Course Identification
Mathematics for biologists
Lecturers and Teaching Assistants
Dr. Josephine Shamash
Course Schedule and Location
Sunday, 09:15 - 11:00
Monday, 12:15 - 13:00
11/12/2023
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
Life Sciences (ExCLS Track): Lecture; Elective; 3.00 points
Comments
This course will be held on zoom
Registration by
03/10/2023
Attendance and participation
Estimated Weekly Independent Workload (in hours)
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.