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One of the larger problems in biomedical research is reproducibility: consistent results of the same experiment is often elusive. Another problem is one of complexity — biology is inherently a complex subject and implementing it in computer code often leads to even more complications. Both of these problems can be traced, in part, to the choice of computer languages used when doing experiments.
In this session, we will look at a basic implementation of pattern matching DNA/RNA sequences using traditional code constructs and then reimplement them using F# using functional constructs. We will touch on why the F# solution addresses both the reproducibility problem as well as the code complexity problem. After this session, the attendee will gain a greater appreciation of the power of F# and how it can make complex algorithms simple.
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Rethinking Bioinformatic Algorithms Using F#
Jamie Dixon is a lifelong technologist who spent his childhood in front of green screens and adulthood with his fingers on the keyboard. He is a passionate and continual learner who has moved seamlessly across domains. He is a leader of high-performing teams that deliver high-ROI solutions on-time and on-budget. His current interest is focused on computational genomics and the application of both modern software engineering techniques and the latest in machine learning to improve dna/rna/protein modeling performance and accuracy.