Keywords: paralog processing, transcriptomic analysis, machine learning, single-cell RNA sequencing

Latest 25 Papers

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

daily transpiration machine learning gravimetric load cells Random Forest XGBoost

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

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

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

Single-cell metabolome and RNA-seq multiplexing on single plant cells

Authors: Kang, M., Vu, A. H., Casper, A. L., Kim, R., Wurlitzer, J., Heinicke, S., Yeroslaviz, A., Caputi, L., O'Connor, S. E.

Date: 2025-05-23 · Version: 1

DOI: 10.1101/2025.05.20.655036

Model Organism: General

single-cell RNA sequencing single-cell mass spectrometry metabolomics gene‑to‑metabolite correlation plant biosynthetic pathways multimodal single‑cell analysis

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

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