Latest

• PEA-m6A: an ensemble learning framework for accurately predicting N6-methyladenosine modifications in plants
• easyMF: A Web Platform for Matrix Factorization-Based Gene Discovery from Large-scale Transcriptome Data
• Interactive Web-based Annotation of Plant MicroRNAs with iwa-miRNA
• deepEA: a containerized web server for interactive analysis of epitranscriptome sequencing data
• Exploring transcriptional switches from pairwise, temporal, and population RNA-Seq data using deepTS
• CAFU: a Galaxy framework for exploring unmapped RNA-Seq data
• miRLocator: A Python Implementation and Web Server for Predicting miRNAs from Pre-miRNA Sequences
• A deep convolutional neural network approach for predicting phenotypes from genotypes
• PEA: an Integrated R Toolkit for Plant Epitranscriptome Analysis
• Transcriptome-Wide Annotation of m5C RNA Modifications Using Machine Learning
• A Meta-Analysis Based Method for Prioritizing Candidate Genes Involved in a Pre-specific Function
• miRLocator: Machine Learning-Based Prediction of Mature MicroRNAs within Plant Pre-miRNA Sequences