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Computational biology projects including sequence alignment mapping, phylogenetic tree creation and data compression algorithms

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Computational Biology

A quick summary of the contents:

  • Lab1: Preperations

  • 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

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Computational biology projects including sequence alignment mapping, phylogenetic tree creation and data compression algorithms

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  • Jupyter Notebook 97.7%
  • Python 2.3%