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This was a project for my bioinformatics class. We studied a couple of motif finding algorithms for finding a potential motif in n many randomly generated DNA sequences. This project 1) randomly generates n many DNA sequences 2) randomly generates a kmer 3) edits up to d many positions in that kmer & inserts that kmer (now motif) into each sequence From here, 4) blindly reads these sequences (with emplaced motifs) and 5) brute force searches all n sequences to find n many motifs with the lowest hamming distance from a consensus string 6) Utilizes Gibbs Sampling algorithm (a randomized algorithm) to find the lowest overall hamming distance from a motif profile Implemented in Swift.

Swift 91.91% C++ 7.14% C 0.94%
swift bioinformatics randomized-algorithm dna-sequencing

dna-motif-search's Introduction

👋 Hey, I'm Madison 👩‍💻✨

  • she/her
  • 🔭🐊 UF c/o 2021

About

  • 💻 interests: mobile📱, statistics, data analysis, bioinformatics🧬, ML, theatre👯
  • 💖 Fave Languages: Swift, C++, Python, R
  • 💌 How to reach me: shoot me an email [email protected]

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