Matthew E. Hudson

9.8k total citations · 1 hit paper
83 papers, 4.8k citations indexed

About

Matthew E. Hudson is a scholar working on Plant Science, Molecular Biology and Genetics. According to data from OpenAlex, Matthew E. Hudson has authored 83 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Plant Science, 35 papers in Molecular Biology and 14 papers in Genetics. Recurrent topics in Matthew E. Hudson's work include Soybean genetics and cultivation (24 papers), Legume Nitrogen Fixing Symbiosis (23 papers) and Plant Molecular Biology Research (22 papers). Matthew E. Hudson is often cited by papers focused on Soybean genetics and cultivation (24 papers), Legume Nitrogen Fixing Symbiosis (23 papers) and Plant Molecular Biology Research (22 papers). Matthew E. Hudson collaborates with scholars based in United States, China and Brazil. Matthew E. Hudson's co-authors include Peter H. Quail, Kranthi Varala, Brian W. Diers, Chanhong Kim, Klaus Apel, Bassem Al‐Sady, Enamul Huq, Tong Geon Lee, Karen A. Hudson and Kankshita Swaminathan and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Matthew E. Hudson

82 papers receiving 4.7k citations

Hit Papers

Copy Number Variation of Multiple Genes at Rhg1 Mediates ... 2012 2026 2016 2021 2012 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew E. Hudson United States 36 3.4k 2.1k 954 457 432 83 4.8k
Therese Mitros United States 15 3.3k 1.0× 3.3k 1.5× 694 0.7× 170 0.4× 465 1.1× 16 5.6k
Ronan C. O’Malley United States 31 5.0k 1.5× 5.9k 2.7× 1.1k 1.1× 138 0.3× 271 0.6× 56 8.7k
Harm Nijveen Netherlands 20 1.4k 0.4× 1.7k 0.8× 734 0.8× 161 0.4× 265 0.6× 54 3.7k
Katsushi Yamaguchi Japan 36 2.1k 0.6× 1.7k 0.8× 435 0.5× 287 0.6× 469 1.1× 111 3.5k
W. Brad Barbazuk United States 37 3.3k 1.0× 3.6k 1.7× 1.3k 1.3× 98 0.2× 507 1.2× 93 6.2k
Jean‐Marc Aury France 35 1.8k 0.5× 2.7k 1.3× 778 0.8× 241 0.5× 246 0.6× 99 4.1k
Jill Wegrzyn United States 36 1.4k 0.4× 1.8k 0.8× 1.5k 1.5× 173 0.4× 350 0.8× 111 4.0k
Corinne Da Silva France 36 1.2k 0.4× 1.9k 0.9× 490 0.5× 167 0.4× 225 0.5× 81 3.7k
Sang‐Gyu Kim South Korea 34 4.7k 1.4× 4.1k 1.9× 295 0.3× 603 1.3× 309 0.7× 111 5.9k
Kentaro K. Shimizu Japan 40 2.9k 0.9× 2.8k 1.3× 1.1k 1.1× 200 0.4× 1.3k 3.1× 140 5.1k

Countries citing papers authored by Matthew E. Hudson

Since Specialization
Citations

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

Fields of papers citing papers by Matthew E. Hudson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew E. Hudson

