Nathan T. Weeks

11.1k total citations
23 papers, 817 citations indexed

About

Nathan T. Weeks is a scholar working on Plant Science, Molecular Biology and Genetics. According to data from OpenAlex, Nathan T. Weeks has authored 23 papers receiving a total of 817 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Plant Science, 10 papers in Molecular Biology and 3 papers in Genetics. Recurrent topics in Nathan T. Weeks's work include Soybean genetics and cultivation (9 papers), Legume Nitrogen Fixing Symbiosis (8 papers) and Genomics and Phylogenetic Studies (3 papers). Nathan T. Weeks is often cited by papers focused on Soybean genetics and cultivation (9 papers), Legume Nitrogen Fixing Symbiosis (8 papers) and Genomics and Phylogenetic Studies (3 papers). Nathan T. Weeks collaborates with scholars based in United States, India and Mali. Nathan T. Weeks's co-authors include Steven B. Cannon, Andrew Farmer, Michelle A. Graham, Gregory D. May, Randy C. Shoemaker, James E. Specht, Perry B. Cregan, Vikas Belamkar, David L. Hyten and Qijian Song and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and Scientific Reports.

In The Last Decade

Nathan T. Weeks

21 papers receiving 807 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nathan T. Weeks United States 12 616 253 163 28 20 23 817
Yue Lu China 19 769 1.2× 462 1.8× 208 1.3× 30 1.1× 22 1.1× 44 943
Yuxiao Chang China 15 468 0.8× 483 1.9× 128 0.8× 18 0.6× 33 1.6× 36 720
Zifeng Guo China 13 477 0.8× 131 0.5× 352 2.2× 29 1.0× 13 0.7× 31 636
Miaoyun Xu China 16 654 1.1× 384 1.5× 70 0.4× 41 1.5× 11 0.6× 38 755
Lanzhi Li China 11 379 0.6× 114 0.5× 289 1.8× 57 2.0× 13 0.7× 30 558
Jordi Moreno‐Romero Spain 17 791 1.3× 582 2.3× 69 0.4× 16 0.6× 24 1.2× 25 904
Lidan Sun China 16 595 1.0× 607 2.4× 181 1.1× 27 1.0× 46 2.3× 59 912
Ajay Kumar Mahato India 14 506 0.8× 208 0.8× 71 0.4× 20 0.7× 14 0.7× 42 585

Countries citing papers authored by Nathan T. Weeks

Since Specialization
Citations

This map shows the geographic impact of Nathan T. Weeks'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 Nathan T. Weeks with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nathan T. Weeks more than expected).

Fields of papers citing papers by Nathan T. Weeks

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nathan T. Weeks. 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 Nathan T. Weeks. The network helps show where Nathan T. Weeks may publish in the future.

