Keywords: paralog processing, machine learning, DDM1, genotyping-by-sequencing

Latest 17 Papers

Successful Predictive Modeling of Pollen Fitness Phenotypes Is Enabled by Measures of Expression Specificity

Authors: Mueller, S. A. F., Vejlupkova, Z., Megraw, M., Fowler, J. E.

Date: 2026-01-13 · Version: 2

DOI: 10.64898/2025.12.05.692487

Model Organism: Zea mays

maize pollen phenotype prediction machine learning Ds-GFP insertional mutants expression specificity

Scaling up orphan crop research: A global genetic perspective of cowpea (Vigna unguiculata) diversity from 10,617 accessions

Authors: Pearson, S. M., Hathorn, A., Sun, S., Cruickshank, A., Shatte, T. L., Munisse, P., Macharia, M., Conner, J., Koltunow, A. M. G., Vielle-Calzada, J. P., Ozias-Akins, P., Ishii, T., Dell Acqua, M., Norton, S., Tao, Y., Jordan, D., Mace, E.

Date: 2025-11-05 · Version: 1

DOI: 10.1101/2025.11.03.686174

Model Organism: Vigna unguiculata

cowpea genetic diversity genotyping-by-sequencing germplasm collections population structure

Evaluation of computational tools for predicting CRISPR gRNA on-target efficiency in plants.

Authors: Gong, Z., Chen, M., Zhang, H., Mortimer, J., Botella, J. R.

Date: 2025-10-15 · Version: 1

DOI: 10.1101/2025.10.15.679654

Model Organism: Multi-species

CRISPR guide RNA efficiency plant genome editing in silico prediction tools machine learning

Phylogenomic challenges in polyploid-rich lineages: Insights from paralog processing and reticulation methods using the complex genus Packera (Asteraceae: Senecioneae)

Authors: Moore-Pollard, E. R., Ellestad, P., Mandel, J.

Date: 2025-10-13 · Version: 2

DOI: 10.1101/2025.09.14.676143

Model Organism: Multi-species

phylogenomic discordance polyploidy paralog processing Packera historical biogeography

Usefulness of scRNA-seq data in predicting plant metabolic pathway genes

Authors: Ma, J., Wang, Z., Zou, L., Wang, X., Zuo, X., Wang, F., Wang, Z., Li, Z., Li, L., Wang, P.

Date: 2025-10-02 · Version: 2

DOI: 10.1101/2024.10.07.617125

Model Organism: Arabidopsis thaliana

metabolic pathway genes single-cell RNA sequencing machine learning co-expression networks prediction accuracy

Major alleles of CDCA7α shape CG-methylation in Arabidopsis thaliana

Authors: Bourguet, P., Lorkovic, Z. J., Casado, D. K., Bapteste, V., Cho, C. H., Igolkina, A., Lee, C.-R., Nordborg, M., Berger, F., Sasaki, E.

Date: 2025-09-07 · Version: 1

DOI: 10.1101/2025.09.03.673934

Model Organism: Arabidopsis thaliana

DNA methylation CG methylation (mCG)CDCA7 DDM1 local adaptation

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

Predicting flowering time using integrated morphophysiological and genomic data with machine learning models

Authors: Babaei, M., Nemati, H., Arouiee, H., Torkamaneh, D.

Date: 2025-08-13 · Version: 1

DOI: 10.1101/2025.08.11.669697

Model Organism: Cannabis sativa

flowering time Cannabis sativa genotyping-by-sequencing machine learning SNP markers

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

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