EXPath 2.0: An Updated Database for Integrating High-Throughput Gene Expression Data with Biological Pathways.

Co-expressed genes tend to have regulatory relationships and participate in similar biological processes. Construction of gene correlation networks from microarray or RNA-seq expression data has been widely applied to study transcriptional regulatory mechanisms and metabolic pathways under specific conditions. Furthermore, since transcription factors (TFs) are critical regulators of gene expression, it is worth investigating TFs on the promoters of co-expressed genes.

PlantPAN3.0: a new and updated resource for reconstructing transcriptional regulatory networks from ChIP-seq experiments in plants.

The Plant Promoter Analysis Navigator (PlantPAN; http://PlantPAN.itps.ncku.

microRPM: a microRNA prediction model based only on plant small RNA sequencing data.

Motivation: MicroRNAs (miRNAs) are endogenous non-coding small RNAs (of about 22 nucleotides), which play an important role in the post-transcriptional regulation of gene expression via either mRNA cleavage or translation inhibition. Several machine learning-based approaches have been developed to identify novel miRNAs from next generation sequencing (NGS) data. Typically, precursor/genomic sequences are required as references for most methods.