OBJECTIVES
<br>This course is designed to introduce the fundamental background and concepts as
<br>well as the state of the art of bioinformatics and systems biology. Especially for
<br>those graduates with information technology background who are interested in
<br>knowing how to find interesting biological problems as a research topic and select
<br>a proper method to deal with biological problems.
<br>We will start with introduction by the teachers to give an overview and backgrounds
<br>related to system biology and bioinformatics. This includes basic concepts about
<br>genetic processes in the cells and related biological databases, bioinformatic
<br>theories, models and software tools.
<br>The teachers will point to many recent trend of computational biology according to the
<br>literature. The students will be assigned to read and present current research
<br>literature in the class. The discussions of the ideas in the class are encouraged
<br>and moderated by the teachers.
<br>
<br>MAIN THEMES AND QUESTIONS TO BE DISCUSSED IN
<br>THE CLASS
<br>The course will encourage students to explore the following topics and problems:
<br>§ How to infer or predict the molecular structure (primary, secondary and tertiary) and functions given 
<br>some background
<br>biological knowledge?
<br>§ How to infer biological interaction and pathway models from microarray data?
<br>§ What are the properties of the molecular interaction networks in a cell?
<br>§ How do these networks interact with each other?
<br>§ How does a biological system (a cell) react under various conditions?
<br>§ How does disease result from disruption of normal cellular activities?
<br>§ How does a drug affect the pathways and interactions of the molecular networks?
<br>§ How accurate can we predict 3D protein structure based on its amino acid sequence?
<br>§ How can we predict protein-protein interactions?
<br>§ How can we predict drug adverse effects?
<br>§ How can we predict protein functions based on its physical chemical properties, similarity networks 
<br>and protein domain
<br>structure information? …
<br>The students are required to learn some biological and bioinformatics databases, bio-informatic analytic 
<br>tools and methods
<br>and choose a biological problem as target research topic to which to seek solution in terms of 
<br>bioinformatics and
<br>systems biology approaches.
<br>The students are also required to present and discuss their target topics in the class and write a term 
<br>project and research
<br>proposal based on their subject of interest, lectures and extra reading of the literature.
<br>
<br>COURSE SYLLABUS
<br>一、課程說明(Course Description)
<br>Objective:
<br>二、指定用書(Text Books)
<br>None
<br>三、參考書籍(References)
<br>四、教學方式(Teaching Method)
<br>English presentation
<br>Introduction Lectures by teacher and invited speakers
<br>Seminar and discussion
<br>Writing term project and research proposal
<br>五、教學進度(Syllabus)
<br>3 week Lectures by teachers (background survey and trends)
<br>§ background on DNA RNA and protein
<br>§ backgrounds on cell organelles and their functions
<br>§ computational algorithms on alignment, optimization, machine learning methods
<br>§ Various biological databases: GenBank, PDB, SCOP, SMART, Drug bank, Pfam, protein protein 
<br>interaction, etc.
<br>1 week invited talks
<br>5weeks discussions on special research topics on assigned readings of literature and led by the instructor
<br>5 weeks presentations by students (problems/working hypothesis, resources, methods/tools and 
<br>proposal)
<br>2 weeks Final presentation of research proposal
<br>
<br>COURSE REQUIREMENTS
<br>1. Attend lectures by teacher and the invited speakers
<br>2 Attend the designated paper discussion (papers will be assigned before the
<br>discussion and read before the class)
<br>3 Presentation a biological database, a bioinformatic tool, a computational theory,
<br>model, algorithm for a biological problem
<br>6 Proposal writing:
<br>§ Problem definition (scope and rationales why)
<br>§ Previous work (What have been done and not done)
<br>§ Aims of research (no more than 3)
<br>§ Discuss Data availability
<br>§ Preliminary result (if any)
<br>§ Possible methods and model to solve the problems encountered and predict the effects
<br>and risks.
<br>Presentation of term project and proposal
<br>
<br>COURSE EVALUATION
<br>Evaluation:
<br>Grade: 40% class presentation, 20% research proposal report, , 30% term project, 10%
<br>participation