AIMC Topic: Arabidopsis
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Inferring Unknown Biological Function by Integration of GO Annotations and Gene Expression Data.
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2016
Characterizing genes with semantic information is an important process regarding the description of gene products. In spite that complete genomes of many organisms have been already sequenced, the biological functions of all of their genes are still ...
phenoSeeder - A Robot System for Automated Handling and Phenotyping of Individual Seeds.
Plant physiology
Sep 23, 2016
The enormous diversity of seed traits is an intriguing feature and critical for the overwhelming success of higher plants. In particular, seed mass is generally regarded to be key for seedling development but is mostly approximated by using scanning ...
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...
Machine learning based prediction by PlantCdMiner and experimental validation of cadmium-responsive genes in plants.
Journal of hazardous materials
Aug 15, 2025
Plants have evolved diverse adaptive mechanisms to sense and respond to environmental stimuli such as cadmium stress. The regulation of gene expression plays a critical role in plant responses to abiotic stress. However, homologous genes from differe...
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....
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