Bioinformatics Program
Faculty and Staff
: Academia
Sinica
National Yang Ming University - National Taiwan University - National Central University
|
Academia Sinica has established the Taiwan International Graduate Program (TIGP) in collaboration with a consortium of key national research universities in Taiwan. The purpose of the program is to develop the research manpower pool in those modern multidisciplinary fields that are important in the future economical and social development of Taiwan and to enhance the innovative potential and academic standards of research in these and related fields.
TIGP will offer Ph.D. programs in only selected disciplines to be agreed upon between Academia Sinica and its national research universities partners. It is the intent of the Program to offer Ph.D. degree programs only in inter-disciplinary areas in the physical sciences, applied sciences, engineering, biological and agricultural sciences, health and medical sciences, and humanities and social sciences.
Academia Sinica will assume principal oversight of the academic options of the Program. It will provide the intellectual leadership, the research resources, and the research and physical facilities. Qualified and interested faculty members of the participating national research universities are invited to join the various programs as affiliated faculty of the Program, and participate in the teaching of courses, supervision of research, and mentoring of the international graduate students.
|
The TIGP Program on “Bioinformatics”
|
The Taiwan International Graduate Program has been established to attract highly qualified young researchers both from home and abroad in order to help jump-start the development of several frontier areas that are crucial to the future development in science and technology. Specific graduate programs have been developed to enhance the innovative potential and academic standards of research on these and related fields. Within this context, the graduate program on “Bioinformatics” is designed to offer specific training and research opportunities to Ph.D. students interested in working on this particular area.
The TIGP Program on Bioinformatics (BP) is a joint-degree program sponsored by Academia Sinica (Institute of Information Science, Institute of Statistical Science, and Institute of Biomedical Sciences), National Tsing Hua University, National Chiao Tung University and National Yang Ming University. Additional teaching support will be available from other major research universities in Taiwan. Unlike most Bioinformatics programs offered in other universities that adopt existing courses in various departments, our courses are specifically designed for BP students and taught by active and experienced researchers in bioinformatics. The program provides interdisciplinary training and research opportunities that seamlessly integrate the related areas so that students can be well-prepared for independent research in this new, fascinating areas of bioinformatics. We will focus on genetics and proteomics study and emphasize data transfer, data analysis, biological information and biological feature extraction, knowledge management using advanced computation methodologies and computer science technology. |
|
(1) Computational biology: This area focuses on the design of various algorithms for sequence analysis, gene prediction, disease gene mapping, motif finding, and gene networks.
(2) Biological knowledge management: This area focuses on the integration of various heterogeneous databases, biological knowledge representation, automation of pipeline experiments, and the construction of various annotation databases. In addition, biological literature search is also a crucial component.
(3) Bioinformatics applications: This area focuses on using existing tools to analyze biological sequences, microarray data, proteomic data, etc. Statistical analysis and data mining techniques will be used to reach the goal of "information-driven biomedical research."
(4) Computational structural biology: This area focuses on protein structure prediction and classification, automated biomolecule docking, and molecular dynamics.
