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GENE 245 Project Machine Learning for HiC data
Författare
Lan Huong Nguyen, Dan Iter, Robert Bierman
Last Updated
för 8 år sedan
Licens
Creative Commons CC BY 4.0
Sammanfattning
In this work we apply machine learning as a conducive method towards identifying previously unstudied patterns in chromosome interaction data sets. We rst use supervised learning to show that patterns identi ed by a user can be learned by tensor ow models, and then transition into unsupervised methods to delve even more deeply into the possibilities of discovery without human intervention.
![GENE 245 Project Machine Learning for HiC data](https://writelatex.s3.amazonaws.com/published_ver/4135.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240727T031819Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240727/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=6dee6cb7ec57212a3420730cf4b2d0bbb6cb334535973a3bb8ccb16fc6b20f27)