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