Trisha L. Bailey

8.0k total citations · 3 hit papers
17 papers, 6.3k citations indexed

About

Trisha L. Bailey is a scholar working on Molecular Biology, Public Health, Environmental and Occupational Health and Ecology. According to data from OpenAlex, Trisha L. Bailey has authored 17 papers receiving a total of 6.3k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 7 papers in Public Health, Environmental and Occupational Health and 3 papers in Ecology. Recurrent topics in Trisha L. Bailey's work include Reproductive Biology and Fertility (7 papers), Physiological and biochemical adaptations (3 papers) and Insect and Arachnid Ecology and Behavior (3 papers). Trisha L. Bailey is often cited by papers focused on Reproductive Biology and Fertility (7 papers), Physiological and biochemical adaptations (3 papers) and Insect and Arachnid Ecology and Behavior (3 papers). Trisha L. Bailey collaborates with scholars based in United Kingdom, United States and France. Trisha L. Bailey's co-authors include Charles Elkan, Michael Gribskov, Matthew I. Gibson, Christopher D. Stubbs, B. Graham, Caroline I. Biggs, Alice E. R. Fayter, John J. O’Shea, Mark J. Smyth and Daniel W. McVicar and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Angewandte Chemie International Edition and Nature Communications.

In The Last Decade

Trisha L. Bailey

17 papers receiving 6.1k citations

Hit Papers

Fitting a mixture model by expectation maximization to di... 1994 2026 2004 2015 1994 1998 1995 1000 2.0k 3.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Trisha L. Bailey United Kingdom 14 4.5k 1.5k 820 463 358 17 6.3k
Renata C. Geer United States 10 3.9k 0.9× 1.9k 1.3× 653 0.8× 828 1.8× 419 1.2× 12 6.4k
Penny Coggill United Kingdom 16 5.4k 1.2× 1.7k 1.1× 1.0k 1.2× 974 2.1× 595 1.7× 23 7.7k
Stefan Götz Germany 21 3.2k 0.7× 2.4k 1.6× 960 1.2× 786 1.7× 497 1.4× 54 7.2k
Jaap Heringa Netherlands 12 4.3k 1.0× 950 0.6× 837 1.0× 531 1.1× 304 0.8× 29 6.1k
Nicola Buso United Kingdom 5 3.1k 0.7× 944 0.6× 594 0.7× 582 1.3× 421 1.2× 5 5.2k
Balaji Santhanam United States 35 4.2k 0.9× 676 0.5× 596 0.7× 514 1.1× 382 1.1× 59 5.5k
Noreen R. Gonzales United States 14 4.3k 0.9× 2.1k 1.4× 640 0.8× 867 1.9× 473 1.3× 18 6.8k
Jean‐Charles Sanchez Switzerland 5 3.6k 0.8× 1.1k 0.8× 433 0.5× 406 0.9× 616 1.7× 6 5.4k
Peter Cock United Kingdom 24 4.4k 1.0× 2.2k 1.5× 985 1.2× 1.0k 2.2× 299 0.8× 59 7.4k
Fábio Madeira United Kingdom 9 3.2k 0.7× 916 0.6× 600 0.7× 573 1.2× 430 1.2× 14 5.4k

Countries citing papers authored by Trisha L. Bailey

Since Specialization
Citations

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

Fields of papers citing papers by Trisha L. Bailey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Trisha L. Bailey. 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 Trisha L. Bailey. The network helps show where Trisha L. Bailey may publish in the future.

