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Class Schedule Listing

 

Fall 2019
Mar 28, 2024
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Sections Found
Computational Genomics - 22735 - BCHM 49500 - 002  Link Id: A1  Linked Section RequiredLinked Sections Required(A2)

“This course introduces students to the basics of modern genomics and computational tools that will be used for screening. We will review the notion of gene, genome, transcriptome, and epigenome, and show how next generation sequencing technologies are utilized to measure these within cells.”
Associated Term: Fall 2019
Registration Dates: Mar 18, 2019 to Aug 25, 2019
Levels: Graduate, Professional, Undergraduate
Attributes: Upper Division, Variable Title

West Lafayette Campus
Lecture Schedule Type
3.000 Credits
Syllabus Available
View Catalog Entry
Course Materials


Scheduled Meeting Times
Type Time Days Where Date Range Schedule Type Instructors
Class 3:30 pm - 5:20 pm W Lilly Hall of Life Sciences G428 Aug 19, 2019 - Dec 07, 2019 Lecture Majid Kazemian (P)E-mail


Computational Genomics - 22736 - BCHM 49500 - 003  Link Id: A2  Linked Section RequiredLinked Sections Required(A1)

“This course introduces students to the basics of modern genomics and computational tools that will be used for screening. We will review the notion of gene, genome, transcriptome, and epigenome, and show how next generation sequencing technologies are utilized to measure these within cells.”
Associated Term: Fall 2019
Registration Dates: Mar 18, 2019 to Aug 25, 2019
Levels: Graduate, Professional, Undergraduate
Attributes: Upper Division, Variable Title

West Lafayette Campus
Laboratory Schedule Type
0.000 Credits
View Catalog Entry
Course Materials


Scheduled Meeting Times
Type Time Days Where Date Range Schedule Type Instructors
Class 3:30 pm - 5:20 pm F Lilly Hall of Life Sciences G428 Aug 19, 2019 - Dec 07, 2019 Laboratory Majid Kazemian (P)E-mail


R For Molecular Biosciences - 12883 - BCHM 49500 - 004  Link Id: A3  Linked Section RequiredLinked Sections Required(A4)

Students will learn R to acquire, clean, explore and analyze biological data sets. Lectures and example data sets will show how data are linked to biological phenomena through human observation or instrumentation with inherent limitations. Students will learn how to organize data sets to optimize clarity and analytic possibilities while minimizing errors with examples drawn from the literature or biological databases. R programming will be taught starting with small-scale data such as drug sensitivity assays, qPCR, and metabolomics, moving to genome-scale analyses such as gene expression and pathway analysis later in the course. These skills will be taught in the light of enabling reproducible research through clear documentation of data sets and analyses. Relevant concepts from statistics will be reviewed, but it is assumed that students are familiar with basic statistical analyses.”
Associated Term: Fall 2019
Registration Dates: Mar 18, 2019 to Aug 25, 2019
Levels: Graduate, Professional, Undergraduate
Attributes: Upper Division, Variable Title

West Lafayette Campus
Lecture Schedule Type
3.000 Credits
View Catalog Entry
Course Materials


Scheduled Meeting Times
Type Time Days Where Date Range Schedule Type Instructors
Class 1:30 pm - 3:20 pm W Stanley Coulter Hall 179 Aug 19, 2019 - Dec 07, 2019 Lecture Pete E Pascuzzi (P)E-mail


R For Molecular Biosciences - 12894 - BCHM 49500 - 005  Link Id: A4  Linked Section RequiredLinked Sections Required(A3)

Students will learn R to acquire, clean, explore and analyze biological data sets. Lectures and example data sets will show how data are linked to biological phenomena through human observation or instrumentation with inherent limitations. Students will learn how to organize data sets to optimize clarity and analytic possibilities while minimizing errors with examples drawn from the literature or biological databases. R programming will be taught starting with small-scale data such as drug sensitivity assays, qPCR, and metabolomics, moving to genome-scale analyses such as gene expression and pathway analysis later in the course. These skills will be taught in the light of enabling reproducible research through clear documentation of data sets and analyses. Relevant concepts from statistics will be reviewed, but it is assumed that students are familiar with basic statistical analyses.”
Associated Term: Fall 2019
Registration Dates: Mar 18, 2019 to Aug 25, 2019
Levels: Graduate, Professional, Undergraduate
Attributes: Upper Division, Variable Title

West Lafayette Campus
Laboratory Schedule Type
0.000 Credits
View Catalog Entry
Course Materials


Scheduled Meeting Times
Type Time Days Where Date Range Schedule Type Instructors
Class 1:30 pm - 3:20 pm F Stanley Coulter Hall 179 Aug 19, 2019 - Dec 07, 2019 Laboratory Pete E Pascuzzi (P)E-mail



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