|
· Institute
of Information Science
Der-Tsai Lee
Ph.D., University of Illinois, Urbana
Computational geometry, computational molecular biology
Wen-Lian Hsu
Ph.D., Cornell University
Algorithms, computational molecular biology, intelligent agents, knowledge management, natural language processing
Chun-Nan Hsu
Ph. D., University of Southern California
Intelligent agents, machine learning
Ting-Yi Sung
Ph.D., New York University
Algorithms, knowledge management, computational molecular biology
Ming-Tat Ko
Ph.D., National Tsing Hua Univeristy
Algorithms, computational molecular biology, visualization
Tsan-Sheng Hsu
Ph.D., University of Texas, Austin
Algorithms, medical informatics
Hong-Yuan Liao
Ph.D., Northwestern University
Image processing, computer vision
Wen-Liang Hwang
Ph.D., New York University
Signal and image processing, computer vision
Hsueh-I Lu
Ph.D., Brown University
Algorithms, computational molecular biology
Chun-Chieh Shih
Ph.D., National Central University
Image processing, computational molecular biology
· Institute of Biomedical
Sciences
Lan-Yang Chang
Ph.D., Vanderbilt University
Genomics, bioinformatics
Ming-Jing Hwang
Ph.D., University of Pittsburgh
Computational biology, bioinformatics, structural biology, genome science
Wen-Chang Lin
Ph.D., Case Western Reserve University
Bioinformatics, tumor biology
Shen-Jang Fann
Ph.D., University of Iowa
Genetic statistics, genetic epidemiology
Song-Kun Shyue
Ph.D., Univ. of Texas, Houston
Gene therapy, gene and protein expression analysis
· Institute of Statistical
Science
Chun-Hou Chen
Ph.D., University of California, Los Angeles
Bioinformatics, Information visualization, multivariate analysis, statistical computing
Shwu-Rong Shieh
Ph.D., University of Wisconsin, Madison
Analysis of microarray gene expression data, construction of gene networks and biomedical pathways, directional data
Lung-An Li
Ph.D., State University of New York, Albany
Sampling survey, past global changes
Shao-Wei Cheng
Ph.D., University of Michigan
Statistics in industry, experimental design, fractional factorial designs
Tsung-Hsi Tsai
Ph.D., University of Wisconsin, Madison
Markov chains, analysis of algorithms
Yi-Hau Chen
Ph.D., National Taiwan University
Biostatistics, statistical methods, public health, operations research
· Institute
of Botany
Yue-Ie Hsing
Ph.D., University of Illinois
Comparative genomics, global analysis of gene expression, positional cloning of specific rice genes, transposable elements of plant genome
· Institute of Molecular
Biology
Y. Henry Sun
Ph.D., Caltech
Developmental biology, gene regulation
National Chiao Tung University
Jenn-Kang Hwang
Ph.D., University of Southern California
Computational structural biology, molecular simulation, QM/MM simulation
Yuh-Jyh Hu
Ph.D., University of California, Irvine
Bioinformatics, machine learning, data mining, artificial intelligence
Hong-Hsin Lu
Ph.D., Cornell University
Function estimation, wavelets, survival analysis, reliability, statistical computing, medical images, and bioinformatics
Chuan Yi Tang
Ph.D., National Chiao Tung University
Algorithms, computational biology, bioinformatics, protocol testing, parallel processing
P. C. Lyu
Ph.D., New York University
Computational structure genomics, de novo protein design
Ueng-Cheng Yang
Ph.D., Princeton University
Information-driven biomedical research: integration of genome, transcriptome, and proteome information, disease gene hunting
Wailap Victor Ng
Ph.D., University of Massachusetts
System biology
Jen-Hsiang Chuang
Ph.D., Columbia University
Natural language processing, data mining
Chuan-Hsiung Chang
Ph.D., University of Southern California
Comparative genomics, genome engineering
Cheng-Yan Kao
Ph.D., University of Wisconsin, Madison
Genetic algorithms, bioinformatics
Kuan-Mao Chao
Ph.D., The Pennsylvania State University
Algorithms, computational molecular biology, network design
Chih-Jen Lin
Ph. D., University of Michigan
Support vector machine, semi-definite programming
Hung Chen
Ph.D., University of California, Berkeley.
Efficient semi-parametric modeling, locating maximizer of a nonlinear function, missing covariate problem and continuous time Markov chain with applications to cancer modeling
Jorng-Tzong Horng
Ph.D., National Taiwan University
Database, data warehouse, genetic algorithm, bioinformatics
Tsung-Shan Tsou
Ph.D., The Johns Hopkins University
Statistical principle, statistics in medicine, biostatistics, statistical inference
There are three types of courses: (1) Required courses: courses to be taken by all students. (2) Core courses: basic courses in molecular biology and computing methods. Students with sufficient prior background can waive some of these courses (if approved by the program committee). (3) Elective courses. A total of 24 credit units are required for graduation.
