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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 2020, 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:
Kenta Terai (Graduate School of Life Sciences)

Naoki Honda (Graduate School of Life Sciences)
Tadashi Imayoshi (Graduate School of Life Sciences)
Yusuke Suzuki (Graduate School of Life Sciences)
Takeshi Hirashima (Graduate School of Medicine)

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:
It provides an introduction to mathematics, statistics, and computational biology, which are the basic knowledge necessary for interdisciplinary fusion research in life science these days.
The target is graduate students who mainly belong to the experimental life science laboratory and are interested in mathematical, statistical, and computational biology.
The purpose is to understand this knowledge and apply it to 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.

Lesson plan: See itinerary below

  ---- 2020 class schedule(schedule) ----

(Cancelled) April 27: Explanation of class outline, basics and solution of differential equations

May 25: Explanation of class outline, basics and solution of differential equations June 22: Mathematical modeling and numerical analysis by intracellular signal transmission system / ordinary differential equations Introduction to MATLAB July 1x: ODE solver / nerve firing Mathematical model Nullcline July 27: Partial differential equation (reaction diffusion / flow)
August 24: Cell motility, morphogenesis, epithelial dynamics September 28: Statistical basis (probability distribution, stochastic process, etc.)
October 26: Application to machine learning and time series analysis November 30: Bioinformatics, statistical advance, principal component analysis December 21: Multivariate analysis January 25: Image processing basics for bioimaging data Hen February 22: Image processing application for bioinformatics data ―― 1
March 29: Image processing application for bioimaging data ―― 2

* The lesson plan and contents will be explained in the lecture (Zoom) on May 25, so please attend.

Grade evaluation method / viewpoint and achievement level:
【Evaluation method】
Evaluate by a small report submitted to each instructor. Small reports are evaluated based on the degree of achievement of the achievement goal.
Details will be explained at the start of the course.
【Evaluation criteria】
As a general rule, focus on attendance and report submission. After each lecture, we will give a task to judge whether we understand the lecture contents, so we will submit it at the next lecture.

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