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<center>'''BIOL47120 Biomedical Genomics II'''</center>
<center>Spring 2019</center>
<center>'''Instructor:''' Weigang Qiu, Ph.D.<br>Professor, Department of Biological Sciences, City University of New York, Hunter College & Graduate Center<br>Adjunct Faculty, Department of Physiology and Biophysics,
Institute for Computational Biomedicine, Weil Cornell Medical College</center>
<center>'''Office:''' B402 Belfer Research Building, 413 East 69th Street, New York, NY 10021, USA</center>
<center>'''Email:''' weigang@genectr.hunter.cuny.edu</center>
<center>'''Lab Website:''' http://diverge.hunter.cuny.edu/labwiki/</center>

==Course Overview==
Welcome to Introductory BioMedical Genomics, a seminar course for advanced undergraduates and graduate students. A genome is the total genetic content of an organism. Driven by breakthroughs such as the decoding of the first human genome and rapid DNA and RNA-sequencing  technologies, biomedical sciences are undergoing a rapid & irreversible transformation into a highly data-intensive field, that requires familiarity  with concepts in both biology, computational, and data sciences.  

Genome information is revolutionizing virtually all aspects of life sciences including basic research, medicine, and agriculture. Meanwhile, use of genomic data requires life scientists to be familiar with concepts and skills in biology, computer science, as well as data analysis. 

This workshop is designed to introduce computational analysis of genomic data through hands-on computational exercises, using published studies.

The pre-requisites of the course are college-level courses in molecular biology, cell biology, and genetics. Introductory courses in computer programming and statistics are preferred but not strictly required.

==Learning goals==
By the end of this course successful students will be able to: 
* Describe next-generation sequencing  (NGS) technologies & contrast it with traditional Sanger sequencing
* Explain applications of NGS technology including pathogen genomics, cancer genomics, human genomic variation, transcriptomics, meta-genomics, epi-genomics, and microbiome.
* Visualize and explore genomics data using RStudio
* Replicate key results using a raw data set produced by a primary research paper

==Web Links==
* Install R base: https://cloud.r-project.org
* Install R Studio (Desktop version): http://www.rstudio.com/download
* Download: [http://www.r4all.org/books/datasets R datasets]
* A reference book: [https://r4ds.had.co.nz/ R for Data Science (Wickharm & Grolemund)]

==Quizzes and Exams==
Student performance will be evaluated by attendance, three (4) quizzes and a final report:
* Attendance & In-class participation: 50 pts
* Assignments: 5 x 10 = 50 pts 
* Quizzes: 2 x 25 pts = 50 pts
* Mid-term: 50 pts
* Final presentation & report: 100 pts
Total: 300 pts

==Course Schedule==