Keywords: paralog processing, SWI3, ascorbate, machine learning, single-cell RNA sequencing

Latest 21 Papers

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

Conserved spatial patterning of gene expression in independent lineages of C4 plants

Authors: Sun, T., Bonthala, V. S., Stich, B., Luginbuehl, L. H., Hibberd, J. M.

Date: 2025-05-15 · Version: 1

DOI: 10.1101/2025.05.14.654047

Model Organism: Gynandropsis gynandra, Flaveria bidentis

C4 photosynthesis single-cell RNA sequencing single-nucleus RNA sequencing bundle sheath cells transcription factors

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

Imputation integrates single-cell and spatial gene expression data to resolve transcriptional networks in barley shoot meristem development

Authors: Demesa-Arevalo, E., Dorpholz, H., Vardanega, I., Maika, J. E., Pineda-Valentino, I., Eggels, S., Lautwein, T., Kohrer, K., Schnurbusch, T., von Korff, M., Usadel, B., Simon, R.

Date: 2025-05-11 · Version: 1

DOI: 10.1101/2025.05.09.653223

Model Organism: Hordeum vulgare

Barley (Hordeum vulgare)inflorescence meristems single-cell RNA sequencing spatial transcriptomics developmental gene regulation

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

Large-scale single-cell profiling of stem cells uncovers redundant regulators of shoot development and yield trait variation

Authors: Xu, X., Passalacqua, M., Rice, B., Demesa-Arevalo, E., Kojima, M., Takebayashi, Y., Harris, B., Sakakibara, H., Gallavotti, A., Gillis, J., Jackson, D.

Date: 2025-04-17 · Version: 2

DOI: 10.1101/2024.03.04.583414

Model Organism: Multi-species

single-cell RNA sequencing shoot stem cells Arabidopsis thaliana Zea mays stem cell regulators

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

The minimal cell-cycle control system in Marchantia as a framework for understanding plant cell proliferation

Authors: Romani, F., Bonter, I., Rebmann, M., Takahashi, G., Guzman-Chavez, F., De Batte, F., Hirakawa, Y., Haseloff, J.

Date: 2025-03-13 · Version: 1

DOI: 10.1101/2025.03.12.642684

Model Organism: Marchantia polymorpha

Cyclin-CDK regulation Marchantia polymorpha single-cell RNA sequencing phylogenetic analysis fluorescent reporter imaging

Sunflower yield modeling with XAI: Historical weather impacts and forecasting

Authors: Majumder, S., Mason, C.

Date: 2025-02-28 · Version: 1

DOI: 10.1101/2025.02.27.640573

Model Organism: Helianthus annuus

explainable AI sunflower yield climate variability machine learning Shared Socioeconomic Pathways

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