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BMEN 6389 Michael Zhang | |||||
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BMEN 6389 Michael Zhang | |||||
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Grades: 249
Median GPA: B+
Mean GPA: 3.276
2
Professor rating
5
Difficulty
1
Ratings given
N/A
Would take again
Computational Biology
BMEN 6389
Erik Jonsson School of Engineering and Computer Science
Machine learning and probabilistic graphical models have become essential tools for analyzing and understanding complex systems biology data in biomedical research. This course introduces fundamental principles and methods behind the most important high throughput data analysis tools. Applications will cover molecular evolutionary models, DNA/protein motif discovery, gene prediction, high-throughput sequencing and microarray data analysis, computational modeling gene expression regulation, and biological pathway and network analysis. 3 credit hours.
Prerequisite: Some background in elementary statistics/probability or introductory bioinformatics, or instructor consent required.
Offering Frequency: Spring
Grades: 7
Median GPA: A
Mean GPA: 3.716
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Grades: 249
Median GPA: B+
Mean GPA: 3.276
2
Professor rating
5
Difficulty
1
Ratings given
N/A
Would take again
Computational Biology
BMEN 6389
Erik Jonsson School of Engineering and Computer Science
Machine learning and probabilistic graphical models have become essential tools for analyzing and understanding complex systems biology data in biomedical research. This course introduces fundamental principles and methods behind the most important high throughput data analysis tools. Applications will cover molecular evolutionary models, DNA/protein motif discovery, gene prediction, high-throughput sequencing and microarray data analysis, computational modeling gene expression regulation, and biological pathway and network analysis. 3 credit hours.
Prerequisite: Some background in elementary statistics/probability or introductory bioinformatics, or instructor consent required.
Offering Frequency: Spring
Grades: 7
Median GPA: A
Mean GPA: 3.716
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