Helen Attrill

14.7k total citations
28 papers, 1.0k citations indexed

About

Helen Attrill is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Immunology. According to data from OpenAlex, Helen Attrill has authored 28 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 7 papers in Cellular and Molecular Neuroscience and 4 papers in Immunology. Recurrent topics in Helen Attrill's work include Bioinformatics and Genomic Networks (6 papers), Glycosylation and Glycoproteins Research (4 papers) and Biomedical Text Mining and Ontologies (4 papers). Helen Attrill is often cited by papers focused on Bioinformatics and Genomic Networks (6 papers), Glycosylation and Glycoproteins Research (4 papers) and Biomedical Text Mining and Ontologies (4 papers). Helen Attrill collaborates with scholars based in United Kingdom, United States and Japan. Helen Attrill's co-authors include Paul R. Crocker, Daan M. F. van Aalten, Steven J Marygold, Giulia Antonazzo, Anthony Watts, Alix J. Rey, Joshua L. Goodman, Kathleen Falls, Gillian Millburn and Peter Harding and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Nano Letters.

In The Last Decade

Helen Attrill

27 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Helen Attrill United Kingdom 16 776 284 156 112 77 28 1.0k
Jill Wilken United States 15 546 0.7× 222 0.8× 69 0.4× 146 1.3× 109 1.4× 19 1.2k
Lynn Helena Caporale United States 19 577 0.7× 253 0.9× 45 0.3× 127 1.1× 103 1.3× 35 982
A. V. Belyavsky Russia 21 1.3k 1.7× 137 0.5× 147 0.9× 25 0.2× 53 0.7× 87 1.7k
Dmitry Shcherbo Russia 13 1.4k 1.8× 185 0.7× 366 2.3× 109 1.0× 127 1.6× 19 2.2k
Timothy J. Ragan United Kingdom 16 854 1.1× 80 0.3× 134 0.9× 20 0.2× 25 0.3× 26 1.1k
Cheryl A. Telmer United States 17 710 0.9× 80 0.3× 52 0.3× 70 0.6× 63 0.8× 36 986
T. V. Chepurnykh Russia 7 758 1.0× 51 0.2× 187 1.2× 57 0.5× 67 0.9× 13 1.2k
Adelaine Kwun-Wai Leung United States 13 645 0.8× 39 0.1× 149 1.0× 68 0.6× 56 0.7× 24 979
Csaba Ortutay Finland 16 502 0.6× 147 0.5× 53 0.3× 42 0.4× 15 0.2× 35 703
Ronald Mertz Germany 13 808 1.0× 85 0.3× 230 1.5× 43 0.4× 55 0.7× 13 1.1k

