Building and Tuning Deep Learning Models

Deep learning (DL) algorithmic solutions are currently being leveraged in several biological and life sciences domains to address some of the most challenging problems in healthcare, medicine, agriculture, genomics, and so on. Among these disciplines, genomics poses extreme challenges to DL because of how complex the field of genomics is, which goes way beyond the knowledge of how to interpret genomes. Thankfully, a lot of genomics research with DL has led to the design of sophisticated deep neural networks (DNN) architectures that are suited to genomic tasks. This intersection of DL with genomics proved very successful, leading to the application of DL to several genomic applications in regulatory genomics, functional genomics, structural genomics, and so on. Furthermore, it allowed the genomics research community to gain a global perspective of the human genome, which is paving the way for the goal of genomic medicine in near future.

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