Harnessing cutting-edge technologies to enhance crop productivity is a pivotal goal in
modern plant breeding. Artificial intelligence (AI) is renowned for its prowess in big data …

Technological developments have revolutionized measurements on plant genotypes and
phenotypes, leading to routine production of large, complex data sets. This has led to …

Systematically identifying functional peptides is difficult owing to the vast combinatorial
space of peptide sequences. Here we report a machine-learning pipeline that mines the …

Networks are powerful tools to uncover functional roles of genes in phenotypic variation at a
system-wide scale. Here, we constructed a maize network map that contains the genomic …

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

Understanding plant stress memory under extreme temperatures such as cold and heat
could contribute to plant development. Plants employ different types of stress memories …

In recent years, generation of large‐scale data from genome, transcriptome, proteome,
metabolome, epigenome, and others, has become routine in several plant species. Most of …

With the development of high-throughput biology techniques and artificial intelligence, it has
become increasingly feasible to design and construct artificial biological parts, modules …

Over the past few decades, data-driven machine learning (ML) has distinguished itself from
hypothesis-driven studies and has recently received much attention in environmental …

Introduction In climate change, breeding crop plants with improved productivity,
sustainability, and adaptability has become a daunting challenge to ensure global food …