Course Director: David Fenyö (David@FenyoLab.org)

Course Overview

This course provides an overview of foundational knowledge and essential methods relevant for all areas of biomedical informatics. Students will explore recurring themes and application domains most frequently used in the field. The course will be technical and rigorous, and it will include a number of computer science topics. The course content has been selected by the curriculum committee, and the topics will change over time. The majority of the coursework will be programming assignments and readings.

Learning objectives

The student will learn and understand the most commonly used methodologies in the field of biomedical informatics.

Course Assessment

• Programming Assignments (40%).
• Discussions (25%)
• Final Project (35%)

• Programming:
  • General - Best Practices for Scientific Computing by Wilson et al.
  • Linux/HPC
  • Git
  • Python - Learning Python 5, Think Python, Python for Data Analysis, SciPy, How to Think Like a Computer Scientist: Learning with Python, Learn Python the Hard Way
  • R - Learning R
  • MATLAB - MATLAB: A Practical Introduction to Programming and Problem Solving 2nd Edition by Stormy Attaway
  • JavaScript, JQuery, D3: Tutorials
  • Databases - Learning SQL, MySQL Reference Manual, MongoDB the Definitive Guide
• Algorithms
• Linear Algebra
• Optimization
• Statistics
• Machine Learning
• Information Retrieval
• Data visualization
• Experimental design
• Signal Processing
• Pathways and Networks
• Modeling and Simulation

In addition to the lectures listed below, the students should also attend the relevant lectures from Introduction to Biostatistics and Bioinformatics Fall 2014 (BMSC-GA 4451)

Lecture 1 Introduction (September 9, 2014 TRB 739 5pm)
Lecturer: Fenyo


Lecture 2 Algorithms (September 16, 2014 TRB 739 5pm)
Lecturer: Peskin & Fenyo
Homework (due date: December 16)

Reading List