I’ah Donovan-Banfield

647 total citations · 1 hit paper
8 papers, 164 citations indexed

About

I’ah Donovan-Banfield is a scholar working on Infectious Diseases, Epidemiology and Molecular Biology. According to data from OpenAlex, I’ah Donovan-Banfield has authored 8 papers receiving a total of 164 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Infectious Diseases, 3 papers in Epidemiology and 2 papers in Molecular Biology. Recurrent topics in I’ah Donovan-Banfield's work include SARS-CoV-2 and COVID-19 Research (3 papers), COVID-19 Clinical Research Studies (2 papers) and Cytomegalovirus and herpesvirus research (2 papers). I’ah Donovan-Banfield is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (3 papers), COVID-19 Clinical Research Studies (2 papers) and Cytomegalovirus and herpesvirus research (2 papers). I’ah Donovan-Banfield collaborates with scholars based in United Kingdom, United States and Singapore. I’ah Donovan-Banfield's co-authors include Christopher Ruis, Thomas P. Peacock, Hassan Hartman, Theo Sanderson, Alessandra Løchen, David A. Matthews, Julian A. Hiscox, Keith N. Leppard, Andrew S. Turnell and Catherine M. K. Ho and has published in prestigious journals such as Nature, Nucleic Acids Research and PLoS ONE.

In The Last Decade

I’ah Donovan-Banfield

6 papers receiving 164 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.

A molnupiravir-associated mutational signature in global SARS-CoV-2 genomes

2023 97 citations Theo Sanderson, I’ah Donovan-Banfield et al. Nature profile →

Peers

I’ah Donovan-Banfield

ID

MB

GENET

EPIDE

ASZ

Christian Marier United States

Wendong Han China

Sheri Harari Israel

Xianmiao Ye China

Flora Donati France

Annie Bernier Canada

Alison Ciling United States

Kathy Stephens United States

Fabian Hausmann Germany

Zepeng Xu China

Christian Marier United States

I’ah Donovan-Banfield

128 ×1.4

ID

63 ×1.2

MB

26 ×0.7

GENET

28 ×0.8

EPIDE

13 ×0.6

ASZ

Citations per year, relative to I’ah Donovan-Banfield I’ah Donovan-Banfield (= 1×) peers Christian Marier

Countries citing papers authored by I’ah Donovan-Banfield

Since Specialization

Citations

This map shows the geographic impact of I’ah Donovan-Banfield'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 I’ah Donovan-Banfield with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites I’ah Donovan-Banfield more than expected).

Fields of papers citing papers by I’ah Donovan-Banfield

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by I’ah Donovan-Banfield. 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 I’ah Donovan-Banfield. The network helps show where I’ah Donovan-Banfield may publish in the future.

Co-authorship network of co-authors of I’ah Donovan-Banfield

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

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Dong, Xiaofeng, David A. Matthews, Giulia Gallo, et al.. (2025). Using minor variant genomes and machine learning to study the genome biology of SARS-CoV-2 over time. Nucleic Acids Research. 53(4). 1 indexed citations

2.

Chong, Jasmine, Oscar Hou In Chou, Wiyada Wongwiwat, et al.. (2025). A direct RNA-seq-based EBV latency transcriptome offers insights into the biogenesis of EBV gene products. Journal of General Virology. 106(8).

3.

Penrice-Randal, Rebekah, I’ah Donovan-Banfield, Craig W. Duffy, et al.. (2024). SARS-CoV-2 population dynamics in immunocompetent individuals in a closed transmission chain shows genomic diversity over the course of infection. Genome Medicine. 16(1). 89–89. 2 indexed citations

4.

Donovan-Banfield, I’ah, et al.. (2024). ‘Queer in Microbiology’: a Microbiology Society members’ endeavour for creating a safe and inclusive environment for LGBTQIA+ microbiologists. Microbiology. 170(6).

5.

Sanderson, Theo, I’ah Donovan-Banfield, Hassan Hartman, et al.. (2023). A molnupiravir-associated mutational signature in global SARS-CoV-2 genomes. Nature. 623(7987). 594–600. 97 indexed citations breakdown →

6.

Donovan-Banfield, I’ah, Rachel Milligan, Tianyi Gao, et al.. (2022). Direct RNA sequencing of respiratory syncytial virus infected human cells generates a detailed overview of RSV polycistronic mRNA and transcript abundance. PLoS ONE. 17(11). e0276697–e0276697. 10 indexed citations

7.

Donovan-Banfield, I’ah, Andrew S. Turnell, Julian A. Hiscox, Keith N. Leppard, & David A. Matthews. (2020). Deep splicing plasticity of the human adenovirus type 5 transcriptome drives virus evolution. Communications Biology. 3(1). 124–124. 43 indexed citations

8.

Ho, Catherine M. K., I’ah Donovan-Banfield, Li Tan, et al.. (2016). Inhibition of IKKα by BAY61-3606 Reveals IKKα-Dependent Histone H3 Phosphorylation in Human Cytomegalovirus Infected Cells. PLoS ONE. 11(3). e0150339–e0150339. 11 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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