AIMC Topic: Arabidopsis
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A Factor Graph Approach to Automated GO Annotation.
PloS one
Jan 15, 2016
As volume of genomic data grows, computational methods become essential for providing a first glimpse onto gene annotations. Automated Gene Ontology (GO) annotation methods based on hierarchical ensemble classification techniques are particularly int...
NBSPred: a support vector machine-based high-throughput pipeline for plant resistance protein NBSLRR prediction.
Bioinformatics (Oxford, England)
Dec 9, 2015
UNLABELLED: The nucleotide binding site leucine-rich repeats (NBSLRRs) belong to one of the largest known families of disease resistance genes that encode resistance proteins (R-protein) against the pathogens of plants. Various defence mechanisms hav...
DNA-binding protein prediction using plant specific support vector machines: validation and application of a new genome annotation tool.
Nucleic acids research
Aug 24, 2015
There are currently 151 plants with draft genomes available but levels of functional annotation for putative protein products are low. Therefore, accurate computational predictions are essential to annotate genomes in the first instance, and to provi...
Use of Semisupervised Clustering and Feature-Selection Techniques for Identification of Co-expressed Genes.
IEEE journal of biomedical and health informatics
Jul 20, 2015
Studying the patterns hidden in gene-expression data helps to understand the functionality of genes. In general, clustering techniques are widely used for the identification of natural partitionings from the gene expression data. In order to put cons...
Alpha-plane based automatic general type-2 fuzzy clustering based on simulated annealing meta-heuristic algorithm for analyzing gene expression data.
Computers in biology and medicine
Jul 2, 2014
This paper considers microarray gene expression data clustering using a novel two stage meta-heuristic algorithm based on the concept of α-planes in general type-2 fuzzy sets. The main aim of this research is to present a powerful data clustering app...
Methylomes Reveal Recent Evolutionary Changes in Populations of Two Plant Species.
Genome biology and evolution
May 30, 2025
Plant DNA methylation changes occur hundreds to thousands of times faster than DNA mutations and can be transmitted transgenerationally, making them useful for studying population-scale patterns in clonal or selfing species. However, a state-of-the-a...
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....
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...
Machine learning-augmented m6A-Seq analysis without a reference genome.
Briefings in bioinformatics
May 1, 2025
Methylated RNA m6A immunoprecipitation sequencing (m6A-Seq) is a powerful technique for investigating transcriptome-wide m6A modification. However, most of the existing m6A-Seq protocols rely on reference genomes, limiting their use in species lackin...
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...
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