University of Tsukuba | Grad. Scho. Syst. and Info. Eng. | Dept. Comp. Sci. | List of Courses
基礎計算生物学_E
Instructor(s)
T. Sakurai, M. Shoji, Y. Inagaki, S. Makino, M. Sato, K. Morikuni
E-Mail sakurai@cs.tsukuba.ac.jp, yuji@ccs.tsukuba.ac.jp, mshoji@ccs.tsukuba.ac.jp, maki@tara.tsukuba.ac.jp, msato@cs.tsukuba.ac.jp, morikuni@cs.tsukuba.ac.jp
URL
Office hours
Cource# 01CH107,02RA210
Area Information Mathematics and Modeling
Basic/Advanced
Course style Lecture
Term Fall AB
Period Thu1,2
Room# 3B301
Keywords Computational Science, Computational Biology, High Performance Computing
Prerequisites
relation degree program competence Knowledge Utilization Skills,Research Skills,Expert Knowledge
Goal
Outline In this lecture, we will understand basic methods to solve a wide variety of problems by using a program in the field of biology. Explain molecular phylogenetic analysis molecular dynamics method, modelization and algorithm of a phenomenon, high- performance computation (HPC), and component analysis.
Course plan
  1. 1st week: Mathematical modeling and algorithms (1)
    Overview of the course, mathematical modeling and numerical simulation
  2. 2nd week: Mathematical modeling and algorithms (2)
    Computational algorithms, molecular simulaiton and eigenvalue solver
  3. 3rd week: Biodiversity
    Biodiversity on earth and global eukaryotic phylogeny
  4. 4th week: Basics of molecular phylogeny
    Maximum-parsimony, distance, maximum-likelihood, and heuristic tree search
  5. 5th week: Theoretical methods for biology
    Methods and applications of classical molecular dynamics
  6. 6th week: Quantum mechanics for biology
    Methods and applications of quantum mechanical methods
  7. 7th week: Independent component analysis and blind signal separation
    Basic theory of independent component analysis and its application to blind signal separation
  8. 8th week: Sparse component analysis and blind signal separation
    Basic theory of sparse component analysis and its application to blind signal separation
  9. 9th week: High performance computing technology (1)
    Parallel processing and parallel systems
  10. 10th week: High performance computing technology (2)
    Parallel programming, and trends of high performance computing
Textbook
References
Evaluation
TF / TA
Misc.
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