1. Directed Reading (1 credit unit, 1.5 hours/week for two semesters)
2. Seminar (1 credit unit per semester, a total of 4 credit units)
B1. Basic molecular biology for bioinformatics (3 credit units)
● Functions of the molecules and organelles in the cell
● Basic strategies of biochemistry-assay and cell fraction
● Enzyme kinetics and mechanisms
● Major pathways and principles in biology
● Introduction to genetics
● Introduction to genes and gene structures
● Gene expression & regulation
● DNA replication & other perpetuations
● Genetic engineering
● Introduction to protein structures
● Forces that determine protein structures
● Protein structure determination
● Protein structure prediction
B2. Basic molecular biology for bioinformatics II (3 credit units)
● Genome sequence acquisition & analysis
● The human genome project
● Genomic variations
● Genomics Databases & Bioinformatics Applications (I)
● Genomics Databases & Bioinformatics Applications (II)
● Introduction to statistical genetics
● Introduction to evolutionary genomics
● DNA Microarrays: principles and applications (I)
● DNA Microarrays: principles and applications (II)
● Transcriptome - related bioinformatics databases & applications
● Protein informatics
● Structural proteomics & drug design
● Protein-protein interaction network and databases
● Databases of biochemical pathways
C1. Biological computing I：Design and analysis of algorithms for biologists (3 credit units)
l Introduction to data structure
l Growth of functions & Asymptotic notation
l Recurrence relations
l Sorting - insertion sort, quicksort, mergesort, heapsort, radix sort
l The greedy method
l The divide-and-conquer strategy
l Tree searching strategies
l Dynamic programming
l Graph algorithms - Representations, BFS, DFS
l Graph algorithms – MST
l Data mining
l NP-completeness
l Approximation algorithms
l Case studies of computational biology problem specification and modeling solutions
C2. Biological computing II (3 credit units)
l Dynamic programming – applications (alignment, structure prediction )
l BLAST and its variations
l Stochastic processes and probability theory
l Hidden Markov Models
l Basic statistics: random variables, distributions, estimation, testing hypothesis, randomization
l Regression
l Experimental design and ANOVA
l Sampling and resampling
l Statistical graphics
l Analysis of microarray data: data pre-processing, missing data imputation, permutation test
l Association rules: categorical and continuous random variables, relationship among multiple variables
l Multivariate analysis: clustering, PCA, canonical correlation, classification, etc
l Statistical genetics
At least one of the following two courses C3 and C4:
C3. Advanced algorithms in computational biology (3 credit units)
l String matching - KMP, Boyer-Moore
l Sequence analysis algorithms
l Multiple sequence alignment
l Restriction mapping - Double digest problem
l Map assembly - Interval graphs SVM
l Gene-prediction algorithms
l Genome rearrangements
l Phylogenetic trees construction
l Structure prediction
l Protein classification
● Computational proteomics
● Selected topics
C4. Advanced statistical methods (3 credit units)
l Introduction to microarray experiments: principles and experimental design
l Biomedical image analysis (2D gel, DNA and protein chips)
l Advanced analysis of microarray data
l Markov Chain Monte Carlo
l Exploratory data analysis and visualization
l Cluster analysis: hierarchical clustering, k-means, self-organizing maps, gene shaving, plaid models, dimension reduction, principal component analysis, singular value decomposition, correspondence analysis, multi-dimensional scaling
l Supervised learning: discriminant analysis, neural networks, error-rate concepts, support vector machines, tree-based methods, bagging, boosting
l Bayesian networks: graphical probabilistic models and related computation algorithms, applications to genetic networks
l Comparative genomics
l Genetic modeling
l Current research topics of interest
L1. Lab work (1 credit unit, spend 6 hours/week working in a lab of student's choice for one semester)
This courses can be taken more than once, but not with the same lab.
TA experience is an essential part of our program. Thus, all students from TIGP must serve as TA for at least one semester. Additionally, in order to help their daily lives’ communication with the local people, international students are required to take a required one year course of Mandarin Chinese.
The program emphasizes research training and developing one’s capability and self-confidence for independent research. Once entering this program, students can choose mentors and thesis advisors for their study according to their research interests. Students are required to advance to doctoral candidacy by the end of the third year or the beginning of the fourth year. A student may petition for probation; but he or she still needs to complete this requirement by the end of the fourth year in the program.
In this program, we invite faculty from various disciplines to participate. This program adopts a team-teaching system, where each faculty member teaches a subject according to his or her expertise. In keeping up with the international trend, all courses are offered in English.
Requirements for advancing to candidacy include:
1. Satisfactory completion of coursework: core courses and 24 credit units.
2. Satisfactory performance in a written qualifying exam (must finish before the end of the third year), which will be offered once every year after the winter break. The exam will cover C1, C2, B1, B2 and at least one of C3 or C4.
