Biomedical Informatics 217: Translational Bioinformatics

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• Problem Set 4 Histogram (2011/06/09 17:55)

  Problem Set 4 Histogram

  
• pset3 histogram (2011/06/09 17:54)

  Problem Set 3 Histogram

  
• Updated the wiki (2011/06/06 07:21)

  I have updated the wiki page on the Final Project to match the email we sent out last week. -- Atul

  
• BMI 217 Final Exam (2011/05/09 09:32)

  Just a note that the BMI 217 Final Exam only covers material from after the Midterm, specifically starting with Hunter Fraser’s lecture on May 2. -- Atul

   

  
• Histogram for Pset 2 (2011/05/06 09:19)

  Histogram for Problem Set 2 is here.
  Median: 100   Mean: 98.37   Std. Dev: 8.78

  
• Histogram for Midterm (2011/05/06 09:18)

  The midterm histogram can be found here.
  Median: 87.5   Mean: 84.95   Std. Dev: 10.93

  
• Group information for project report discussion (2011/05/05 13:02)

  We have split the class into three discussion groups, trying to match areas of interest, details can be found here. Each discussion will be lead by a TA and will consist of a student's presentation of his project to the rest of the group (5 mins) and questions and suggestions (5 mins). The discussions will take place on Friday May 5th, on 3:15pm (should last about 2 hours, let us know if you have to leave early), on the classrooms detailed in the link above.

  SCPD students will be contacted by the TA to schedule a conference call if possible.

  Let us know if we somehow missed putting you in a group.

  
• Pharmacogenomics talk resources (2011/05/04 17:31)

  The talk given by Russ Altman on Pharmacogenomics and its companion papers can be found <a href="http://stanford.edu/~tsuname/Pharmacogenomics_talk.zip">here</a>.

  
• BMI 217 Guest lectures today and Wednesday (2011/05/02 11:15)

  Today’s BMI 217 lecture will be presented by guest lecturer Hunter Fraser on GWAS and disease biology.  What can we actually do with all the hits we get from GWAS studies?  Lecture will be in LKSC 120, as usual for Mondays.

                                                                                                                                                                                                                            

  Wednesday’s BMI 217 lecture will be presented by guest lecturer Russ Altman on pharmacogenomics.  How can we find genes and gene variants associated with drug response and side effects?  Lecture will be in LKSC 102, as usual for Wednesdays.

   

  -- Atul

   

  
• PS4 has been posted (2011/04/27 13:29)

  Problem set 4 is now online.

  

Final project presentations will be held in LKSC102 on Wednesday, June 8, from 12:15-3:15pm.

Slides for the Genetic Regulation lecture by David Ruau on Monday, April 18th. lec6_genetic_regulation.pdf

Preliminary Syllabus

Current Schedule

Online lectures; SCPD students, please use this link instead.

It is the responsibility of those of us involved in today's biomedical research enterprise to translate the remarkable scientific innovations we are witnessing into health gains for the nation… At no other time has the need for a robust, bidirectional information flow between basic and translational scientists been so necessary.

– Elias A. Zerhouni, M.D.,
Director, National Institutes of Health
New England Journal of Medicine, 353:1621, 2005

Translational Bioinformatics is the development of analytic, storage, and interpretive methods to optimize the transformation of increasingly voluminous genetic, genomic, and biological data into diagnostics and therapeutics for medicine.

Topics covered in this course:

• Access and utility of publicly available data sources
• Types of genome-scale measurements in molecular biology and genomic medicine
• Analysis of microarray data
• Analysis of polymorphisms, proteomics, and protein interactions
• Linking genome-scale data to clinical data and phenotypes
• New questions in biomedicine using bioinformatics. Case studies.

Also known as: Computer Science 275

Time: Spring Quarter 2010-2011, Monday and Wednesday 3:15-4:30 pm

First class: Monday, March 28, 2011

Location: Stanford Medical School, Wednesdays will be in LK102, Mondays will be in LK120 (NOTE - the room has changed from LKSK 308!).

Prerequisites: Programming ability at the level of cs106A and familiarity with statistics and biology, or approval of the instructor.

Grading: Grading will be based on four problem sets, midterm exam, final exam, and a final project.

