Lecture 1 |
Sequence Alignment |
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- Course introduction
- Overview of bioinformatics
- Introduction to algorithm
- Recursion
- Dynamic programming
- Smith-Waterman algorithm
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Lecture 2 |
Sequence Database Search |
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- Biological databases
- BLAST
- Basic information theory
- Sequence Logo
- Basic theory of computation
- Transformational grammar
- Regular expression
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Lecture 3 |
Motif |
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- String algorithms
- Finite state automata
- Position specific weight matrix
- Markov chain
- Software quality assessment
- Greedy algorithm
- Introduction to graph
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Lecture 4 |
Hidden Markov Model I, Gene Finding I |
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- CpG island
- Decoding
- Evaluation
- Prokaryote gene finding
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Lecture 5 |
Hidden Markov Model II, Gene Finding II |
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- Baum-Welch algorithm
- Pair HMM
- Eukaryote gene finding
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Lecture 6 |
Multiple Alignment |
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- Expectation maximization
- Introduction to Monte Carlo simulation
- Gibbs sampling
- ClustalW
- T-Coffee
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Lecture 7 |
Phylogenetic Tree |
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- Introduction to molecular evolution
- Clustering algorithms
- Maximum parsimony method
- Maximum likelihood method
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Lecture 8 |
Comparative Genomics |
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- Suffix tree
- Genome scale alignment
- Comparative methods to find regulatory regions
- Predicting functions by comparative genomics
- Comparative methods for gene finding
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Lecture 9 |
Genome Sequencing |
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- Whole genome shotgun sequencing
- Emerging sequencing technologies
- Fragment assembly
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Lecture 10 |
Non-coding RNAs |
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- Transformational grammar
- RNA secondary structure
- microRNA prediction
- siRNA design
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Lecture 11 |
Literature Database |
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- PubMed
- MeSH term
- Information retrieval system
- Document clustering
- Gene ontology
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Lecture 12 |
Protein Structure I |
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- Principles of protein structure
- Protein family
- Structural alignment
- Structural classification
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Lecture 13 |
Protein Structure II |
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- Secondary structure prediction
- Introduction to molecular dynamics
- Simulated annealing
- Genetic algorithm
- Homology modeling
- Threading
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Lecture 14 |
DNA Microarray I |
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- Regulatory elements
- Image analysis
- Normalization
- Experimental design
- Gene selection
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Lecture 15 |
DNA Microarray II |
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- Linear discriminant method
- Principal component analysis
- Multidimensional scaling
- Clustering
- Self-organising maps
- Support vector machine
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Lecture 16 |
Proteomics |
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- Peptide mass finger printing
- de novo sequencing
- Spectral analysis
- Protein modification detection
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Lecture 17 |
Metabolomics |
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- Metabolite identification
- Diagnostic marker identification
- Integration of omics data
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Lecture 18 |
Systems Biology |
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- Reconstruction of biochemical networks
- Mathematical representation of reconstructed
networks
- Metabolic pathway databases
- Network modeling tools
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Lecture 19 |
Genetic Epidemiology I |
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- Genetic Markers
- Physical Markers
- Mouse genetics
- SNP and Haplotype
- Mendelian
Inheritance
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Lecture 20 |
Genetic Epidemiology II |
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- Basic Epidemiological and
Statistical Principles
- Familial
Aggregation
- Segregation
Analysis
- Linkage Analysis
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Lecture 21 |
Genetic Epidemiology III |
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- Principles of Population
Genetics
- Testing Candidate Gene
Associations
- Linkage Disequilibrium
Mapping
- Gene
Characterization
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Lecture S |
Spare Time Slot |
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