AIMC Topic: Gene Expression Regulation, Plant

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Model-to-crop conserved NUE Regulons enhance machine learning predictions of nitrogen use efficiency.

The Plant cell May 9, 2025
Systems biology aims to uncover gene regulatory networks (GRNs) for agricultural traits, but validating them in crops is challenging. We addressed this challenge by learning and validating model-to-crop transcription factor (TF) regulons governing ni...
Gene Regulatory Networks Transcription Factors Zea mays Machine Learning Gene Expression Regulation, Plant Arabidopsis Regulon Nitrogen Crops, Agricultural Plant Proteins
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Predicting Fitness-Related Traits Using Gene Expression and Machine Learning.

Genome biology and evolution Feb 3, 2025
Evolution by natural selection occurs at its most basic through the change in frequencies of alleles; connecting those genomic targets to phenotypic selection is an important goal for evolutionary biology in the genomics era. The relative abundance o...
Genetic Fitness Machine Learning Ipomoea Phenotype Selection, Genetic Transcriptome Gene Expression Regulation, Plant Photosynthesis
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Deep learning with a small dataset predicts chromatin remodelling contribution to winter dormancy of apple axillary buds.

Tree physiology Jul 2, 2024
Epigenetic changes serve as a cellular memory for cumulative cold recognition in both herbaceous and tree species, including bud dormancy. However, most studies have discussed predicted chromatin structure with respect to histone marks. In the presen...
Epigenesis, Genetic Bayes Theorem Seasons Deep Learning Gene Expression Regulation, Plant Chromatin Assembly and Disassembly Plant Dormancy Flowers Cold Temperature Malus
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Decoding the cis-regulation of tomato fruit development with deep learning.

The Plant cell May 24, 2022
Gene Expression Regulation, Plant Deep Learning Solanum lycopersicum Fruit Plant Proteins
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Genome-wide cis-decoding for expression design in tomato using cistrome data and explainable deep learning.

The Plant cell May 24, 2022
In the evolutionary history of plants, variation in cis-regulatory elements (CREs) resulting in diversification of gene expression has played a central role in driving the evolution of lineage-specific traits. However, it is difficult to predict expr...
Solanum lycopersicum Fruit Plant Proteins Deep Learning Transcription Factors Gene Expression Regulation, Plant Regulatory Sequences, Nucleic Acid
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Interpreting machine learning models to investigate circadian regulation and facilitate exploration of clock function.

Proceedings of the National Academy of Sciences of the United States of America Aug 10, 2021
The circadian clock is an important adaptation to life on Earth. Here, we use machine learning to predict complex, temporal, and circadian gene expression patterns in Most significantly, we classify circadian genes using DNA sequence features genera...
Apoproteins Phytochrome A Arabidopsis Regulatory Sequences, Nucleic Acid Ecotype Circadian Clocks Gene Expression Regulation, Plant Arabidopsis Proteins Machine Learning Models, Biological Gene Expression Profiling Circadian Rhythm Phytochrome
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Prediction of Rice Transcription Start Sites Using TransPrise: A Novel Machine Learning Approach.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2021
As the interest in genetic resequencing increases, so does the need for effective mathematical, computational, and statistical approaches. One of the difficult problems in genome annotation is determination of precise positions of transcription start...
Machine Learning Software Transcription Initiation Site Transcription, Genetic Oryza Genome, Plant Plant Proteins Promoter Regions, Genetic Gene Expression Regulation, Plant
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Prediction of condition-specific regulatory genes using machine learning.

Nucleic acids research Jun 19, 2020
Recent advances in genomic technologies have generated data on large-scale protein-DNA interactions and open chromatin regions for many eukaryotic species. How to identify condition-specific functions of transcription factors using these data has bec...
Genes, Plant Arabidopsis Proteins Deep Learning Arabidopsis Stress, Physiological Genes, Regulator Gene Regulatory Networks Single-Cell Analysis Promoter Regions, Genetic Transcription Factors RNA-Seq Gene Expression Regulation, Plant Machine Learning Datasets as Topic Gene Expression Profiling
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An Overview on Predicting Protein Subchloroplast Localization by using Machine Learning Methods.

Current protein & peptide science Jan 1, 2020
The chloroplast is a type of subcellular organelle of green plants and eukaryotic algae, which plays an important role in the photosynthesis process. Since the function of a protein correlates with its location, knowing its subchloroplast localizatio...
Protein Transport Machine Learning Gene Expression Regulation, Plant Computational Biology Chloroplast Proteins Plants Chloroplasts Proteome Amino Acid Sequence Models, Statistical Datasets as Topic
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High-throughput phenotyping with deep learning gives insight into the genetic architecture of flowering time in wheat.

GigaScience Nov 1, 2019
BACKGROUND: Measurement of plant traits with precision and speed on large populations has emerged as a critical bottleneck in connecting genotype to phenotype in genetics and breeding. This bottleneck limits advancements in understanding plant genome...
Databases, Nucleic Acid Genetic Association Studies Deep Learning Gene Expression Regulation, Plant Triticum Genotype Flowers
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