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Helixer

Today we have powerful tools to engineer biological systems by changing the
DNA 'source code'. However, biological systems are extraordinarily complex
and knowing which changes to make to bring about a target result is an
ongoing problem. With increasing amounts of high-throughput 'big data'
being produced, Deep Learning is becoming a promising technology to improve
our predictive performance and reduce the effort intensive wet-lab work
required to test biological hypotheses. Here, we specifically focus on
one sub-problem, structural gene prediction. Our prototype Deep Learning
models make ground breaking progress over the existing Hidden Markov Model
based tools (https://doi.org/10.1093/bioinformatics/btaa1044). 

Ongoing work focuses on further improving performance, capturing the 

full biological complexity and developing applicability. 

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