The big picture of this DL project is described in the submitted paper entitled 'Cracking the genetic code by neural networks'. To have a direct visual grasp of what this Deep Learning project does, ...

This is the code base for the paper Efficient Hyperparameter Optimization in Deep Learning Using a Variable Length Genetic Algorithm by Xueli Xiao, Ming Yan, Sunitha Basodi, Chunyan Ji, Yi Pan.

A new deep learning algorithm can pick up the molecular pathways ... Current methods to do so involve costly genetic tests, which can be a slow process. However, researchers from the Department ...

Evolutionary Deep Learning is a guide to improving your deep learning models with AutoML enhancements based on the principles of biological evolution. This exciting new approach utilizes lesser-known ...

In this paper, we propose a method for explaining the working mechanism of deep-learning-based traffic classification as a method of XAI based on a genetic algorithm. We describe the mechanism of the ...

Researchers have successfully employed an algorithm to identify potential ... identifies "open" regions of the genome, and PRINT, a deep-learning-based method to detect these types of footprints ...

With all the excitement over neural networks and deep-learning ... for Cartesian genetic programming (as their technique is called). The process begins by randomly creating a code containing ...

Researchers at the University of Chicago Medicine Comprehensive Cancer Center, working with colleagues in Europe, created a deep learning algorithm ... for certain genetic alterations that may ...

Minority populations have been historically under-represented in existing studies addressing how genetic variations ... therapeutic drug targets. Deep learning algorithms have also been used ...

Summary: A new deep learning algorithm that ... in regions that did not code for proteins seemed to be implicated in these disorders at higher frequency, which means they may serve as alternative ...