Research Project: GrainGenes: Enabling Data Access and Sustainability for Small Grains Researchers

Location: Crop Improvement and Genetics Research

Publications (Clicking on the reprint icon will take you to the publication reprint.)

Wheat data integration and applications: IWGSC, GrainGenes, Ensembl, and other data repositories - (Book / Chapter)
Alaux, M., Dyer, S., Sen, T.Z. 2023. Wheat data integration and applications: IWGSC, GrainGenes, Ensembl, and other data repositories. Book Chapter. https://doi.org/10.1007/978-3-031-38294-9_2.

Co-expression pan-network reveals genes involved in complex traits within maize pan-genome - (Peer Reviewed Journal)
Cagirici, B.H., Andorf, C.M., Sen, T.Z. 2022. Co-expression pan-network reveals genes involved in complex traits within maize pan-genome. BMC Plant Biology. 22. Article 595. https://doi.org/10.1186/s12870-022-03985-z.

G4Boost: A machine learning-based tool for quadruplex identification and stability prediction - (Peer Reviewed Journal)
Cagirici, H.B., Budak, H., Sen, T.Z. 2022. G4Boost: A machine learning-based tool for quadruplex identification and stability prediction. BMC Bioinformatics. 23. Article 240. https://doi.org/10.1186/s12859-022-04782-z.

Experimental and computational studies of cellulases as bioethanol enzymes - (Peer Reviewed Journal)
Ranganathan, S., Mahesh, S., Suresh, S., Nagarajan, A., Sen, T.Z., Yennamalli, R.M. 2022. Experimental and computational studies of cellulases as bioethanol enzymes. Bioengineered. 13(5):14028-14046. https://doi.org/10.1080/21655979.2022.2085541.

Predicting tissue-specific mRNA and protein abundance in maize: A machine learning approach - (Peer Reviewed Journal)
Cho, K., Sen, T.Z., Andorf, C.M. 2022. Predicting tissue-specific mRNA and protein abundance in maize: A machine learning approach. Frontiers in Artificial Intelligence. 5. Article 830170. https://doi.org/10.3389/frai.2022.830170.

GrainGenes: Tools and content to assist breeders improving oat quality - (Peer Reviewed Journal)
Blake, V.C., Wight, C.P., Yao, E., Sen, T.Z. 2022. GrainGenes: Tools and content to assist breeders improving oat quality. Foods. 11(7). Article 914. https://doi.org/10.3390/foods11070914.

Multiple variant calling pipelines in wheat whole exome sequencing - (Peer Reviewed Journal)
Cagirici, B.H., Akpinar, B., Sen, T.Z., Budak, H. 2021. Multiple variant calling pipelines in wheat whole exome sequencing. International Journal of Molecular Sciences. 22(19). Article 10400. https://doi.org/10.3390/ijms221910400.

mirMachine: a one-stop shop for plant miRNA annotation - (Peer Reviewed Journal)
Cagirici, B.H., Sen, T.Z., Budak, H. 2021. mirMachine: a one-stop shop for plant miRNA annotation. The Journal of Visualized Experiments (JoVE). (171). Article e62430. https://www.doi.org/10.3791/62430.

Genome-wide discovery of G-quadruplexes in barley - (Peer Reviewed Journal)
Cagirici, B.H., Budak, H., Sen, T.Z. 2021. Genome-wide discovery of G-quadruplexes in barley. Scientific Reports. 11. Article 7876. https://doi.org/10.1038/s41598-021-86838-3.

Building a successful international research community through data sharing: the case of wheat information system (WheatIS) - (Peer Reviewed Journal)
Sen, T.Z., Caccamo, M., Edwards, D., Quesneville, H. 2020. Building a successful international research community through data sharing: the case of wheat information system (WheatIS). F1000Research. 9. Article 536. https://doi.org/10.12688/f1000research.23525.1.

LncMachine: a machine learning algorithm for long noncoding RNA annotation in plants - (Peer Reviewed Journal)
Cagirici, B.H., Galvez, S., Sen, T.Z., Budak, H. 2021. LncMachine: a machine learning algorithm for long noncoding RNA annotation in plants. Functional and Integrative Genomics. 21:195-204. https://doi.org/10.1007/s10142-021-00769-w.

LncMachine: a machine learning algorithm for long noncoding RNA annotation in plants - (Peer Reviewed Journal)
Cagirici, B.H., Galvez, S., Sen, T.Z., Budak, H. 2021. LncMachine: a machine learning algorithm for long noncoding RNA annotation in plants. Functional and Integrative Genomics. 21(1): 195-204. https://doi.org/10.1007/s10142-021-00769-w.

JBrowse Connect: a server API to connect JBrowse instances and users - (Peer Reviewed Journal)
Yao, E., Buels, R., Stein, L., Sen, T.Z., Holmes, I. 2020. JBrowse Connect: a server API to connect JBrowse instances and users. PLoS Computational Biology. 16(8). https://doi.org/10.1371/journal.pcbi.1007261.

Genome-wide discovery of G-quadruplexes in wheat: distribution and putative functional roles - (Peer Reviewed Journal)
Cagirici, H., Sen, T.Z. 2020. Genome-wide discovery of G-quadruplexes in wheat: distribution and putative functional roles. G3, Genes/Genomes/Genetics. 10(6). https://doi.org/10.1534/g3.120.401288.

Tissue-specific gene expression and protein abundance patterns are associated with fractionation bias in maize - (Peer Reviewed Journal)
Walsh, J.R., Woodhouse, M.R., Andorf, C.M., Sen, T.Z. 2020. Tissue-specific gene expression and protein abundance patterns are associated with fractionation bias in maize. Biomed Central (BMC) Plant Biology. 20. https://doi.org/10.1186/s12870-019-2218-8.

GrainGenes: centralized small grain resources and digital platform for geneticists and breeders - (Peer Reviewed Journal)
Blake, V.C., Woodhouse, M.R., Lazo, G.R., Odell, S.G., Wight, C.W., Tinker, N.A., Wang, Y., Gu, Y.Q., Birkett, C.L., Jannink, J., Matthews, D.E., Hane, D.L., Michel, S.L., Yao, E., Sen, T.Z. 2019. GrainGenes: centralized small grain resources and digital platform for geneticists and breeders. Database: The Journal of Biological Databases and Curation. 2019.

PedigreeNet: A web-based pedigree viewer for biological databases - (Peer Reviewed Journal)
Braun, B.L., Schott, D.A., Portwood Ii, J.L., Andorf, C.M., Sen, T.Z. 2019. PedigreeNet: A web-based pedigree viewer for biological databases. Bioinformatics. 1-3. https://doi.org/10.1093/bioinformatics/btz208.

Visualization, tools, and resources for wheat at GrainGenes - (Abstract Only)

Structural dynamics of lytic polysaccharide monoxygenases reveals a highly flexible substrate binding region - (Peer Reviewed Journal)
Arora, R., Bharyal, P., Sarswati, S., Sen, T.Z., Yennamalli, R.M. 2018. Structural dynamics of lytic polysaccharide monoxygenases reveals a highly flexible substrate binding region. Journal of Molecular Graphics and Modeling. 88:1-10. https://doi.org/10.1016/j.jmgm.2018.12.012.