Keywords: paralog processing, CO2 enrichment, machine learning, metabolomics

Latest 33 Papers

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

Introducing furanocoumarin biosynthetic genes in tomato results in coumarins accumulation and impacted growth

Authors: Bouille, A., Villard, C., Galati, G., Roumani, M., Fauvet, A., Grosjean, J., Hoengenaert, L., Boerjan, W., Ralph, J., Hilliou, F., Robin, C., Hehn, A., Larbat, R.

Date: 2025-07-08 · Version: 1

DOI: 10.1101/2025.07.07.663522

Model Organism: Solanum lycopersicum

metabolic engineering linear furanocoumarin pathway coumarins tomato metabolomics

Integrating Load-Cell Lysimetry and Machine Learning for Prediction of Daily Plant Transpiration

Authors: Friedman, S., Averbuch, N., Nevo, T., Moshelion, M.

Date: 2025-06-30 · Version: 2

DOI: 10.1101/2024.11.24.625038

Model Organism: Multi-species

daily transpiration machine learning gravimetric load cells Random Forest XGBoost

Endophytes induce systemic spatial reprogramming of metabolism in poplar roots under drought

Authors: Aufrecht, J. A., Velickovic, D., Tournay, R., Couvillion, S. P., Balasubramanian, V. K., Winkler, T., Herrera, D., Stanley, R., Doty, S., Ahkami, A. H.

Date: 2025-06-06 · Version: 1

DOI: 10.1101/2025.06.02.657501

Model Organism: General

beneficial endophytes drought stress root metabolome chemical imaging machine learning

Multiplexed profiling of transcriptional regulators in plant cells

Authors: Alamos, S., Waldburger, L., Dee, A., Owens, L., Rattan, R., Ong, S., Shih, P.

Date: 2025-05-14 · Version: 1

DOI: 10.1101/2025.05.12.653590

Model Organism: General

transcriptional regulation high-throughput plant assay protein‑coding library machine learning synthetic protein engineering

Phylogenetic Analysis and Machine Learning Identify Signatures of Selection and Predict Deleterious Mutations in Common Bean

Authors: Cordoba-Novoa, H. A., Buckler, E. S., Romay, C., Berthel, A., Johnson, L., Balasubramanian, P., Hoyos Villegas, V.

Date: 2025-05-06 · Version: 1

DOI: 10.1101/2025.05.05.652309

Model Organism: Phaseolus vulgaris

deleterious mutations genetic load common bean MAGIC population machine learning

S2-PepAnalyst: A Web Tool for Predicting Plant Small Signalling Peptides

Authors: Vomo Donfack, K. L., Abaach, M., Luna, A. M., Ginot, G., Doblas, V. G., Morilla, I.

Date: 2025-05-06 · Version: 2

DOI: 10.1101/2024.08.02.606319

Model Organism: General

small signalling peptides machine learning protein language models geometric-topological analysis reinforcement learning

High Density Phenotypic Map of Natural Variation for Intermediate Phenotypes Associated with Stalk Lodging Resistance in Maize

Authors: Kunduru, B., Bokros, N. T., Tabaracci, K., Kumar, R., Brar, M. S., Stubbs, C. J., Oduntan, Y., DeKold, J., Bishop, R. H., Woomer, J., Verges, V. L., McDonald, A., McMahan, C. S., DeBolt, S., Robertson, D. J., Sekhon, R.

Date: 2025-04-06 · Version: 1

DOI: 10.1101/2025.04.03.647088

Model Organism: Zea mays

stalk lodging resistance maize phenomics genetic architecture intermediate phenotypes machine learning

Manipulation of in planta ethylene levels modulates the metabolome of Populus tremula x tremuloides in a microbial-dependent manner.

Authors: Fracchia, F., Guinet, F., Warion, S., Bednareck, M., Chervin, C., Engle, N. L., Tschaplinski, T. J., Veneault-Fourrey, C., Deveau, A.

Date: 2025-03-17 · Version: 1

DOI: 10.1101/2025.03.17.643694

Model Organism: Populus tremula × Populus tremuloides

ethylene signaling poplar microbiota fungal and bacterial community assembly metabolomics root exudates

Temporal analysis of physiological phenotypes identifies novel metabolic and genetic underpinnings of senescence in maize

Authors: Brar, M. S., Kumar, R., Kunduru, B., McMahan, C. S., Tharayil, N., Sekhon, R. S.

Date: 2025-03-12 · Version: 1

DOI: 10.1101/2025.03.07.641920

Model Organism: Zea mays

leaf senescence staygreen metabolomics phenylpropanoids maize

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