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NBSPred: a support vector machine-based high-throughput pipeline for plant resistance protein NBSLRR prediction.

Bioinformatics (Oxford, England)
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
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
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
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...

AtSubP-2.0: An integrated web server for the annotation of Arabidopsis proteome subcellular localization using deep learning.

The plant genome
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...

HNCGAT: a method for predicting plant metabolite-protein interaction using heterogeneous neighbor contrastive graph attention network.

Briefings in bioinformatics
The prediction of metabolite-protein interactions (MPIs) plays an important role in plant basic life functions. Compared with the traditional experimental methods and the high-throughput genomics methods using statistical correlation, applying hetero...

PTFSpot: deep co-learning on transcription factors and their binding regions attains impeccable universality in plants.

Briefings in bioinformatics
Unlike animals, variability in transcription factors (TFs) and their binding regions (TFBRs) across the plants species is a major problem that most of the existing TFBR finding software fail to tackle, rendering them hardly of any use. This limitatio...

miWords: transformer-based composite deep learning for highly accurate discovery of pre-miRNA regions across plant genomes.

Briefings in bioinformatics
Discovering pre-microRNAs (miRNAs) is the core of miRNA discovery. Using traditional sequence/structural features, many tools have been published to discover miRNAs. However, in practical applications like genomic annotations, their actual performanc...

3D Visualization of Microtubules in Epidermal Pavement Cells.

Methods in molecular biology (Clifton, N.J.)
The plant cytoskeleton is instrumental in cellular processes such as cell growth, differentiation, and immune response. Microtubules, in particular, play a crucial role in morphogenesis by governing the deposition of plant cell wall polysaccharides a...

iDHS-Deep: an integrated tool for predicting DNase I hypersensitive sites by deep neural network.

Briefings in bioinformatics
DNase I hypersensitive site (DHS) refers to the hypersensitive region of chromatin for the DNase I enzyme. It is an important part of the noncoding region and contains a variety of regulatory elements, such as promoter, enhancer, and transcription fa...