The course participants will acquire (i) knowledge about the key
problems and challenges, existing resources and databases,
existing software tools, and strategies for analyzing large-scale
data in support of genomics, transcriptomics, proteomics, and
prediction and analysis of biological pathways and networks; and
(ii) skills to design and implement simple computational tools to
uncover hidden information from high-throughput biological
experimental data.

The course is designed for students who have taken the BCMB 8210
or MIBO 8110L course or equivalent and already have basic
knowledge about genomic sequences, gene expression, protein
structure and functions, and pathways and networks.  The course
will provide an in-depth coverage of each topic.  Students are
required to carry out a term project focused on one problem,
provided by the course instructor, selected from one of the
following four areas:  genome analyses, gene expression data
analyses, protein function prediction, or inference of biological
pathways and networks.  The outcome of the project will be a
software tool for solving the given problem, along with a project
report.

By the end of the course each student should be able to:
1)  analyze and interpret large-scale genomic DNA sequence and 
    gene expression data by using existing software tools and 
    resources.
2)  predict protein functions by using existing software tools 
    and resources;
3)  predict simple biological pathways and network using existing 
    tools, experimental data and other resources, and
4)  design and implement simple computation tools for various 
    data mining and computational predictions.

1.  Advanced methods for gene finding
2.  Advanced methods for sequence motif finding
3.  Ortholog and paralog mapping
4.  Gene ontologies
5.  Genomic structural polymorphism (rearrangements), single 
    nucleotide polymorphism (SNP)
6.  Gene expression alteration (micro-array data analyses)
7.  Protein domain and motif identification
8.  RNA structure prediction, and RNA gene finding
9.  Structure-based protein function prediction
10. Protein-protein interaction networks
11. Pathway and network mapping, simulation, and prediction