Keywords: paralog processing, transcriptome reprogramming, deep learning, Triticum aestivum

Latest 26 Papers

Deciphering the Sequence Basis and Application of Transcriptional Initiation Regulation in Plant Genomes Through Deep Learning

Authors: Gao, P., Lian, L., Feng, W., Ma, Y., Lin, J., Qin, L., Hao, S., Zhao, H., Liu, X., Yuan, J., Lin, Z., Li, X., Guan, Y., Wang, X.

Date: 2025-04-24 · Version: 1

DOI: 10.1101/2025.04.22.649999

Model Organism: Glycine max

transcription start site promoter motifs deep learning soybean domestication plant gene regulation

Streptomyces coelicolor-plant association facilitates ergothioneine (EGT) uptake in Triticum aestivum

Authors: Pipinos, A., Kan, J., Smith, A., Zinati, G., Bais, H.

Date: 2025-04-08 · Version: 1

DOI: 10.1101/2025.04.08.647769

Model Organism: Triticum aestivum

ergothioneine Streptomyces coelicolor Triticum aestivum endophytic colonization bio‑stimulant

Real-Time Quantitative PCR Method for Assessing Wheat Cultivars for Resistance to Zymoseptoria tritici

Authors: Adhikari, T. B., Balaji, B., Goodwin, S. B.

Date: 2025-04-06 · Version: 1

DOI: 10.1101/2025.04.02.646880

Model Organism: Triticum aestivum

Zymoseptoria tritici Triticum aestivum real-time qPCR fungal DNA quantification Stb4/Stb8 resistance

The Global Wheat Full Semantic Organ Segmentation (GWFSS) dataset

Authors: Wang, Z., Zenkl, R., Greche, L., De Solan, B., Bernigaud Samatan, L., Ouahid, S., Visioni, A., Robles-Zazueta, C. A., Pinto, F., Perez-Olivera, I., Reynolds, M. P., Zhu, C., Liu, S., D'argaignon, M.-P., Lopez-Lozano, R., Weiss, M., Marzougui, A., Roth, L., Dandrifosse, S., Carlier, A., Dumont, B., Mercatoris, B., Fernandez, J., Chapman, S., Najafian, K., Stavness, I., Wang, H., Guo, W., Virlet, N., Hawkesford, M., Chen, Z., David, E., Gillet, J., Irfan, K., Comar, A., Hund, A.

Date: 2025-03-19 · Version: 1

DOI: 10.1101/2025.03.18.642594

Model Organism: Triticum aestivum

wheat semantic segmentation computer vision deep learning phenotyping

Fiber Bragg grating based sensing system for non-destructive root phenotyping using ResNet prediction

Authors: Binder, S., Hossain, K., Bucksch, A., Fok, M.

Date: 2025-02-28 · Version: 2

DOI: 10.1101/2024.09.17.613457

Model Organism: Zea mays

root architecture fiber Bragg grating real-time phenotyping deep learning Zea mays

TaWUS2D regulates the number of grains per spikelet by enhancing the number of fertile ovaries in Multi-Ovary Wheat

Authors: Schoen, A. W., Sharma, P. K., Mahlandt, A., Chen, A., Sheng, H., Kochian, L., Gao, P., Xiang, D., Quilichini, T., Venglat, P., Wang, S., Yadav, I. S., Gu, Y., Rodriguez-Leal, D., Luo, W., Qi, Y., Meier, N., Kajla, A., Willman, M., Brown-Guedira, G., Youngblood, C., Hulse-Kemp, A., Murphy, A., Gill, B., Uauy, C., Datla, R., Rawat, N., Tiwari, V.

Date: 2025-02-08 · Version: 1

DOI: 10.1101/2025.02.05.636547

Model Organism: Triticum aestivum

Triticum aestivum multi-ovary phenotype TaWUS2D map-based cloning HiFi long‑read genome assembly

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