AIMC Topic: Arabidopsis Proteins

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Measuring semantic similarities by combining gene ontology annotations and gene co-function networks.

BMC bioinformatics Feb 14, 2015
BACKGROUND: Gene Ontology (GO) has been used widely to study functional relationships between genes. The current semantic similarity measures rely only on GO annotations and GO structure. This limits the power of GO-based similarity because of the li...
Semantics Vocabulary, Controlled Gene Regulatory Networks Cytochrome P-450 Enzyme System Computational Biology Software Metabolic Networks and Pathways Algorithms Multigene Family Humans Saccharomyces cerevisiae Proteins Molecular Sequence Annotation Gene Ontology Arabidopsis Proteins
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Machine-learning meta-analysis reveals ethylene as a central component of the molecular core in abiotic stress responses in Arabidopsis.

Nature communications May 22, 2025
Understanding how plants adapt their physiology to overcome severe and often multifactorial stress conditions in nature is vital in light of the climate crisis. This remains a challenge given the complex nature of the underlying molecular mechanisms....
Stress, Physiological Plant Shoots Transcriptome Plant Roots Arabidopsis Ethylenes Gene Expression Regulation, Plant Arabidopsis Proteins Machine Learning Gene Expression Profiling
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AtSubP-2.0: An integrated web server for the annotation of Arabidopsis proteome subcellular localization using deep learning.

The plant genome Mar 1, 2025
The organization of subcellular components in a cell is critical for its function and studying cellular processes, protein-protein interactions, identifying potential drug targets, network analysis, and other systems biology mechanisms. Determining p...
Software Deep Learning Arabidopsis Proteins Arabidopsis Internet Molecular Sequence Annotation Proteome
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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...
Regulatory Sequences, Nucleic Acid Ecotype Arabidopsis Proteins Arabidopsis Apoproteins Phytochrome A Circadian Rhythm Phytochrome Circadian Clocks Gene Expression Regulation, Plant Gene Expression Profiling Models, Biological Machine Learning
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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...
Single-Cell Analysis RNA-Seq Gene Regulatory Networks Transcription Factors Gene Expression Profiling Genes, Plant Deep Learning Arabidopsis Proteins Promoter Regions, Genetic Machine Learning Datasets as Topic Gene Expression Regulation, Plant Arabidopsis Stress, Physiological Genes, Regulator
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