Countries citing papers authored by Helen Attrill

Since Specialization
Citations

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

Fields of papers citing papers by Helen Attrill

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Helen Attrill

This figure shows the co-authorship network connecting the top 25 collaborators of Helen Attrill. A scholar is included among the top collaborators of Helen Attrill 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 Helen Attrill. Helen Attrill 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.
Ontiveros‐Palacios, Nancy, et al.. (2026). GOFlowLLM—curating miRNA literature with large language models and flowcharts. Bioinformatics. 42(1). 1 indexed citations
2.
Hu, Yanhui, Aram Comjean, Helen Attrill, et al.. (2023). PANGEA: a new gene set enrichment tool for Drosophila and common research organisms. Nucleic Acids Research. 51(W1). W419–W426. 29 indexed citations
3.
4.
Liu, Yifang, Joshua Shing Shun Li, Jonathan Rodiger, et al.. (2021). FlyPhoneDB: an integrated web-based resource for cell–cell communication prediction in Drosophila. Genetics. 220(3). 22 indexed citations
5.
Marygold, Steven J, Helen Attrill, Elena Speretta, et al.. (2020). The DNA polymerases of Drosophila melanogaster. Fly. 14(1-4). 49–61. 6 indexed citations
6.
Wood, Valerie, Seth Carbon, Midori A. Harris, et al.. (2020). Term Matrix: a novel Gene Ontology annotation quality control system based on ontology term co-annotation patterns. Open Biology. 10(9). 200149–200149. 6 indexed citations
7.
Attrill, Helen, Pascale Gaudet, Rachael P. Huntley, et al.. (2019). Annotation of gene product function from high-throughput studies using the Gene Ontology. Database. 2019. 20 indexed citations
8.
Rey, Alix J., Helen Attrill, & Steven J Marygold. (2018). Using FlyBase to Find Functionally Related Drosophila Genes. Methods in molecular biology. 1757. 493–512. 7 indexed citations
9.
Marygold, Steven J, Giulia Antonazzo, Helen Attrill, et al.. (2016). Exploring FlyBase Data Using QuickSearch. Current Protocols in Bioinformatics. 56(1). 1.31.1–1.31.23. 5 indexed citations
10.
Marygold, Steven J, Helen Attrill, & Paul Lasko. (2016). The translation factors ofDrosophila melanogaster. Fly. 11(1). 65–74. 15 indexed citations
11.
Alam-Faruque, Yasmin, David P. Hill, Emily Dimmer, et al.. (2014). Representing Kidney Development Using the Gene Ontology. PLoS ONE. 9(6). e99864–e99864. 13 indexed citations
12.
Oates, Joanne, et al.. (2012). The role of cholesterol on the activity and stability of neurotensin receptor 1. Biochimica et Biophysica Acta (BBA) - Biomembranes. 1818(9). 2228–2233. 59 indexed citations
13.
Dorfmueller, Helge C., Wenxia Fang, Francesco Rao, et al.. (2012). Structural and biochemical characterization of a trapped coenzyme A adduct ofCaenorhabditis elegansglucosamine-6-phosphateN-acetyltransferase 1. Acta Crystallographica Section D Biological Crystallography. 68(8). 1019–1029. 13 indexed citations
14.
Attrill, Helen, et al.. (2011). DNA-Templated Protein Arrays for Single-Molecule Imaging. Nano Letters. 11(2). 657–660. 86 indexed citations
15.
Ross, Simon, et al.. (2010). Heterologous high yield expression and purification of neurotensin and its functional fragment in Escherichia coli. Protein Expression and Purification. 74(1). 65–68. 8 indexed citations
16.
Harding, Peter, Helen Attrill, Simon Ross, et al.. (2009). Constitutive Dimerization of the G-Protein Coupled Receptor, Neurotensin Receptor 1, Reconstituted into Phospholipid Bilayers. Biophysical Journal. 96(3). 964–973. 54 indexed citations
17.
Attrill, Helen, Akihiro Imamura, Ritu Sharma, et al.. (2006). Siglec-7 Undergoes a Major Conformational Change When Complexed with the α(2,8)-Disialylganglioside GT1b. Journal of Biological Chemistry. 281(43). 32774–32783. 77 indexed citations
18.
Avril, Tony, Helen Attrill, Jinwei Zhang, Anna Raper, & Paul R. Crocker. (2006). Negative regulation of leucocyte functions by CD33-related siglecs. Biochemical Society Transactions. 34(6). 1024–1027. 40 indexed citations
19.
Avril, Tony, Sylvie Freeman, Helen Attrill, Rosemary G. Clarke, & Paul R. Crocker. (2005). Siglec-5 (CD170) Can Mediate Inhibitory Signaling in the Absence of Immunoreceptor Tyrosine-based Inhibitory Motif Phosphorylation. Journal of Biological Chemistry. 280(20). 19843–19851. 83 indexed citations
20.
Alphey, M.S., Helen Attrill, Paul R. Crocker, & Daan M. F. van Aalten. (2003). High Resolution Crystal Structures of Siglec-7. Journal of Biological Chemistry. 278(5). 3372–3377. 97 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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