Our projects on deep Learning for Biomedicine

This front adapts from our legacy website deepchrome.org and introduces updates of a suite of deep learning tools we have developed for learning patterns and making predictions on biomedical data (mostly from functional genomics). Please feel free to email me when you find my typos.

General Background

Biology and medicine are rapidly becoming data-intensive. A recent comparison of genomics with social media, online videos, and other data-intensive disciplines suggests that genomics alone will equal or surpass other fields in data generation and analysis within the next decade. The volume and complexity of these data present new opportunities, but also pose new challenges. Data sets are complex, often ill-understood and grow at a a faster scale than computational capabilities. Problems of this nature may be particularly well-suited to deep learning techniques (see Opportunities and obstacles for deep learning in biology and medicine). The website introduces a suite of deep learning tools we have developed for learning patterns and making predictions on biomedical data (mostly from functional genomics).

Summary of our tasks and tools

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Our technical focus in this direction center on making DNN interpretable.

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Background of Learning: Representation Learning and Deep Learning

The performance of machine learning algorithms is largely dependent on the data representation (or features) on which they are applied. Deep learning aims at discovering learning algorithms that can find multiple levels of representations directly from data, with higher levels representing more abstract concepts. In recent years, the field of deep learning has lead to groundbreaking performance in many applications such as computer vision, speech understanding, natural language processing, and computational biology.

Contacts:

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Thanks for reading!

Best Paper Award for Deep Motif Dashboard

less than 1 minute read

Jack’s DeepMotif paper (Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks ) have received the “best paper awar...