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Bioinformatics in Python

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Overview

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This course uses Python to analyze biological sequences, covering DNA and RNA operations, FASTA data processing, translation, open reading frames, protein searches, and code refactoring. Exercises draw on Rosalind problems and an NCBI protein search.

Syllabus

Bioinformatics in Python: Intro.
Bioinformatics in Python: DNA Toolkit. Part 1: Validating and counting nucleotides..
Rosalind Problems: Counting DNA Nucleotides.
Rosalind Problems: Python Village.
Bioinformatics in Python: DNA Toolkit. Part 2: Transcription, Reverse Complement.
Rosalind Problems: Transcription and Reverse Complement.
Bioinformatics in Python: DNA Toolkit. Part 3: GC Content Calculation.
Rosalind Problems: GC Content, FASTA File Format, Data Processing.
Bioinformatics in Python: DNA Toolkit. Part 4: Translation, Codon Usage.
Bioinformatics Tips & Tricks: Development Tools Setup.
Bioinformatics in Python: DNA Toolkit. Part 5: Open Reading Frames.
Rosalind Problems: Fibonacci, Rabbits and Recurrence Relations.
Bioinformatics in Python: DNA Toolkit. Part 6: Protein search in a reading frame.
Bioinformatics in Python: DNA Toolkit. Part 7: A search for a real protein from NCBI database.
Bioinformatics in Python: DNA Toolkit. Part 8.1: Code refactoring into a bio_seq class.
Bioinformatics in Python: DNA Toolkit. Part 8.2: Code refactoring into a bio_seq class.
Bioinformatics in Python: DNA Toolkit. Part 9: RNA, Helper functions.
Bioinformatics Tips & Tricks: Hamming Distance.

Taught by

rebelScience

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