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: With new developments in biomedical technology, it is now a viable therapeutic treatment to alter genes with techniques like CRISPR. At the same time, it is increasingly cheaper to do whole genome sequencing, resulting in rapid advancement in gene therapy and editing in precision medicine. Thus, understanding the current industry and academic applications of gene therapy provides an important backdrop to future scientific developments. Additionally, machine learning and artificial intelligence techniques allow for the reduction of time and money spent in the development of new gene therapy products and techniques. In this paper, we survey the current progress of gene therapy treatments for several diseases and explore machine learning applications in gene therapy. We also discuss the ethical implications of gene therapy and the use of machine learning in precision medicine. Machine learning and gene therapy are both topics gaining popularity in various publications, and we conclude that there is still room for continued research and application of machine learning techniques in the gene therapy field.

: Malaria caused by Plasmodium falciparum is one of the major infectious diseases in the world. It is essential to exploit an effective method to predict secretory proteins of malaria parasites to develop effective cures and treatment. Biochemical assays can provide details for accurate identification of the secretory proteins, but these methods are expensive and time-consuming. In this paper, we summarized the machine learning-based identification algorithms and compared the construction strategies between different computational methods. Also, we discussed the use of machine learning to improve the ability of algorithms to identify proteins secreted by malaria parasites.