gracevikman / ucsc_bme160

This repo contains all my projects from BME 160 Research Programming course at UC Santa Cruz.

BME 160: Research Programming in the Life Sciences

This repo contains assignments from the BME160 course at UCSC which focused on programming in Python to manipulate biological data. I took this course in Spring 2021.

Lab 2:

1. converter.py: Convert from amino acid abbreviations to DNA/RNA codons and vice versa.
2. coordinateMathSoln.py: Calculate bond length and angles between C-Ca-N.
3. fastqParse.py: Filter out run data from FASTQ files.
4. seqCleaner.py: Returns sequence with uppercase and replaces block of ambiguous bases with their count.

Lab 3:

1. proteinparams.py: Calculates protein properties such as molecular weight, amino acid composition, theoretical PI, etc.

Lab 4:

1. FastAreader.py: Reads FastA files for analysis.
2. genomeAnalyzer.py: Calls FastAreader and nucparams and formats their outputs.
3. nucparams.py: Calculates sequence properties such as amino acid composition and codon usage.
4. sequenceAnalysis.py: Contains NucParams,FastAreader, and ProteinParams classes.

Lab 5:

1. findORFs.py: findORFs will be able to return possible ORFS for a set of parameters, including several start codon(s), stop codon(s), if longest gene is desired, and minimum gene length. Calls fastAreader and ORFfinder from sequenceAnalysis.py.
2. sequenceAnalysis.py: Updated to include ORFfinder class to find all possible open reading frames.

Lab 6:

1. findUnique.py: Takes FASTA sequences of mitochondrial tRNA and returns unique (does not occur in any other sequence) and essential (minimized) tRNA sets.
2. sequenceAnalysis.py: Inludes ORFfinder, NucParams, FastAreader, and ProteinParams classes.