Course Identification

Mathematics for biologists
20253141

Lecturers and Teaching Assistants

Dr. Josephine Shamash
Ziv Huppert

Course Schedule and Location

2025
First Semester
Sunday, 09:15 - 11:00, Science Teaching Lab 1
Monday, 11:15 - 12:00, Science Teaching Lab 1
03/11/2024
27/01/2025

Field of Study, Course Type and Credit Points

Life Sciences: Lecture; 3.00 points
Life Sciences (Brain Sciences: Systems, Computational and Cognitive Neuroscience Track): Lecture; 3.00 points

Comments

On Sunday December 8 the course will be held at Musher conference room
On Sunday December 15 the course will be held at Musher conference room
On Sunday January 12 2025 the course will be held at Science Teaching Lab 2
On Monday January 27 2025 the course will be held at Musher conference room
Hours remain the same

Prerequisites

No

Restrictions

15

Language of Instruction

English

Attendance and participation

Expected and Recommended

Grade Type

Numerical (out of 100)

Grade Breakdown (in %)

20%
80%

Evaluation Type

Examination

Scheduled date 1

02/02/2025
N/A
1000-1300
WSoS Room B

Scheduled date 2

20/03/2025
N/A
1000-1300
WSoS Room B

Estimated Weekly Independent Workload (in hours)

N/A

Syllabus

 

The course will introduce students who come from a non-mathematical background to basic mathematical tools that are essential for much of today's biological research: differential equations, linear algebra and linear systems theory, and a brief introduction to Fourier analysis. The intention is to provide a firm mathematical background for applications to be covered in advanced courses in Systems Biology and in Theoretical Neuroscience.

Topics to be covered:

  • Introduction to differential equations.
  • First-order ordinary differential equations: linear equations, separable equations, modeling with first-order equations, equilibrium solutions. Examples of applications include: RC circuits and current-integration by neurons.
  • Introduction to linear algebra: Matrix and vector operations.
  • Determinants.
  • Systems of linear equations.
  • Linear transformations.
  • Matrix diagonalization. Systems of linear differential equations, Relation of matrix diagonalization to solutions of systems of differential equations. Examples of applications include: predator-prey interactions.
  • Inner product spaces.
  • Orthogonal and orthonormal bases.
  • Introduction to Fourier analysis.
     

 

Learning Outcomes

Familiarity with basic mathematical tools that are essential for much of today's biological research: ordinary differential equations, linear algebra and linear systems theory, and a brief introduction to Fourier analysis. Knowledge sufficient to provide a mathematical background for applications to be covered in advanced courses in Systems Biology and in Theoretical Neuroscience.

Reading List

N/A

Website

N/A