Keywords: decoding modules, ELF4 function, transcriptome, deep learning, transcriptomics, ascorbate, SWI3

Latest 49 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

Light on its feet: Acclimation to high and low diurnal light is flexible in Chlamydomonas reinhardtii

Authors: Dupuis, S., Chastain, J. L., Han, G., Zhong, V., Gallaher, S. D., Nicora, C. D., Purvine, S. O., Lipton, M. S., Niyogi, K. K., Iwai, M., Merchant, S. S.

Date: 2025-09-02 · Version: 1

DOI: 10.1101/2025.08.28.672467

Model Organism: Chlamydomonas reinhardtii

photoprotection diurnal light acclimation thylakoid ultrastructure transcriptomics proteomics

DECREASE IN DNA METHYLATION 1-mediated epigenetic regulation maintains gene expression balance required for heterosis in Arabidopsis thaliana

Authors: Matsuo, K., Wu, R., Yonechi, H., Murakami, T., Takahashi, S., Kamio, A., Akter, M. A., Kamiya, Y., Nishimura, K., Matsuura, T., Tonosaki, K., Shimizu, M., Ikeda, Y., Kobayashi, H., Seki, M., Dennis, E. S., Fujimoto, R.

Date: 2025-08-26 · Version: 1

DOI: 10.1101/2025.08.21.671646

Model Organism: Arabidopsis thaliana

heterosis DNA methylation DDM1 Arabidopsis thaliana transcriptomics

A sublethal drought and rewatering time course reveals intricate patterning of responses in the annual Arabidopsis thaliana

Authors: Fitzek-Campbell, E., Psaroudakis, D., Weisshaar, B., Junker, A., Braeutigam, A.

Date: 2025-07-27 · Version: 1

DOI: 10.1101/2025.07.25.666782

Model Organism: Arabidopsis thaliana

drought stress Arabidopsis thaliana transcriptomics high‑throughput phenotyping biomarker transcripts

Transcriptomics uncovers molecular mechanisms underlying salt-inhibited root growth in Festuca rubra

Authors: Lan, B., Ru, D., Du, F. K., Yin, K.

Date: 2025-07-26 · Version: 1

DOI: 10.1101/2025.07.22.665687

Model Organism: Festuca rubra

salt stress root growth inhibition Festuca rubra transcriptomics hormone signaling

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

The transcriptional mechanism behind Mimosa pudica leaf-folding in response to mechanical disturbance

Authors: Buti, M., Checcucci, A., Vergata, C., Renna, L., Pollastri, S., Loreto, F., Mancuso, S., Martinelli, F.

Date: 2025-07-21 · Version: 1

DOI: 10.1101/2025.07.17.665295

Model Organism: Mimosa pudica

Mimosa pudica mechanical stress chlorophyll fluorescence transcriptomics stress‑responsive gene expression

Enhancement of Arabidopsis growth by Enterobacter sp. SA187 under elevated CO2 is dependent on ethylene signalling activation and primary metabolism reprogramming

Authors: Ilyas, A., Mauve, C., Pateyron, S., Paysant-Le Roux, C., Bigeard, J., Hodges, M., de Zelicourt, A.

Date: 2025-07-09 · Version: 1

DOI: 10.1101/2025.07.08.663752

Model Organism: Arabidopsis thaliana

Enterobacter sp. SA187 elevated CO2 Arabidopsis thaliana phytohormone signaling transcriptomics

Integrative Multi-Omics Analysis Reveals Stress-Specific Molecular Architectures in Soybean under Drought and Rust Infection

Authors: Husein, G., Castro-Moretti, F. R., Prado, M., Amorim, L., Mazzafera, P., Canales, J., Monteiro-Vitorello, C. B.

Date: 2025-07-08 · Version: 1

DOI: 10.1101/2025.07.07.663534

Model Organism: Glycine max

Asian soybean rust drought stress transcriptomics metabolomics co-expression network

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

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