Layla Hirsh

5.4k total citations · 1 hit paper
11 papers, 3.3k citations indexed

About

Layla Hirsh is a scholar working on Molecular Biology, Materials Chemistry and Cellular and Molecular Neuroscience. According to data from OpenAlex, Layla Hirsh has authored 11 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 4 papers in Materials Chemistry and 1 paper in Cellular and Molecular Neuroscience. Recurrent topics in Layla Hirsh's work include Protein Structure and Dynamics (7 papers), RNA and protein synthesis mechanisms (7 papers) and Enzyme Structure and Function (4 papers). Layla Hirsh is often cited by papers focused on Protein Structure and Dynamics (7 papers), RNA and protein synthesis mechanisms (7 papers) and Enzyme Structure and Function (4 papers). Layla Hirsh collaborates with scholars based in Peru, Italy and Argentina. Layla Hirsh's co-authors include Silvio C. E. Tosatto, Damiano Piovesan, Lisanna Paladin, Alex Bateman, Matloob Qureshi, Jaina Mistry, Sara El-Gebali, Erik L. L. Sonnhammer, Sean R. Eddy and ROBERT FINN and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and Journal of Structural Biology.

In The Last Decade

Layla Hirsh

10 papers receiving 3.3k 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.

The Pfam protein families database in 2019

2018 3.2k citations Sara El-Gebali, Jaina Mistry et al. Nucleic Acids Research profile →

Peers

Layla Hirsh

MB

PS

ECOLO

GENET

IS

Sara El-Gebali Switzerland

Sara Chuguransky Argentina

Chris Boursnell United Kingdom

Shriya Raj United States

Fu Lu United States

Tamer Gür United Kingdom

Zhouxi Wang United States

Joon Lee South Korea

Mingzhang Yang United States

Laurent Falquet Switzerland

Sara El-Gebali Switzerland

Layla Hirsh

2.2k ×1.0

MB

1.1k ×1.0

PS

490 ×1.0

ECOLO

368 ×1.0

GENET

162 ×1.0

IS

Citations per year, relative to Layla Hirsh Layla Hirsh (= 1×) peers Sara El-Gebali

Countries citing papers authored by Layla Hirsh

Since Specialization

Citations

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

Fields of papers citing papers by Layla Hirsh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Layla Hirsh

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

Hirsh, Layla, et al.. (2025). BAV-LLPS: a database of bacterial, archaea, and virus liquid–liquid phase separation proteins. Bioinformatics. 41(10).

2.

Monzón, Alexander Miguel, Arne Elofsson, Pablo Mier, et al.. (2023). A STRP-ed definition of Structured Tandem Repeats in Proteins. Journal of Structural Biology. 215(4). 108023–108023. 6 indexed citations

3.

Escobedo, Nahuel, et al.. (2022). CoDNaS-Q: a database of conformational diversity of the native state of proteins with quaternary structure. Bioinformatics. 38(21). 4959–4961. 3 indexed citations

4.

Hirsh, Layla, et al.. (2021). CoDNaS-RNA: a database of conformational diversity in the native state of RNA. Bioinformatics. 38(6). 1745–1748. 2 indexed citations

5.

Monzón, Alexander Miguel, et al.. (2020). Revenant: a database of resurrected proteins. Database. 2020. 6 indexed citations

6.

El-Gebali, Sara, Jaina Mistry, Alex Bateman, et al.. (2018). The Pfam protein families database in 2019. Nucleic Acids Research. 47(D1). D427–D432. 3202 indexed citations breakdown →

7.

Hirsh, Layla, Lisanna Paladin, Damiano Piovesan, & Silvio C. E. Tosatto. (2018). RepeatsDB-lite: a web server for unit annotation of tandem repeat proteins. Nucleic Acids Research. 46(W1). W402–W407. 17 indexed citations

8.

Roche, Daniel B., et al.. (2017). Classification of β-hairpin repeat proteins. Journal of Structural Biology. 201(2). 130–138. 15 indexed citations

9.

Paladin, Lisanna, Layla Hirsh, Damiano Piovesan, et al.. (2016). RepeatsDB 2.0: improved annotation, classification, search and visualization of repeat protein structures. Nucleic Acids Research. 45(D1). D308–D312. 27 indexed citations

10.

Hirsh, Layla, Damiano Piovesan, Lisanna Paladin, & Silvio C. E. Tosatto. (2016). Identification of repetitive units in protein structures with ReUPred. Amino Acids. 48(6). 1391–1400. 10 indexed citations

11.

Hirsh, Layla, Damiano Piovesan, Manuel Giollo, Carlo Ferrari, & Silvio C. E. Tosatto. (2014). The Victor C++ library for protein representation and advanced manipulation. Bioinformatics. 31(7). 1138–1140. 5 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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