Sequencing technologies are evolving at a rapid pace, enabling the generation of massive
amounts of data in multiple dimensions (eg, genomics, epigenomics, transcriptomic …

Abstract Machine learning (ML) is a field of artificial intelligence that has rapidly emerged in
molecular biology, thus allowing the exploitation of Big Data concepts in plant genomics. In …

Accurate computational identification of promoters remains a challenge as these key DNA
regulatory regions have variable structures composed of functional motifs that provide gene …

The conformal predictions framework is a recent development in machine learning that can
associate a reliable measure of confidence with a prediction in any real-world pattern …

MicroRNAs (miRNAs) are a large new class of small non-coding RNAs. To date, hundreds of
microRNAs have been identified in plants. MicroRNAs play important roles in post …

Background MicroRNAs (miRNAs) are endogenously expressed small RNAs with a length
of about 21 nt. MiRNAs silence their target genes at the post-transcriptional level. In plants …

Though central to our understanding of how roots perform their vital function of scavenging
water and solutes from the soil, no direct genetic evidence currently exists to support the …

Root system architecture responds plastically to some abiotic stresses, including
phosphorus (P), iron (Fe) and water deficiency, but its response mechanism is still unclear …

Establishing transcriptional regulatory networks by analysis of gene expression data and
promoter sequences shows great promise. We developed a novel promoter classification …

Our current knowledge of eukaryotic promoters indicates their complex architecture that is
often composed of numerous functional motifs. Most of known promoters include multiple …