CSRU2020/CSRU2021 Biomedical Informatics Syllabus:

Week 1:
INTRODUCTION: Biochemistry/Molecular Biology, Scientific Computing/Informatics,
Genomics, Systems Biology, Genomic Medicine, Pharmacogenomics, ESL Issues

LAB TOPIC: Intro to protein and DNA / Obtaining sequence data from biological samples
EXPERIMENTS: DNA and Protein Purification

Week 2:
MOLECULAR BIOLOGY AND BIOCHEMISTRY
        Central dogma
        Gene structure/protein structure
        Chemical bonds
        Molecular Biology tools and technology
        Genomic perspectives

LAB TOPIC: Interpreting DNA sequences / The anatomy of the gene

EXPERIMENTS: intron/exon sequence analysis

Week 3:
COMPUTATIONAL SCIENCES AND SCIENTIFIC COMPUTING
        Central dogma
        Sequence acquisition
        Sequence alignments
        Database searches and information retrieval
        Algorithms and data analysis
        Machine learning techniques and data mining

LAB TOPIC: transcriptional and translational control / open reading frames
EXPERIMENTS: identifying and testing consensus translation initiation sequences

Week 4:
GENOMICS/PHYLOGENETICS
        Phylogenetic trees
        Distance matrix methods
        Parsimony
        Character-based methods
        Molecular phylogenies
        Tree of life

LAB TOPIC: Computer-assisted sequence comparison 1 / Molecular phylogenies
and evolution
EXPERIMENTS: FastA

Week 5:
GENOMICS: SEQUENCE VARIATIONS
        Prokaryote and eukaryote genomes
        Gene structure and GC content
        Global and local alignment
        Multiple sequence alignment
        Genomic identification
        The ultimate genomic phenotype
        Ethical consequences of genomic variation

LAB TOPIC: protein vs nucleotide sequence analysis
EXPERIMENTS: BLASTP, BLASTN, BLASTX

Week 6:
GENOMICS: GENE EXPRESSION
        Gene expression and serial analysis
        Introduction to microarrays
        Microarray gene expression data structure
        Gene expression data analysis
        Analytical toolds
        Case Study

LAB TOPIC: Introduction to databases
EXPERIMENTS: Gene informatics using NCBI

Week 7:
GENOMICS: PROTEOMICS
        Protein sequences
        Protein 3-D structures
        Protein-interaction networks
        Protein-structure prediction
        Protein classification
        Case Study

LAB TOPIC: ClustalW alignments, introduction to model organisms
EXPERIMENTS: Flybase and Wormbase gene annotation. ClustalW alignment and tree construction

Week 8:
GENOME ONTOLOGY AND SYSTEMS BIOLOGY
        Whole genome perspective
        Integrated protein circuits
        Modeling complex systems
        3-hierachical sets of GO terminology
        Integration of regulators, metabolism, and P-P and P-D interactions

Case Study

LAB TOPIC: Introduction to proteomics

EXPERIMENTS:  protein analysis with ExPasy tools

 
Week 9:
GENOMIC MEDICINE
        From genetics to genomics in medicine
        Diseases and disorders
        Medical diagnostics
        Medical imaging technologies
        Functional MRI
        Personal, private, predictive medicine

LAB TOPIC: Biological approaches to the genome: molecular and genetic screens
EXPERIMENTS: Design and planning of microarray experiments

Week 10:
PHARMACOGENOMICS
        Drug design and discovery
        Ligand screening and docking
        Structure-based virtual screening
        Consensus scoring
        Identification of biomarkers
        Case Study

LAB TOPIC: introduction to microarray data analysis
EXPERIMENTS: analysis of microarray dataset

Week 11:
ESL ISSUES IN BIOMEDICINE AND HEALTH
        Ethical Implications of modern biomedicine breakthroughs
        Social issues arising from current biomedical research
        Legal issues and public policy
        From biological systems to ecosystems
        Common goals toward health and happiness

LAB TOPIC: Bioinformatics Journal Club

Week 12:

ADVANCED TOPICS IN BMH INFORMATICS

Neuroscience (neurobiology, cognitive neuroscience, and computational neuroscience)

Information and Intelligence

Systems Science (natural networks, designed networks, and abstract networks)

Machine learning and Data mining

Social Science

Arts and Humanities

LAB TOPIC: Final Projects Presentation

CSRU 2020/CSRU2021, Syllabus, Hsu/Staff

3/4/07