Summary of MBB211 (1st sem AY2020-2021) JGCA1-PairwiseAlignment

Main Ideas and Concepts

• Introduction to Pairwise Alignment

  Pairwise Alignment is a method used to compare two biological sequences (DNA, RNA, or protein) to identify regions of similarity and dissimilarity. Dr. George Hill Angeles is the instructor for the course, emphasizing the importance of alignment in bioinformatics.

• Basic Concepts of Pairwise Alignment

  Pairwise Alignment involves aligning two sequences to maximize their identity and conservation of residues. The alignment can reveal identical residues, mismatches, gaps, and regions of similarity.

• Manual vs. Computational Alignment

  Short sequences can be aligned manually, but longer sequences require computational methods due to complexity. Statistical algorithms are used to compute the best alignment for long sequences.

• Types of Alignments
  • Global Alignment: Aligns entire sequences, using algorithms like Needleman-Wunsch.
  • Local Alignment: Focuses on the highest scoring matches within sequences, using algorithms like Smith-Waterman.
• Scoring Systems

  Alignment scores are derived from substitution matrices (e.g., PAM, BLOSUM) that account for evolutionary changes in amino acids over time. The scoring system includes penalties for mismatches and gaps.

• Identifying Similarity and Identity
  • Identity: Same residues at specific positions.
  • Similarity: Residues that are not identical but share biochemical or structural properties.
  • Percent Similarity: A measure of how many residues are identical or similar, excluding gaps.
• Substitution Matrices

  PAM (Percent Accepted Mutation) and BLOSUM (BLOcks SUbstitution Matrix) are commonly used matrices for scoring alignments based on evolutionary data. Different matrices are suited for different types of sequences (e.g., closely related vs. distantly related).

• Dot Matrix Alignment

  A visual representation of Pairwise Alignment where matches are indicated by dots, helping to identify regions of similarity, gaps, and repeats.

• Computational Steps for Pairwise Alignment
  • Set Up the Matrix: Write sequences in a matrix format.
  • Score the Matrix: Use chosen scoring systems to fill in the matrix.
  • Identify Optimal Alignment: Determine the best scoring alignment based on the computed scores.
• Future Topics

  The next lectures will cover the BLAST algorithm, which is a specific application of Pairwise Alignment for searching sequence databases.

Methodology / Instructions

• Pairwise Alignment Steps
  1. Set Up the Matrix: Write one sequence across the top and the other down the side of the matrix.
  2. Score the Matrix: Choose a substitution matrix (PAM/BLOSUM) and define gap penalties. Fill in the matrix based on matches, mismatches, and gaps.
  3. Identify Optimal Alignment: Trace back through the matrix to find the highest scoring alignment.

Speakers / Sources Featured

• Dr. George Hill Angeles: Instructor and lecturer from the Philippine Genome Center program for agriculture.

Notable Quotes

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Category

Educational

Video