary structure changes in proteins suggests a role for disorder‐to‐order transitions in nucleotide binding proteins. Proteins Structure Function and Bioinformatics. 78(2). 236–248. 16 indexed citations

16.

Ofran, Yanay, Avner Schlessinger, & Burkhard Rost. (2008). Automated Identification of Complementarity Determining Regions (CDRs) Reveals Peculiar Characteristics of CDRs and B Cell Epitopes. The Journal of Immunology. 181(9). 6230–6235. 66 indexed citations

17.

Punta, Marco & Yanay Ofran. (2008). The Rough Guide to In Silico Function Prediction, or How To Use Sequence and Structure Information To Predict Protein Function. PLoS Computational Biology. 4(10). e1000160–e1000160. 78 indexed citations

18.

Ofran, Yanay & Hanah Margalit. (2006). Proteins of the same fold and unrelated sequences have similar amino acid composition. Proteins Structure Function and Bioinformatics. 64(1). 275–279. 20 indexed citations

19.

Ofran, Yanay, Marco Punta, Reinhard Schneider, & Burkhard Rost. (2005). Beyond annotation transfer by homology: novel protein-function prediction methods to assist drug discovery. Drug Discovery Today. 10(21). 1475–1482. 63 indexed citations

20.

Ofran, Yanay & Burkhard Rost. (2003). Predicted protein–protein interaction sites from local sequence information. FEBS Letters. 544(1-3). 236–239. 192 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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