Computational Biology

A quick summary of the contents:

Lab1

Preparations

Lab2

Analzying sequences, generating phylogenetic trees, and identifying sequences using BLAST
Tools: Biophython, BLAST, matplotlib

Lab3

Determine statistics on word occurences and Zipf's law
Tools: matplotlib

Lab4

Investigate and document the relationships between genes, enzymes and pathways
Tools: SQL(sqlite3), pandas, Biopython, entrez

Lab5

Obtain secondary structures of folded RNA investigate riboswitch scenarios in the paper by Penchovsky and Breaker
Tools: RNAfold

Lab6

Run bowtie analysis on strains of Shewanella oneidensis, solving contamination and analyzing coverage statistics
Tools: bowtie2, samtools, matplotlib

Lab7

Investigate compression algorithms on generated binary and fasta files and real biological information
Tools: numpy, matplotlib, gzip, bzip2, pbzip2, ArithmeticCompress, entrez

Lab8&9

Assemble genome de novo using PacBio and Illumina reads, extract quality statistics, identify taxonomic origin, and obtain two genome annotations via different pipelines
Tools: spades, assembly-stats, rna_hmm3, bedtools, SeqMatch, BASys, RAST