/SIRE503_2018

SIRE503 Course

Course Syllabus

SIRE 503 MEDICAL BIOINFORMATICS Academic Year 2018

MASTER OF SCIENCE PROGRAM IN MEDICAL BIOINFORMATICS (INTERNATIONAL PROGRAM), FACULTY OF MEDICINE SIRIRAJ HOSPITAL

Date: September 18 – December 4, 2018

Date Time Room Topic Lecturer
T Sep 18 9 - 12 SIMR301 Overview of the course & Introduction to Medical Bioinformatics & the Central Dogma slides Bhoom Suktitipat
13 - 16 SIMR301 The RNA World & Systems Biology slides Varodom Charoensawan
T Sep 25 9 - 12 SIMR301 Proteomics & Application of Mass Spectrometry slides Kessiri Kongmanas
13 - 16 SIMR301 Molecular Biology Techniques & Bioinformatics Data slides Wanna Thongnoppakhun
T Oct 2 9 - 12 SIMR301 BLAST, Primer3, and Sequence Alignment slides Prapat Suriyaphol
13 - 16 SIMR301 Next-generation sequencing technologies slides Bhoom Suktitipat
T Oct 9 9 - 12 SIMR301 Metabolomics & its application slides Sakda Khumroong
13 - 16 SIMR301 Genome assembly & Reference Mapping slides Harald Grove
T Oct 16 9 - 12 SIMR301 Variant Calling & Annotation slides Harald Grove
T Oct 30 9 - 12 SIMR301 Overview of Machine Learning slides Bhoom Suktitipat
13 - 16 SIMR301 Data mining & Text mining slides Apirak Hoonlor
T Nov 6 9 - 12 SIMR301 Applying genomic data into a real clinical practice: A dawn of the 'real' precision medicine slides Vip Viprakasit
13 - 16 SIMR301 Genetic Risk Profile slides Bhoom Suktitipat
T Nov 13 9 - 12 SIMR301 Molecular Evolution I slides Pravech Ajawatanawong
13 - 16 SIMR301 Molecular Evolution II slides Pravech Ajawatanawong
T Dec 4 9 - 12 SIMR301 Final Exam Faculty

 

Scoring:

  • Attendance: 10%

  • Homework: 40%

    • Blast/Primer3

    • Genome assembly

    • Variant calling & annotation

  • Term Paper: 30%

  • Final Exam: 20%

Grading:

  • A > 90%

  • B+ [80-90)

  • B [70-80)

  • C < 70%

Term paper

Pick an original article from this list that is related to bioinformatics data analysis. Focus more on articles that use high-throughput data in their research, either genomics, transcriptomics, proteomics, metabolomics, or other big data related to biological questions and experiments. Stay away from papers that focus mainly on classical epidemiology, conventional risk factors, or biostatistics, that do not have much utilization of biological data.

  1. Science

  2. Nature

  3. Nature Genetics

  4. Nature Medicine

  5. Nature Cell Biology

  6. New England Journal of Medicine

  7. British Medical Journal (BMJ)

  8. American Journal of Human Genetics

  9. Cell

  10. PNAS

  11. PLOS Genetics

  12. PLOS Medicine

  13. Genome Research

  14. Genome Biology

  15. Human Mutation

  16. Human Molecular Genetics

* Other ground breaking publications not on this list. Please discuss with the course director. *

 

Answer the following questions (3 sections)

Section 1: What is already known on this topic

In less than three single-sentence bullet points, please summarize the state of scientific knowledge on this topic. Emphasize on “why” this study needed to be done.

Section 2: What this study adds

In one or two single sentence bullet points, give a simple answer to the questions “What do we now know as a result of this study that we did not know before?” “Is there any implications for practice, research, policy, or public health?”

Be brief, succinct, specific, and accurate.

Section 3: How the data were analyzed

Pick 3 figures and describe the followings

  1. What is question that this figure tried to answer?

  2. What data have been generated to answer the question?

  3. What analysis have been done to get to the conclusion?

 

Course coordinator:

Assistant professor Dr. Bhoom Suktitipat, MD, PhD
Graduate Program in Medical Bioinformatics
Department of Biochemistry, Faculty of Medicine Siriraj Hospital &
Integrative Computational BioScience Center, Mahidol University