Chapter 1. Molecular Biology and Biological Chemistry
What is Bioinformatics?
Genetic Material: DNA, nucleotide bases (A, T, C, G)
DNA structure, base pairs and hydrogen bonding, orientation, reverse complement
DNA Replication: DNA polymerase
RNA role in cell
Central dogma: transcription, translation, RNA polymerase, ribosomes
Codons: amino acid encodings, read frames,
Transcription process in Prokaryotes vs. Eukaryotes
Eukaryotic genes: intron, exons, splicing, alternative splicing
Translation (elongation) process: tRNA, rRNA, mRNA, anticodon,
Regulation of protein production: regulatory region, untranslated regions, start codon, stop codon, transcription factor, regulatory factor
Protein Structure and function: primary, secondary, tertiary, quaternary
Amino acid R-groups and their properties: polar/nonpolar, hydrophobic/hydrophilic
Chemistry Review: elements, atoms, neutron, protron, electron, isotopes, ions
Quantum numbers, chemical reactivity, covalent bonding, valence
Electronegativity, polar bonds and hydrogen bonding, hydrophilic, and hydrophobic
Molecular Biology Tools: restriction enzyme digests, blunt ends and sticky ends,
gel electrophoresis, blotting, probe, hybridization, microarray (DNA chip)
cloning, PCR reaction, DNA sequencing methods
Genemoic Information content: C-value, C-value paradox, junk DNA
Chapters 2. Database searches and Pairwise Alignments
dot plots, alignment, homologs, simple alignment, gap, origination penalty, length penalty
mutation, insertions and deletions, indels
Scoring Matrices: BLAST matrix
similarity vs. distance
Amino acid scoring matrices: PAM-1, PAM-1000, PAM-250, BLOSUM-62, BLOSUM-80
Dynamic Programming: general idea
Needleman and Wunsch Algorithm for global alignment: partial alignment score table and determining optimal alignment(s)
Semiglobal alignment: partial alignment score table and determining optimal alignment(s)
Smith-Waterman Algorithm for local alignment: partial alignment score table and determining optimal alignment(s)
Database searches:
BLAST and its variations, general steps of the algorithm
FASTA algorithm, general steps of the algorithm
Search results: alignment score (S), P scores, E scores, statistical significance
Multiple sequence alignment: Problem with dynamic programming approach, CLUSTAL