Keywords: paralog processing, CO2 enrichment, transcriptomic analysis, computer vision, ascorbate, deep learning

Latest 22 Papers

Botanic Spectrum Analyser: A Deep Learning GUI for Plant Image Segmentation in Hyperspectral and RGB Phenotyping

Authors: Walsh, J. J., Gorgu, L., Cavel, E., Poulain, V., Gutierrez, L., Mangina, E., Negrao, S.

Date: 2025-09-17 · Version: 1

DOI: 10.1101/2025.09.14.676080

plant phenotyping image segmentation U‑Net hyperspectral imaging deep learning

Gain and loss of gene function shaped the nickel hyperaccumulation trait in Noccaea caerulescens

Authors: Belloeil, C., Garcia de la Torre, V. S., Contreras Aguilera, R., Kupper, H., Lopez-Roques, C., Iampetro, C., Vandecasteele, C., Klopp, C., Launay-Avon, A., Leemhuis, W., Yamjabok, J., van den Heuvel, J., Aarts, M. G. M., Quintela Sabaris, C., Thomine, S., MERLOT, S.

Date: 2025-07-25 · Version: 1

DOI: 10.1101/2025.07.22.664359

Model Organism: Noccaea caerulescens

nickel hyperaccumulation Noccaea caerulescens genome assembly transcriptomic analysis metal transporters

Phenotypic scoring of Canola Blackleg severity using machine learning image analysis

Authors: Hu, Q., Anderson, S. N., Gardner, S., Ernst, T. W., Koscielny, C. B., Bahia, N. S., Johnson, C. G., Jarvis, A. C., Hynek, J., Coles, N., Falak, I., Charne, D. R., Ruidiaz, M. E., Linares, J. N., Mazis, A., Stanton, D. J.

Date: 2025-07-22 · Version: 1

DOI: 10.1101/2025.07.17.665372

Model Organism: Multi-species

blackleg disease canola (Brassica spp.)deep learning image-based phenotyping disease severity scoring

RegenPGC View: Semantic Segmentation of Perennial Groundcover Cropping Systems to Restore American Croplands

Authors: Meyering, B., Schlautman, B.

Date: 2025-07-06 · Version: 1

DOI: 10.1101/2025.07.03.663038

Model Organism: General

perennial groundcovers cover cropping deep learning convolutional neural network image‑based phenotyping

MdBRC1 and MdFT2 Interaction Fine-Tunes Bud Break Regulation in Apple

Authors: Gioppato, H. A., Estevan, J., Al Bolbol, M., Soriano, A., Garighan, J., Jeong, K., Georget, C., Soto, D. G., El Khoury, S., Falavigna, V. d. S., George, S., Perales, M., Andres, F.

Date: 2025-06-24 · Version: 1

DOI: 10.1101/2025.06.20.660803

Model Organism: Malus domestica

bud dormancy MdBRC1 MdFT2 transcriptomic analysis protein interaction

Unraveling the cis-regulatory code controlling abscisic acid-dependent gene expression in Arabidopsis using deep learning

Authors: Opdebeeck, H., Smet, D., Thierens, S., Minne, M., De Beukelaer, H., Zuallaert, J., Van Bel, M., Van Montagu, M., Degroeve, S., De Rybel, B., Vandepoele, K.

Date: 2025-06-06 · Version: 1

DOI: 10.1101/2025.06.03.657584

Model Organism: Arabidopsis thaliana

Abscisic acid Arabidopsis thaliana deep learning promoter motifs ABF binding sites

Constitutive expression of full-length or partial of SOC1 genes for yield enhancement in tomato

Authors: Danial, G. H., Jaikham, J., Song, G.-q.

Date: 2025-06-06 · Version: 1

DOI: 10.1101/2025.06.03.657751

Model Organism: Solanum lycopersicum

SOC1 tomato fruit yield heterologous gene expression branching transcriptomic analysis

Evaporative cooling signals for wound healing in plants

Authors: Balem, J. M., Tan, C., Dias, N. C. F., Arnold, M. L., Tran, S., Severns, P. M., Teixeira, P. J. P. L., Li, C., Yang, L.

Date: 2025-05-28 · Version: 1

DOI: 10.1101/2025.05.23.655667

Model Organism: Arabidopsis thaliana

wound healing Arabidopsis thaliana cold-responsive genes CBF transcription factors computer vision

Arabidopsis lines with modified ascorbate concentrations reveal a link between ascorbate and auxin biosynthesis

Authors: Fenech, M., Zulian, V., Moya-Cuevas, J., Arnaud, D., Morilla, I., Smirnoff, N., Botella, M. A., Stepanova, A. N., Alonso, J. M., Martin-Pizarro, C., Amorim-Silva, V.

Date: 2025-05-16 · Version: 1

DOI: 10.1101/2025.05.15.654287

Model Organism: Arabidopsis thaliana

ascorbate Arabidopsis thaliana auxin biosynthesis redox homeostasis transcriptomics

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

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