Subject: Subject Sylbus: Genomic Data Science - 138046

Genomic Data Science - 138046
Will not be given the year
Credit
Points
2.5
 
  Lecture Exercise Laboratory Project or
Seminar
House
Work
Weekly
Hours
2 1      

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


Prerequisites ( General Genetics 134020
and Biostatistics for Biologists 134154
and Introduction to Computing with Python 234128 )
or ( General Genetics 134020
and Biostatistics for Biologists 134154
and Tools in Bioinformatics for Life Science 134158 )
or ( General Genetics 134020
and Computational Biology 134141
and Biostatistics for Biologists 134154 )
or ( General Genetics 134020
and Biostatistics for Biologists 134154
and Introduction to Bioinformatics 236523 )
or ( Molecular Biology 134082
and Biostatistics for Biologists 134154
and Introduction to Computing with Python 234128 )
or ( Molecular Biology 134082
and Computational Biology 134141
and Biostatistics for Biologists 134154 )
or ( Molecular Biology 134082
and Biostatistics for Biologists 134154
and Introduction to Bioinformatics 236523 )
or ( Biology 1 134058
and Biostatistics for Biologists 134154
and Tools in Bioinformatics for Life Science 134158
and Introduction to Computing with Python 234128 )
or ( Biology 1 134058
and Biostatistics for Biologists 134154
and Tools in Bioinformatics for Life Science 134158 )
 
Identical Courses Genomic Data Science 138047


The Course Will Introduce the Students to Modern Bioinformatics Programming, Accessing Public Genomic Data and Performing State-of-the-Art Genomic Computational Analyses. Throughout the Course, the Students Will Experience Analyzing Different Types of Genome-Scale Data, Including Gene Expression, Epigenetics and in the End of the Course the Student Will Be Able to:
1. Code in R and Use Different Libraries to Perform Advanced Analyses.
2. Download Different Types of Genomic Data from Public Resources, Run a Complete Analytic Pipeline and Extract Insights from the Data.
3. Use Statistical Tools to Extract Insights That Are Robust and Significant.




Textbooks
Compulsory
Book
PublishedPublisherAuthorsBook
Compulsory2021chapman and hall/crc.rafael a. irizarry, michael i. lovedata analysis for the life sciences קישורית תפורסם לסטודנט במהלך השתלמותו.
Compulsory2020  computational genomics with r קישורית תפורסם לסטודנט במהלך השתלמותו

Created in 13/08/2022 Time 09:29:43