Instructor: Atul Butte, MD, PhD, Assistant Professor of Medicine (Medical Informatics) and Pediatrics abutte@stanford.edu, and two time winner of the American Association for Clinical Chemistry Outstanding Speaker Award. Profile Lab

Teaching Assistants: Kenneth Jung kjung@stanford.edu, Pablo G. Cordero tsuname@stanford.edu, Erik Corona ecoronap@stanford.edu

Contact: Most questions should be posted to the piazzza group page, so that all students can benefit from the answers. Professor Butte or the TAs will respond as soon as possible. For private matters, you can contact us at biomedin217-spr1011-staff@lists.stanford.edu

Office Hours:

• Erik Corona: Friday, 2:00 PM - 3:00 PM. MSOB First Floor. Start from Professor Butte's office (X-163), go down the hall past Rong Chen's office.
• Pablo Cordero: Monday, 4:40 PM - 5:40 PM. MSOB Second Floor lounge. (time and location may change depending on attendance)
• Kenneth Jung: Tuesday, 11:00 AM - 12:00 PM. MSOB Second Floor, cube X2C19A. (time and location may change depending on attendance)
• Professor Butte: By appointment, email Susan Aptekar saptekar@stanford.edu to set up a meeting time. MSOB X-163

• Directions to MSOB

This course is designed for:

• Graduate students in biomedical informatics, genetics, computer science, or other related disciplines
• Medical students
• Medical, pediatric, surgical or other fellows with an interest in learning and using bioinformatics in research
• Interested undergraduates
• Auditors welcome including medical staff, medical/pediatric/surgical fellows, post-doctoral fellows, and undergraduates. Please contact us to be added to the class email list.

The posters around campus

Required books: None (the course will be taught using recent publications)

Recommended books:

• Genomic and Personalized Medicine, Vol 1-2. Ed. Huntington Willard and Geoffrey Ginsburg. 2008. These two books cover a comprehensive look at “advances in the diagnosis, prevention and treatment of human disease.”
• Peter Dalgaard. Introductory Statistics with R. 2002. This short book serves as a handbook and tutorial for learning the free statistical system R, used in this course. This book is not specific for biological data analysis. Link E-books at Lane
• Robert Gentleman, Vince Carey, Wolfgang Huber, Rafael Irizarry, Sandrine Dudoit. Bioinformatics and Computational Biology Solutions Using R and Bioconductor. 2005. This large book serves as a comprehensive book on using the Bioconductor libraries in R for biomedical data analysis. Link E-books at Lane
• Terry Brown. Genomes 3. 2006. A great non-overwhelming reference on molecular biology, with specific focus on novel genome-era measurement tools, such as microarrays. A previous edition of this text is available free at NCBI.]] E-books at Lane

Students should use the piazzza group page. To access it, please first subscribe to the bmi217 class in piazzza. After that this link will direct you to the group. Use it for discussion and posting questions/answers related to the course and problem sets.

Readings are linked from each lecture on the schedule page. Expect two to three readings per class as preparation.

Four problem sets: hands-on analysis of data, which start with reproducing the findings in one or two publications given their raw data, then adding a twist.

Problem set coding language policy: You must use R and/or MySQL for the problem sets.

Problem set collaboration policy: You can talk with others in the class about this problem set but you must turn in your own individual work.

Problem set due dates: Problem sets are due at or before NOON on the due date. You are allotted 4 free late days total this quarter, so use them wisely for the four problem sets. After that, 20% off your grade per day late. Not using all your late days may influence your final grade (bump up) if borderline.

In the second half of the quarter, the students will research, design, and implement a project of similar scope to one of the problem sets. Final presentations will be held on Wed, June 8 from 12:15 to 3:15 pm, LKSC102.

Final project details

• Problem Set 1: Integrative genomics, part 1: Genome wide association studies
• Problem Set 2: Integrative genomics, part 2: Gene Expression, variants, and functional annotation
• Problem Set 3: Integrative clinomics: Integrating molecular measurements with clinical data.
• Problem Set 4: Whole genome sequencing.

Based on the lectures and the readings. Open book. To be held during class, Wednesday, April 27th.

Based on all the lectures and the readings. Open book. To be held during the last class, Wednesday, June 1st.

Midterms and finals may be graded on a curve. Final grades will be calculated: