Subject: Subject Sylbus: Introduction to Bioinformatics - 236523 (Current)

Introduction to Bioinformatics - 236523
Credit
Points
2.5
 
Given In
Semester
a
 
  Lecture Exercise Laboratory Project or
Seminar
House
Work
Weekly
Hours
2 1     2

Determination of the grade according to progress during the semester and the submission of the final thesis


Prerequisites ( Topics in Biology 134127
and Introduction to Computing with Matlab 234127 )
or ( Biology 1 134058
and Programming )C( 234112 )
or ( Topics in Biology 134127
and Programming )C( 234112 )
or ( Biology 1 134058
and Introduction to Computer Science 234114 )
or ( Topics in Biology 134127
and Introduction to Computer Science 234114 )
or ( Biology 1 134058
and Introduction to Computing with Python 234128 )
or ( Topics in Biology 134127
and Introduction to Computing with Python 234128 )
or ( Biology 1 134058
and Introduction to Computing with Matlab 234127 )
 
Overlapping Courses Tools in Bioinformatics for Life Science 134158
Introduction to Bioinformatics 234523
Introduction to Bioinformatics M 234525


The Course Will Introduce Algorithmic, Statistical, and Machine Evolution, and Disease Mechanisms. Every Lecture We Will Present a Topic from the Field of Bioinformatics, Including Its Biology Background, and Discuss Computational Concepts for Problem Solving. the Biological Applications We Will Deal with Include: Genetic Sequence Analysis, Gene Expression Analysis, Genomic and Epigenomic Regulation, Protein Folding, Genetic Variation and Associations, Disease Mapping, Population Genetics, Cancer Genomics and Single-Cell Genomics. We Will Also Learn to Apply the Principles by Using Basic Tools and Major Databases in the Bioinformatics Field. the Course Includes 4 Hw Assignments and a Final Project to Be Presented in a Poster Day.

Learning Outcomes
By the End of the Course the Students Will Be Able to:
1. Explain Fundamental Life Sciences Principles.
2. Explain and Demonstrate Key Algorithms and Sdtatistical Tools That Are Used to Solve Problems in Bioinformatics.
3. Analyze Different Types of Biological Data by Utilizing Computational Tools.
4. Design and Execute a (Small-Scale) Research Project Using Biological Databases and Computational Tools.


Timetable to semester 01/2022 2202/2023 Winter Semester
RoomBuildingHourdayLecturerExercise
Lecture
no.Registering
Group
9טאוב10:30-12:30WednesdayDr. Aran DvirLecture1011
5טאוב09:30-10:30Monday Exercise11
 
9טאוב10:30-12:30WednesdayDr. Aran DvirLecture1012
6טאוב13:30-14:30Thursday Exercise12


Textbooks
PublishedPublisherAuthorsBook
1998cambridge university pressrichard durbin, et albiological sequence analysis: probabilistic models proteins and nucleic acids
2001wiley-intersciencerichard duda, peterhart, david storkpattern clasification

Created in 29/09/2022 Time 01:41:16