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Introductory course in mathematical, statistical and computational biology for experimental biologists [1 credit (year-round)]

Basic Course in Mathematical, Statistical and Computational Biology for Experimental Biologists.

In 2021, we will use Zoom to teach.

Join the Zoom lecture from the link that appears in each individual's PandA account.

Name of person in charge:
Tadashi Imayoshi (Graduate School of Life Sciences)

Yusuke Suzuki (Graduate School of Life Sciences)

Kenta Terai (Graduate School of Medicine)

Takeshi Hirashima (Graduate School of Life Sciences)

Dividend grade: Master
Number of credits: 1
Opening period: All year
Day time: 5th month (16: 30-18: 00)

Class format: Lectures / practices

Language used: Japanese

Class outline / purpose:
We provide introductory knowledge and techniques of mathematical, statistical, and computational biology necessary for interdisciplinary fusion research in recent life sciences. The main target is graduate students who belong to the experimental laboratory of life science and are interested in mathematics. The purpose is to be able to utilize it in my research.


Attainment target:
Based on the above knowledge, it will be possible to describe various life phenomena with mathematical models, verify operating principles and extract working hypotheses through computer simulations.

2021 class schedule(schedule):

April 26 Class Guidance, Basics of Differential Equations

May 24 Introduction to programming, introduction to dynamical systems

June 28 Introduction to Systems Biology 1 (Cell I / O System, Network Motif)

July 26, Introduction to Systems Biology 2 (Feedback Loop)

August 23 Agent-based modeling (cell migration, herd)

September 27 Diffusion, pattern formation, basics of partial differential equations

October 25 Stochastic process / probability distribution / descriptive statistics

November 22 Biostatistics (mainly test)

December 27 Life Science Data Analysis

January 24 Image Processing Basics for Bioimaging Data

February 28 Image processing application for bioimaging data ―― 1

March 28 Image processing application for bioimaging data ―― 2

* Attendance as the lesson plan and contents will be explained in the lecture (Zoom) on April 26th.

Grade evaluation method / viewpoint and achievement level:
【Evaluation method】
Evaluate by a small report submitted to the instructor. Details will be explained at the start of the course.


【Evaluation criteria】
Emphasis on attendance and report submission.

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