Matthew G. Durrant

2.1k total citations · 2 hit papers
16 papers, 674 citations indexed

About

Matthew G. Durrant is a scholar working on Molecular Biology, Genetics and Plant Science. According to data from OpenAlex, Matthew G. Durrant has authored 16 papers receiving a total of 674 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 3 papers in Genetics and 2 papers in Plant Science. Recurrent topics in Matthew G. Durrant's work include RNA and protein synthesis mechanisms (8 papers), CRISPR and Genetic Engineering (7 papers) and Genetic Associations and Epidemiology (3 papers). Matthew G. Durrant is often cited by papers focused on RNA and protein synthesis mechanisms (8 papers), CRISPR and Genetic Engineering (7 papers) and Genetic Associations and Epidemiology (3 papers). Matthew G. Durrant collaborates with scholars based in United States, Germany and Japan. Matthew G. Durrant's co-authors include Ami S. Bhatt, Stephen B. Montgomery, Benjamin A. Siranosian, Michelle M. Li, Patrick D. Hsu, Nicholas T. Perry, Silvana Konermann, April Pawluk, Sita S. Chandrasekaran and Peter Lotfy and has published in prestigious journals such as Nature, Science and Nature Biotechnology.

In The Last Decade

Matthew G. Durrant

16 papers receiving 668 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.

Sequence modeling and design from molecular to genome scale with Evo

2024 127 citations Michael Poli, Matthew G. Durrant et al. Science profile →
Bridge RNAs direct programmable recombination of target and donor DNA

2024 67 citations Matthew G. Durrant, Nicholas T. Perry et al. Nature profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthew G. Durrant United States	11	460	116	75	69	60	16	674
Rolf Hilker Germany	11	425 0.9×	133 1.1×	103 1.4×	98 1.4×	74 1.2×	12	566
Eszter Ari Hungary	14	282 0.6×	73 0.6×	63 0.8×	29 0.4×	49 0.8×	22	478
Anubrata Ghosal United States	13	479 1.0×	123 1.1×	165 2.2×	137 2.0×	41 0.7×	18	721
John Beaulaurier United States	8	461 1.0×	106 0.9×	203 2.7×	87 1.3×	46 0.8×	11	626
Emil A. Sørensen Denmark	3	363 0.8×	55 0.5×	134 1.8×	74 1.1×	25 0.4×	3	490
Fuzhou Ye China	14	421 0.9×	130 1.1×	66 0.9×	42 0.6×	33 0.6×	23	575
Andrey Kislyuk United States	10	634 1.4×	112 1.0×	172 2.3×	100 1.4×	19 0.3×	11	776
Zhewen Zhang China	13	250 0.5×	45 0.4×	52 0.7×	38 0.6×	38 0.6×	26	480
Huiguang Yi China	13	226 0.5×	65 0.6×	61 0.8×	42 0.6×	141 2.4×	18	465
Pengxia Wang China	15	377 0.8×	127 1.1×	185 2.5×	67 1.0×	111 1.9×	34	649

Countries citing papers authored by Matthew G. Durrant

Since Specialization

Citations

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

Fields of papers citing papers by Matthew G. Durrant

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew G. Durrant. 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 Matthew G. Durrant. The network helps show where Matthew G. Durrant may publish in the future.

Co-authorship network of co-authors of Matthew G. Durrant

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

All Works

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16 of 16 papers shown

Fanton, Alison, Jade Martins, Laine Goudy, et al.. (2025). Site-specific DNA insertion into the human genome with engineered recombinases. Nature Biotechnology. 1 indexed citations

Perry, Nicholas T., Dhruva Katrekar, Matthew G. Durrant, et al.. (2025). Megabase-scale human genome rearrangement with programmable bridge recombinases. Science. 391(6790). eadz0276–eadz0276. 5 indexed citations

Hiraizumi, Masahiro, Nicholas T. Perry, Matthew G. Durrant, et al.. (2024). Structural mechanism of bridge RNA-guided recombination. Nature. 630(8018). 994–1002. 31 indexed citations

Durrant, Matthew G., Nicholas T. Perry, Aditya R. Jangid, et al.. (2024). Bridge RNAs direct programmable recombination of target and donor DNA. Nature. 630(8018). 984–993. 67 indexed citations breakdown →

Poli, Michael, Matthew G. Durrant, Brian Kang, et al.. (2024). Sequence modeling and design from molecular to genome scale with Evo. Science. 386(6723). eado9336–eado9336. 127 indexed citations breakdown →

Lotfy, Peter, Emily A. Gibson, Sita S. Chandrasekaran, et al.. (2023). Deep learning and CRISPR-Cas13d ortholog discovery for optimized RNA targeting. Cell Systems. 14(12). 1087–1102.e13. 37 indexed citations

Gloudemans, Michael J., Brunilda Balliu, Daniel Nachun, et al.. (2022). Integration of genetic colocalizations with physiological and pharmacological perturbations identifies cardiometabolic disease genes. Genome Medicine. 14(1). 31–31. 10 indexed citations

Durrant, Matthew G., Alison Fanton, Josh Tycko, et al.. (2022). Systematic discovery of recombinases for efficient integration of large DNA sequences into the human genome. Nature Biotechnology. 41(4). 488–499. 102 indexed citations

Smail, Craig, Nicole M. Ferraro, Qin Hui, et al.. (2022). Integration of rare expression outlier-associated variants improves polygenic risk prediction. The American Journal of Human Genetics. 109(6). 1055–1064. 13 indexed citations

10.

Haigh, Ivan D., et al.. (2022). Digitising historical sea level records in the Thames Estuary, UK. Scientific Data. 9(1). 3 indexed citations

11.

Balliu, Brunilda, Ivan Carcamo‐Orive, Michael J. Gloudemans, et al.. (2021). An integrated approach to identify environmental modulators of genetic risk factors for complex traits. The American Journal of Human Genetics. 108(10). 1866–1879. 16 indexed citations

12.

Durrant, Matthew G. & Ami S. Bhatt. (2020). Automated Prediction and Annotation of Small Open Reading Frames in Microbial Genomes. Cell Host & Microbe. 29(1). 121–131.e4. 32 indexed citations

13.

Balliu, Brunilda, Matthew G. Durrant, Nathan S. Abell, et al.. (2019). Genetic regulation of gene expression and splicing during a 10-year period of human aging. Genome biology. 20(1). 230–230. 47 indexed citations

14.

Durrant, Matthew G., Michelle M. Li, Benjamin A. Siranosian, Stephen B. Montgomery, & Ami S. Bhatt. (2019). A Bioinformatic Analysis of Integrative Mobile Genetic Elements Highlights Their Role in Bacterial Adaptation. Cell Host & Microbe. 27(1). 140–153.e9. 145 indexed citations

15.

Durrant, Matthew G., et al.. (2017). Evidence of an evolutionary hourglass pattern in herbivory‐induced transcriptomic responses. New Phytologist. 215(3). 1264–1273. 9 indexed citations

16.

Durrant, Matthew G., Dennis L. Eggett, & David D. Busath. (2015). Investigation of a recent rise of dual amantadine-resistance mutations in the influenza A M2 sequence. BMC Genetics. 16(Suppl 2). S3–S3. 29 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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