Computational Medicine
Computational Medicine
02-718: Fall 2021
This is course on the algorithms and computational methods used in modern medicine. The topics to be covered include computational strategies for advancing personalized medicine, pharmacogenomics for predicting individual drug responses, metagenomics for learning the role of the microbiome in human health, mining electronic medical records to identify disease phenotypes, and case studies in complex human diseases such as cancer and asthma. We will discuss how machine learning methodologies such as regression, classification, clustering, semi-supervised learning, probabilistic modeling, and time-series modeling are being used to analyze a variety of datasets collected by clinicians. Class sessions will consist of lectures, discussions of papers from the literature, and guest presentations by clinicians and other domain experts. Grading will be based on homework assignments and a project. This course is self contained. There are no prerequisites.
This is course on the algorithms and computational methods used in modern medicine. The topics to be covered include computational strategies for advancing personalized medicine, pharmacogenomics for predicting individual drug responses, metagenomics for learning the role of the microbiome in human health, mining electronic medical records to identify disease phenotypes, and case studies in complex human diseases such as cancer and asthma. We will discuss how machine learning methodologies such as regression, classification, clustering, semi-supervised learning, probabilistic modeling, and time-series modeling are being used to analyze a variety of datasets collected by clinicians. Class sessions will consist of lectures, discussions of papers from the literature, and guest presentations by clinicians and other domain experts. Grading will be based on homework assignments and a project. This course is self contained. There are no prerequisites.
Previously offered: Spring 2016, Spring 2017, Fall 2018, Fall 2019, Fall 2020
Previously offered: Spring 2016, Spring 2017, Fall 2018, Fall 2019, Fall 2020
See also SARS Wars: A New Hope A free, online course intended to provide basic information on the biology and medicine relevant to SARS-CoV-2/COVID-19
Automation of Scientific Research
Automation of Scientific Research
02-450 and 02-750: Spring 2021:
(formerly called Automation of Biological Research)
Automated science and engineering combines Robotics, Machine Learning, and Artificial Intelligence to accelerate the pace of discovery and rational design. This course introduces students to the Machine Learning and Artificial Intelligence algorithms that enable this emerging paradigm. Emphasis is placed on techniques for sequential analysis (i.e., model discovery and hypothesis generation), design of experiments, and optimization to maximize the return on research capital. Specific approaches will include Active Learning, Reinforcement Learning, and Bayesian Optimization..
Automated science and engineering combines Robotics, Machine Learning, and Artificial Intelligence to accelerate the pace of discovery and rational design. This course introduces students to the Machine Learning and Artificial Intelligence algorithms that enable this emerging paradigm. Emphasis is placed on techniques for sequential analysis (i.e., model discovery and hypothesis generation), design of experiments, and optimization to maximize the return on research capital. Specific approaches will include Active Learning, Reinforcement Learning, and Bayesian Optimization..
Previously offered: Fall 2014, Fall 2015, Fall 2016, Fall 2017, Spring 2018, Spring 2019, Spring 2020
Previously offered: Fall 2014, Fall 2015, Fall 2016, Fall 2017, Spring 2018, Spring 2019, Spring 2020
Cell and Systems Modeling
Cell and Systems Modeling
02-730: Fall 2015:
This is an introductory course in Systems Biology focusing on the development, simulation, and analysis of mechanistic models of biological systems.
This is an introductory course in Systems Biology focusing on the development, simulation, and analysis of mechanistic models of biological systems.
Previously offered: Spring 2011, Spring 2012, Spring 2013, Fall 2013, Fall 2014
Previously offered: Spring 2011, Spring 2012, Spring 2013, Fall 2013, Fall 2014
Algorithms for Computational Structural Biology
Algorithms for Computational Structural Biology
This course is an introductory survey of the algorithmic techniques used in the field of structural biology.
This course is an introductory survey of the algorithmic techniques used in the field of structural biology.
Previously offered: Fall 2004, Spring 2007, Spring 2010
Previously offered: Fall 2004, Spring 2007, Spring 2010
Advanced Algorithms for Computational Structural Biology
Advanced Algorithms for Computational Structural Biology
02-722: Fall 2012 Guest-taught by Prof. Ilyin
This is a seminar-style course on the current literature in computational structural biology.
This is a seminar-style course on the current literature in computational structural biology.
Pre-req: 15-879A, or permission of the instructor
Previously offered: Spring 2005, Fall 2005
Previously offered: Spring 2005, Fall 2005
Computational Biology Journal Club
Computational Biology Journal Club
02-730: Spring 2015:
This is a journal club focusing on the recent literature in Computational Biology
This is a journal club focusing on the recent literature in Computational Biology
Previously offered: Sprint 2014
Previously offered: Sprint 2014
Fundamental Data Structures and Algorithms
Fundamental Data Structures and Algorithms
Previously offered: Fall 2005, Fall 2006, Fall 2007, Fall 2008, Fall 2009, Fall 2010, Fall 2011
Previously offered: Fall 2005, Fall 2006, Fall 2007, Fall 2008, Fall 2009, Fall 2010, Fall 2011
Formal Methods in Systems Biology
Formal Methods in Systems Biology
15-872A:
15-872A:
This is a seminar-style course on the use of formal methods in modeling biological systems. Topics will include applications of model checking, algebraic methods, rule-based modeling, and type theory.
This is a seminar-style course on the use of formal methods in modeling biological systems. Topics will include applications of model checking, algebraic methods, rule-based modeling, and type theory.
Open to graduate students from SCS and MCS and others by permission
Open to graduate students from SCS and MCS and others by permission
Previously offered: Spring 2008
Previously offered: Spring 2008