As a data-driven science, genomics largely utilizes machine learning to capture
dependencies in data and derive novel biological hypotheses. However, the ability to extract …

Deep learning, which is especially formidable in handling big data, has achieved great
success in various fields, including bioinformatics. With the advances of the big data era in …

Background The recent development of metagenomic sequencing makes it possible to
massively sequence microbial genomes including viral genomes without the need for …

Our era has witnessed tremendous advances in plant genomics, characterized by an
explosion of high-throughput techniques to identify multi-dimensional genome-wide …

Covering: up to 2021 Plants and their associated microbial communities are known to
produce millions of metabolites, a majority of which are still not characterized and are …

Gene regulation is a central topic in cell biology. Advances in omics technologies and the
accumulation of omics data have provided better opportunities for gene regulation studies …

Interpreting the functional impacts of genetic variants (GVs) is an important challenge for
functional genomic studies in crops and next-generation breeding. Previous studies in rice …

Deciphering the genomic regulatory code of enhancers is a key challenge in biology
because this code underlies cellular identity. A better understanding of how enhancers work …

Microbial cell factories (MCFs) have been leveraged to construct sustainable platforms for
value-added compound production. To optimize metabolism and reach optimal productivity …

Here we present a computational model, Score of Unified Regulatory Features (SURF), that
predicts functional variants in enhancer and promoter elements. SURF is trained on data …