ML for genomics

Thanks to rapid advancements in NGS, genomics has shown tremendous growth in the last decade, which has led to an outpouring of massive sequence data. In addition to whole-genome sequencing (WGS), other promising techniques have emerged, such as whole-exome sequencing (WES) to measure the expressed region of the genome, whole-transcriptome sequencing (WTS) or RNA-sequencing (RNA-seq) to measure mRNA expression, ChIP-sequencing (ChIP-seq) to identify transcription-factor binding sites, and Ribo-sequencing (Ribo-seq) to identify actively translating mRNAs for quantifying relative protein abundance, and so on. The challenge now is not “what to measure ” but “how to analyze the data to extract meaningful data and turn those insights into applications”. While the development of NGS technologies and the generation of massive data has provided opportunities for a new field called “bioinformatics” to grow significantly, it has also...