Maya Elgrably‐Weiss

24 total papers · 1.1k total citations
17 papers, 817 citations indexed

About

Maya Elgrably‐Weiss is a scholar working on Molecular Biology, Genetics and Ecology. According to data from OpenAlex, Maya Elgrably‐Weiss has authored 17 papers receiving a total of 817 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 9 papers in Genetics and 6 papers in Ecology. Recurrent topics in Maya Elgrably‐Weiss's work include Bacterial Genetics and Biotechnology (8 papers), RNA and protein synthesis mechanisms (7 papers) and Bacteriophages and microbial interactions (6 papers). Maya Elgrably‐Weiss is often cited by papers focused on Bacterial Genetics and Biotechnology (8 papers), RNA and protein synthesis mechanisms (7 papers) and Bacteriophages and microbial interactions (6 papers). Maya Elgrably‐Weiss collaborates with scholars based in Israel, Germany and United States. Maya Elgrably‐Weiss's co-authors include Shoshy Altuvia, Ilan Rosenshine, Kobi Baruch, Hanah Margalit, Ruth Hershberg, Gilly Padalon‐Brauch, Éric Westhof, Ron Kohen, Jörg Vogel and Cecília M. Abe 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

Maya Elgrably‐Weiss

17 papers receiving 808 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Maya Elgrably‐Weiss 500 407 257 205 115 17 817
R E Gill 514 1.0× 436 1.1× 189 0.7× 356 1.7× 85 0.7× 12 1000
Tyler G. Kimbrough 414 0.8× 467 1.1× 177 0.7× 356 1.7× 146 1.3× 12 923
Javier López‐Garrido 429 0.9× 356 0.9× 320 1.2× 111 0.5× 150 1.3× 23 757
Thomas Hindré 556 1.1× 381 0.9× 136 0.5× 209 1.0× 179 1.6× 21 951
Erin R. Murphy 486 1.0× 322 0.8× 144 0.6× 211 1.0× 80 0.7× 30 850
D Liu 384 0.8× 312 0.8× 284 1.1× 297 1.4× 173 1.5× 8 797
James J. Barondess 428 0.9× 423 1.0× 294 1.1× 175 0.9× 67 0.6× 8 715
L. K. Romana 410 0.8× 294 0.7× 293 1.1× 258 1.3× 229 2.0× 13 827
Simanti Datta 618 1.2× 477 1.2× 214 0.8× 191 0.9× 84 0.7× 9 915
Laura M. Faure 435 0.9× 367 0.9× 187 0.7× 240 1.2× 98 0.9× 11 805

Countries citing papers authored by Maya Elgrably‐Weiss

Since Specialization
Citations

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

Fields of papers citing papers by Maya Elgrably‐Weiss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maya Elgrably‐Weiss. 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 Maya Elgrably‐Weiss. The network helps show where Maya Elgrably‐Weiss may publish in the future.

Co-authorship network of co-authors of Maya Elgrably‐Weiss

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

All Works

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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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