Co-authorship network of co-authors of Trisha L. Bailey

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

All Works

17 of 17 papers shown
1.
Bailey, Trisha L., Juan R. Hernández‐Fernaud, & Matthew I. Gibson. (2021). Proline pre-conditioning of cell monolayers increases post-thaw recovery and viability by distinct mechanisms to other osmolytes. RSC Medicinal Chemistry. 12(6). 982–993. 15 indexed citations
2.
Bailey, Trisha L., et al.. (2019). Synthetically Scalable Poly(ampholyte) Which Dramatically Enhances Cellular Cryopreservation. Biomacromolecules. 20(8). 3104–3114. 45 indexed citations
3.
Stubbs, Christopher D., Trisha L. Bailey, Kathryn A. Murray, & Matthew I. Gibson. (2019). Polyampholytes as Emerging Macromolecular Cryoprotectants. Biomacromolecules. 21(1). 7–17. 89 indexed citations
4.
Tomás, Ruben M. F., Trisha L. Bailey, Muhammad Hasan, & Matthew I. Gibson. (2019). Extracellular Antifreeze Protein Significantly Enhances the Cryopreservation of Cell Monolayers. Biomacromolecules. 20(10). 3864–3872. 55 indexed citations
5.
Bailey, Trisha L., et al.. (2018). Bio-inspired cell cryopreservation using synthetic analogues. Cryobiology. 85. 129–129. 1 indexed citations
6.
Tomás, Ruben M. F., et al.. (2018). Engineering Cell Surfaces by Covalent Grafting of Synthetic Polymers to Metabolically-Labeled Glycans. ACS Macro Letters. 7(11). 1289–1294. 25 indexed citations
7.
Biggs, Caroline I., Trisha L. Bailey, B. Graham, et al.. (2017). Polymer mimics of biomacromolecular antifreezes. Nature Communications. 8(1). 1546–1546. 208 indexed citations
8.
Graham, B., et al.. (2017). Polyproline as a Minimal Antifreeze Protein Mimic That Enhances the Cryopreservation of Cell Monolayers. Angewandte Chemie. 129(50). 16157–16160. 14 indexed citations
9.
Guy, Collette S., Gemma L. Kay, Daniel J. Phillips, et al.. (2017). Identification of the anti‐mycobacterial functional properties of piperidinol derivatives. British Journal of Pharmacology. 174(14). 2183–2193. 8 indexed citations
10.
Graham, B., et al.. (2017). Polyproline as a Minimal Antifreeze Protein Mimic That Enhances the Cryopreservation of Cell Monolayers. Angewandte Chemie International Edition. 56(50). 15941–15944. 115 indexed citations
11.
Bailey, Trisha L., et al.. (2015). Protective effects of osmolytes in cryopreserving adherent neuroblastoma (Neuro-2a) cells. Cryobiology. 71(3). 472–480. 36 indexed citations
12.
Grundy, William Noble & Trisha L. Bailey. (1999). Family pairwise search with embedded motif models.. Bioinformatics. 15(6). 463–470. 12 indexed citations
13.
Bailey, Trisha L. & Michael Gribskov. (1998). Combining evidence using p-values: application to sequence homology searches.. Bioinformatics. 14(1). 48–54. 963 indexed citations breakdown →
14.
Bailey, Trisha L. & Charles Elkan. (1995). The value of prior knowledge in discovering motifs with MEME.. PubMed. 3. 21–9. 532 indexed citations breakdown →
15.
Bailey, Trisha L. & Charles Elkan. (1994). Fitting a mixture model by expectation maximization to discover motifs in biopolymers.. PubMed. 2. 28–36. 3966 indexed citations breakdown →
16.
O’Shea, John J., Daniel W. McVicar, Trisha L. Bailey, Christopher M. Burns, & Mark J. Smyth. (1992). Activation of human peripheral blood T lymphocytes by pharmacological induction of protein-tyrosine phosphorylation.. Proceedings of the National Academy of Sciences. 89(21). 10306–10310. 155 indexed citations
17.
O’Shea, John J., Jonathan D. Ashwell, Trisha L. Bailey, et al.. (1991). Expression of v-src in a murine T-cell hybridoma results in constitutive T-cell receptor phosphorylation and interleukin 2 production.. Proceedings of the National Academy of Sciences. 88(5). 1741–1745. 25 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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