Course Identification

Bioinformatics
20243522

Lecturers and Teaching Assistants

Dr. Shifra Ben-Dor, Dr. Elena Fidel
N/A

Course Schedule and Location

2024
Second Semester
Wednesday, 09:00 - 11:00, FGS, Rm C
Thursday, 09:00 - 11:00, FGS, Rm B
10/04/2024
11/07/2024

Field of Study, Course Type and Credit Points

Life Sciences: Lecture; Elective; Regular; 2.00 points
Life Sciences (Molecular and Cellular Neuroscience Track): Lecture; 2.00 points
Life Sciences (Computational and Systems Biology Track): Lecture; 2.00 points
Life Sciences (ExCLS Track): Elective; 2.00 points

Comments

This course will be held by frontal learning.

Prerequisites

No

Restrictions

100

Language of Instruction

English

Attendance and participation

Expected and Recommended

Grade Type

Numerical (out of 100)

Grade Breakdown (in %)

40%
60%

Evaluation Type

Final assignment

Scheduled date 1

N/A
N/A
-
N/A

Estimated Weekly Independent Workload (in hours)

4

Syllabus

This course will teach the data and algorithms behind the most commonly used bioinformatics tools from a biological perspective.  When the course is over, participants should be able to use the data and programs and make informed choices as to the program, the parameters and databases, regardless of the particular site used. Best practices (recommended sites and programs) for various biological contexts will also be taught. In the final project students will take one gene and follow through everything we did in the course on their gene of interest. 

 

Basic topics:

Introduction to Databases

DNA sequencing and assembly

Pairwise comparison

Database similarity searching

Multiple alignment

Motifs, patterns and profiles

Gene Structure

Genome databases and browsers

 

Additional topics (time permitting):

 

Comparative genomics

Protein secondary structure

Gene Ontology

Pathway Analysis

Gene knockdown (miRNA, siRNA, and CRISPR)

 

 

Learning Outcomes

Upon successful completion of the course the students will be able to:

  • Make informed choices as the programs, parameters and databases to use for solving various biological problems

 

Reading List

Links to relevant papers will be provided on the course web page

Website

N/A