3. A TOEFL score of 600 is required for non-native speakers.
4. Research Plan approved by director of research group.
5. Successful defense of the above research plan.
1. At least two (full) papers presented at leading international conferences (such as
RECOMB, ISMB and PSB) and journals in the field as approved by the exam committee.
2. Ph.D. thesis.
3. Successful defense of the thesis, in which the candidate must show that she/he has
made original and substantial scientific contribution.
Admission to the Ph.D. Program
The Program admits students to the fall semester only. The following materials and qualification are required for application:
1. Master’s or Bachelor’s degree in biology, computer science, statistics or other
related areas.
2. Fluency in English: TOEFL score of 550 (213 on computer-based) or higher. However, this can be waived for those who have obtained bachelor or master
degrees from English speaking countries.
3. GRE score from the general exam. For the Bioinformatics Program, an applicant may submit one of the following material in place of a GRE general test score:
· Any evidence of research ability such as papers published in international conferences or journals.
· Satisfactory performance in any course or project work related to the design of algorithms or probability such as discrete mathematics, algorithms, computational complexity, data structure, probability, computer architecture, compiler, and computer programming.
4. (Required) Basic programming skills
5. A Statement of Purpose that includes a research plan
6. Official transcripts from academic institutions attended after senior high school
7. Three letters of recommendation
8. GRE score from related subject exam (highly recommended, but not mandatory)
Applicants in Taiwan can take the General English Proficiency Test (GEPT)
administered by the Language Training and Testing Center. Applicants are required
to submit their high-intermediate level certificate when applying for admission.
The above submitted application materials will not be returned to applicants under
any circumstances. The complete application materials must reach TIGP before March 31, 2005.
Please send them to:
Admission Office
Taiwan International Graduate Program
128, Sec. 2, Academia Road
Nankang, Taipei 115
Taiwan
Student Status and Degree Conferral Policy
For administrative reasons, students will need to officially register at our partner institutions, i.e. National Tsing Hua University, National Chiao Tung University or National Yang Ming University, depending on their research interests. Upon completion of our program, students will receive a diploma of Ph.D. degree from the designated partner institution and a certificate jointly signed by the President of Academia Sinica and the President of the partner institution.
The payment of tuition fees
(about US$ 1,500 per year) are due upon registration.
The TIGP will provide full fellowship support for all graduate students for 3 years. In subsequent years, the financial support for outstanding students will be in general in the form of graduate research assistantships provided by the National Science Council or Academia Sinica. The stipend levels are about NT$ 32,000 (about US$ 950) per month.
Four months after they receive their student I.D., the students will qualify for Taiwan’s National Health Insurance Program. The students pay the same premium (about US$ 210 per year) as all the Taiwan citizens and will be entitled to the same medical coverage.
Options include on-campus housing and off-campus housing. A dormitory building for TIGP graduate students near the Academia Sinica campus is under construction. Until this structure is completed, a block of double rooms with bath have been set aside in the Guest House of the Activity Center of Academia Sinica. This type of housing will be available to the TIGP graduate students at reasonable costs. Off-campus private housing is generally more expensive. Rents for off-campus apartments range from NT$ 5,000 - 15,000 per month.
Meals are also available at the Activity Center Cafeteria/Dining Hall, the Café, the Chinese restaurant, and the Western restaurant on the Academia Sinica campus at modest costs.
Correspondence and Information
For general
information concerning TIGP, please contact:
Ms. Nancy
Yang
Administrative Assistant
Taiwan
International Graduate Program
128, Section 2, Academia Road
Nankang, Taipei 115, Taiwan
E-mail: nancyy@gate.sinica.edu.tw
Tel.: 886-2-2789-8050
Fax: 886-2-2789-8045
For information concerning this Program,
please contact:
Dr. Wen-Lian Hsu
Institute of Information Science
Academia Sinica
128, Section 2,
Academia Road
Nankang,
E-mail: hus@gate.sinica.edu.tw
Tel: 886-2-2788-3799 ext 1804
Fax: 886-2-2782-4814
Dr. Ting-Yi Sung
Institute of Information Science
Academia Sinica