Arabidopsis Genetics

DNA sequence and structure properties analysis reveals similarities and differences to promoters of stress responsive genes in Arabidopsis thaliana

Understanding regulatory mechanisms of stress response in plants has important biological and agricultural significances. In this study, we firstly compiled a set of genes responsive to different stresses in Arabidopsis thaliana and then …

Machine learning-based differential network analysis: a study of stress-responsive transcriptomes in Arabidopsis

Machine learning (ML) is an intelligent data mining technique that builds a prediction model based on the learning of prior knowledge to recognize patterns in large-scale data sets. We present an ML-based methodology for transcriptome analysis via …

mlDNA

Machine learning-based differential network analysis

Application of the Gini correlation coefficient to infer regulatory relationships in transcriptome analysis

One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to …

RSGCC

Gini-based transcriptiome analysis