Genomic Data Science - 138047
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Lecture |
Exercise |
Laboratory |
Project or Seminar |
House Work |
Weekly Hours |
2 |
2 |
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Determination of the grade according to progress during the semester and the submission of the final thesis
Prerequisites
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(
| | General Genetics |
134020
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and
| Molecular Biology |
134082
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and
| Biostatistics for Biologists |
134154
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and
| Introduction to Bioinformatics |
236523
| ) |
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Identical Courses
| | | | Genomic Data Science |
138046
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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 Machine-
Learning Outcomes
At 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.
TextbooksPublished | Publisher | Authors | Book |
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2021 | chapman and hall/crc | rafael a. irizarry, michael i. love | data analysis for the life sciences |
2020 | online book | | online book computational genomics with r |
Created in 03/02/2023 Time 05:58:07