Co-authorship network of co-authors of Nathan T. Weeks

This figure shows the co-authorship network connecting the top 25 collaborators of Nathan T. Weeks. A scholar is included among the top collaborators of Nathan T. Weeks 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 Nathan T. Weeks. Nathan T. Weeks 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.
Cameron, Connor, Alan Cleary, Joel Berendzen, et al.. (2022). Doing Genetic and Genomic Biology Using the Legume Information System and Associated Resources. Methods in molecular biology. 2443. 81–100. 4 indexed citations
2.
Berendzen, Joel, Anne V. Brown, Connor Cameron, et al.. (2021). The legume information system and associated online genomic resources. Legume Science. 3(3). 13 indexed citations
3.
Brown, Anne V., Wei Huang, Andrew Wilkey, et al.. (2020). A new decade and new data at SoyBase, the USDA-ARS soybean genetics and genomics database. Nucleic Acids Research. 49(D1). D1496–D1501. 71 indexed citations
4.
Wilkey, Andrew, Nathan T. Weeks, & Anne V. Brown. (2020). LegumeFederation/gcvit: GCViT 1.0. Zenodo (CERN European Organization for Nuclear Research).
5.
Brown, Anne V., Jacqueline Campbell, Teshale Assefa, et al.. (2018). Ten quick tips for sharing open genomic data. PLoS Computational Biology. 14(12). e1006472–e1006472. 8 indexed citations
6.
Weeks, Nathan T. & Glenn R. Luecke. (2017). Optimization of SAMtools sorting using OpenMP tasks. Cluster Computing. 20(3). 1869–1880. 7 indexed citations
7.
8.
Belamkar, Vikas, et al.. (2016). Genomics-assisted characterization of a breeding collection of Apios americana, an edible tuberous legume. Scientific Reports. 6(1). 34908–34908. 20 indexed citations
9.
Kramer, Luke, James E. Koltes, Eric Fritz-Waters, et al.. (2016). Epistatic interactions associated with fatty acid concentrations of beef from angus sired beef cattle. BMC Genomics. 17(1). 891–891. 7 indexed citations
10.
Weeks, Nathan T., Glenn R. Luecke, Li Ma, et al.. (2016). High-performance epistasis detection in quantitative trait GWAS. The International Journal of High Performance Computing Applications. 32(3). 321–336. 18 indexed citations
11.
Boddicker, Rebecca L., James E. Koltes, Eric Fritz-Waters, et al.. (2016). Genome‐wide methylation profile following prenatal and postnatal dietary omega‐3 fatty acid supplementation in pigs. Animal Genetics. 47(6). 658–671. 28 indexed citations
12.
Dash, Sudhansu, Jacqueline Campbell, Ethalinda K. S. Cannon, et al.. (2015). Legume information system (LegumeInfo.org): a key component of a set of federated data resources for the legume family. Nucleic Acids Research. 44(D1). D1181–D1188. 115 indexed citations
13.
Luecke, Glenn R., Nathan T. Weeks, Li Ma, et al.. (2015). Fast Epistasis Detection in Large-Scale GWAS for Intel Xeon Phi Clusters. 2015 IEEE Trustcom/BigDataSE/ISPA. 228–235. 11 indexed citations
14.
Belamkar, Vikas, Nathan T. Weeks, Arvind K. Bharti, et al.. (2014). Comprehensive characterization and RNA-Seq profiling of the HD-Zip transcription factor family in soybean (Glycine max) during dehydration and salt stress. BMC Genomics. 15(1). 950–950. 107 indexed citations
15.
Koesterke, Lars, James E. Koltes, Nathan T. Weeks, et al.. (2014). Discovery of biological networks using an optimized partial correlation coefficient with information theory algorithm on Stampede's Xeon and Xeon Phi processors. Concurrency and Computation Practice and Experience. 26(13). 2178–2190. 9 indexed citations
16.
Kudapa, Himabindu, Arvind K. Bharti, Steven B. Cannon, et al.. (2012). A Comprehensive Transcriptome Assembly of Pigeonpea (Cajanus cajan L.) using Sanger and Second-Generation Sequencing Platforms. Molecular Plant. 5(5). 1020–1028. 62 indexed citations
17.
Severin, Andrew, Yung‐Tsi Bolon, Bindu Joseph, et al.. (2011). Gene expression patterns are correlated with genomic and genic structure in soybean. Genome. 54(1). 10–18. 22 indexed citations
18.
Hyten, David L., Steven B. Cannon, Qijian Song, et al.. (2010). High-throughput SNP discovery through deep resequencing of a reduced representation library to anchor and orient scaffolds in the soybean whole genome sequence. BMC Genomics. 11(1). 38–38. 211 indexed citations
19.
Bolon, Yung‐Tsi, Bindu Joseph, Steven B. Cannon, et al.. (2010). Complementary genetic and genomic approaches help characterize the linkage group I seed protein QTL in soybean. BMC Plant Biology. 10(1). 41–41. 86 indexed citations
20.
Blecher, Stan R., et al.. (1982). Possible homology of ectodermal dysplasia and tabby, and possible role of egf. Abstr.. The Mouseion at the JAXlibrary (Jackson Laboratory). 17. 3 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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