Abstract Machine learning (ML) is a powerful technique to tackle many problems in data
mining and predictive analytics. We believe that ML will be of considerable potentials in the …

The last few years have seen an advancement in genomic research in bioinformatics. With
the introduction of high-throughput sequencing techniques, researchers now can analyze …

Abstract Machine learning (ML) is an analytical approach that has been on increasing
importance in this field. In this chapter, we would like to highlight the use of ML for disease …

In recent years, machine learning (ML) has been revolutionizing biology, biomedical
sciences, and gene‐based agricultural technology capabilities. Massive data generated in …

Abstract Machine learning has become a pivotal tool for many projects in computational
biology, bioinformatics, and health informatics. Nevertheless, beginners and biomedical …

Bioinformatics is the field of science that harnesses the potential of computational tools to
analyze and interpret biological data. While this combination is highly useful for medical …

The scale of genetic, epigenomic, transcriptomic, cheminformatic and proteomic data
available today, coupled with easy-to-use machine learning (ML) toolkits, has propelled the …

Biomacromolecules, primarily proteins, DNA, and RNA, are crucial for vital physiological
processes. Biomacromolecules can generally be represented by sequences, comprising …

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With the recent development in biotechnology, especially next-generation sequencing in
genomics, there is an explosion of genomic data generated. The data are big in terms of …