Abstract Machine learning is a useful computational tool for large and complex tasks such as
those in the field of enzyme engineering, selection and design. In this review, we examine …

Background The automated prediction of the enzymatic functions of uncharacterized
proteins is a crucial topic in bioinformatics. Although several methods and tools have been …

As a great challenge in bioinformatics, enzyme function prediction is a significant step
toward designing novel enzymes and diagnosing enzyme-related diseases. Existing studies …

Metalloenzymes are 40% of all enzymes and can perform all seven classes of enzyme
reactions. Because of the physicochemical similarities between the active sites of …

Nucleosome is a central element of eukaryotic chromatin, which composes of histone
proteins and DNA molecules. It performs vital roles in many eukaryotic intra-nuclear …

Abstract Background and Objectives Enhancers are pivotal DNA elements, which are widely
used in eukaryotes for activation of transcription genes. On the basis of enhancer strength …

Chronic diseases have seriously affected human activities, especially in many develo**
countries and underdeveloped countries. The long duration of chronic diseases and the …

Enzymes, as a group of crucial biocatalysts produced by living cells, enable the chemical
reactions in organisms to be more efficient. According to the properties of the reactions …

Engineering the microbial production of secondary metabolites is limited by the known
reactions of correctly annotated enzymes. Therefore, the machine learning discovery of …

The learning from imbalanced data is a deeply studied problem in standard classification
and, in recent times, also in multilabel classification. A handful of multilabel resampling …