Supplementary Readings

Chapter 1: BLAST and Karlin-Altschul Statistics

• A Model of Evolutionary Change in Proteins
• Identification of Common Molecular Subsequences
• Viral src gene products are related to the catalytic chain of mammalian cAMP-dependent protein kinase
• Basic Local Alignment Search Tool
• Amino Acid Substitution Matrices from an Information Theoretic Perspective
• Applications and statistics for multiple high-scoring segments in molecular sequences
• On-Line Construction of Suffix Trees
• BLAT—The BLAST-Like Alignment Tool
• BLAST Program Selection Guide

Chapter 2: Genome Assembly and Lander-Waterman Statistics

• Genomic Mapping by Fingerprinting Random Clones: A Mathematical Analysis
• A New Algorithm for DNA Sequence Assembly
• The Sequence of the Human Genome
• An Eulerian path approach to DNA fragment assembly
• Whole-genome shotgun assembly and comparison of human genome assemblies
• Velvet: Algorithms for de novo short read assembly using de Bruijn graphs
• How to apply de Bruijn graphs to genome assembly
• Why are de Bruijn graphs useful for genome assembly?
• Evaluation of the impact of Illumina error correction tools on de novo genome assembly
• Human contamination in bacterial genomes has created thousands of spurious proteins
• Scalable Genome Assembly through Parallel de Bruijn Graph Construction for Multiple k-mers

Chapter 3: Coalescent Theory and Ancestral Recombination Graphs

• Geneological Trees, Coalescent Theory and the Analysis of Genetic Polymorphisms
• Comparative immunopeptidomics of humans and their pathogens
• Coalescent-Based Association Mapping and Fine Mapping of Complex Trait Loci
• Mapping Trait Loci by Use of Inferred Ancestral Recombination Graphs
• Approximating the coalescent with recombination
• Genome-Wide Inference of Ancestral Recombination Graphs
• Developments in coalescent theory from single loci to chromosomes

Chapter 4: Hidden Markov Models - The Learning Problem

• Maximum Likelihood from Incomplete Data via the EM Algorithm
• CpG Islands in Vertebrate Genomes
• A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition
• Maximum-Likelihood Estimation of Molecular Haplotype Frequencies in a Diploid Population
• A Gentle Tutorial of the EM Algorithm and its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models
• The EM Algorithm and the Rise of Computational Biology
• What is a hidden Markov model?
• Identification of CpG islands in DNA sequences using statistically optimal null filters

Chapter 5: Clustering Theory and Spectral Clustering

• Gene Expression Clustering with Functional Mixture Models
• Incremental genetic K-means algorithm and its application in gene expression data analysis
• A Tutorial on Spectral Clustering
• Spectral Clustering Based Classification Algorithm for Text Classification
• Spectral clustering via half-quadratic optimization

Chapter 6 Readings: Protein Folding Algorithms

• The Protein Folding Problem
• Introduction to Protein Structure
• Protein Folding Quotes
• Folding on 2D Lattices and the Hart-Istrail Algorithm
• Contact Maps and Skolnick Clustering
• Protein Structure Alignment

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