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew E. Hudson. A scholar is included among the top collaborators of Matthew E. Hudson 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 E. Hudson. Matthew E. Hudson 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.
Jia, Dong, Stephan Lane, Daniel C. Castro, et al.. (2025). Enhancing lipid production in plant cells through automated high-throughput genome engineering and phenotyping. The Plant Cell. 37(2). 5 indexed citations
2.
Zhang, Zhihai, João Paulo Gomes Viana, Bosen Zhang, et al.. (2024). Major impacts of widespread structural variation on sorghum. Genome Research. 34(2). 286–299. 5 indexed citations
3.
Lee, Tong Geon, et al.. (2024). Impact of Rhg1 copy number variation on a soybean cyst nematode resistance transcriptional network. G3 Genes Genomes Genetics. 2 indexed citations
4.
He, Guo, Xuhong Zhao, Yan Xu, et al.. (2023). An efficient virus‐induced gene silencing (VIGS) system for gene functional studies in Miscanthus. GCB Bioenergy. 15(6). 805–820. 7 indexed citations
5.
Yoshihara, Takeshi, Nathan D. Miller, Fernando A. Rabanal, et al.. (2022). Leveraging orthology within maize and Arabidopsis QTL to identify genes affecting natural variation in gravitropism. Proceedings of the National Academy of Sciences. 119(40). e2212199119–e2212199119. 3 indexed citations
6.
Heldenbrand, Jacob R., et al.. (2022). CROPSR: an automated platform for complex genome-wide CRISPR gRNA design and validation. BMC Bioinformatics. 23(1). 74–74. 12 indexed citations
7.
Heldenbrand, Jacob R., Saurabh Baheti, Matthew A. Bockol, et al.. (2019). Recommendations for performance optimizations when using GATK3.8 and GATK4. BMC Bioinformatics. 20(1). 557–557. 35 indexed citations
8.
Baheti, Saurabh, Matthew A. Bockol, Travis Drucker, et al.. (2019). Sentieon DNASeq Variant Calling Workflow Demonstrates Strong Computational Performance and Accuracy. Frontiers in Genetics. 10. 736–736. 134 indexed citations
9.
Masonbrink, Rick E., Tom Maier, Usha Muppirala, et al.. (2019). The genome of the soybean cyst nematode (Heterodera glycines) reveals complex patterns of duplications involved in the evolution of parasitism genes. BMC Genomics. 20(1). 119–119. 59 indexed citations
10.
Wickland, Daniel P., Gopal Battu, Karen A. Hudson, Brian W. Diers, & Matthew E. Hudson. (2017). A comparison of genotyping-by-sequencing analysis methods on low-coverage crop datasets shows advantages of a new workflow, GB-eaSy. BMC Bioinformatics. 18(1). 586–586. 55 indexed citations
12.
Avalos, Arián, Hailin Pan, Cai Li, et al.. (2017). A soft selective sweep during rapid evolution of gentle behaviour in an Africanized honeybee. Nature Communications. 8(1). 1550–1550. 35 indexed citations
13.
Stephens, Zachary, et al.. (2016). Simulating Next-Generation Sequencing Datasets from Empirical Mutation and Sequencing Models. PLoS ONE. 11(11). e0167047–e0167047. 44 indexed citations
14.
Cook, David E., Tong Geon Lee, Xiaoli Guo, et al.. (2012). Copy Number Variation of Multiple Genes at Rhg1 Mediates Nematode Resistance in Soybean. Science. 338(6111). 1206–1209. 455 indexed citations breakdown →
15.
Schwarz, Dietmar, Hugh M. Robertson, Jeffrey L. Feder, et al.. (2009). Sympatric ecological speciation meets pyrosequencing: sampling the transcriptome of the apple maggot Rhagoletis pomonella. BMC Genomics. 10(1). 633–633. 85 indexed citations
17.
Toth, Amy L., Kranthi Varala, Thomas C. Newman, et al.. (2007). Wasp Gene Expression Supports an Evolutionary Link Between Maternal Behavior and Eusociality. Science. 318(5849). 441–444. 208 indexed citations
18.
Hudson, Matthew E.. (2007). Sequencing breakthroughs for genomic ecology and evolutionary biology. Molecular Ecology Resources. 8(1). 3–17. 285 indexed citations
19.
Huq, Enamul, Bassem Al‐Sady, Matthew E. Hudson, et al.. (2004). PHYTOCHROME-INTERACTING FACTOR 1 Is a Critical bHLH Regulator of Chlorophyll Biosynthesis. Science. 305(5692). 1937–1941. 415 indexed citations
20.
Hudson, Matthew E., Damon Lisch, & Peter H. Quail. (2003). The FHY3 and FAR1 genes encode transposase‐related proteins involved in regulation of gene expression by the phytochrome A‐signaling pathway. The Plant Journal. 34(4). 453–471. 155 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026