Courses in Systems Biology and Computational Biology

 

Advanced Statistical and Computational Methods in Genetics and Genomics

Faculty: Iuliana Ionita-Laza
Department: Biostatistics
Description: Design and analysis of high-dimensional genetic studies. Genome-wide linkage and association analyses, next-generation sequencing studies, and network genetics.

 

 

Biological Networks

Faculty: Dana Pe'er
Department: Biological Sciences, Department of Systems Biology
Description: Methods and principles involved in studying the structure and function of molecular networks using genomic and proteomic data.

 

 

Biological Sequence Analysis

Faculty: Richard Friedman
Department: Biomedical Informatics, and Integrated Program in Cellular, Molecular, and Biomedical Studies
Description: A lecture/laboratory course for experimental biologists in running bioinformatics programs

 

 

Biophysical Chemistry

Faculty: Ruben Gonzalez and Ann Mc Dermott
Department: Chemistry
Description: Includes laboratory exercises in molecular computer graphics and in structural biological and chemical informatics.

 

 

Computational Biology: Functional and Integrative Genomics

Faculty: Andrea Califano and colleagues
Department: Biomedical Informatics
Description: An advanced course for students specializing in computational biology and bioinformatics: optimization, comparative genomics and phylogentics, functional genomics (microarray analysis) network reconstruction and data integration

 

 

Computational Genomics

Faculty: Itsik Pe'er
Department: Computer Science
Description: An introduction to the analysis of biological sequences and DNA microarray expression data using techniques from machine learning

 

 

Introduction to Molecular Modeling

Faculty: Richard A. Friesner
Department: Chemistry
Description: Computational modeling in chemistry and biochemistry.

 

 

Computational Systems Biology: Proteins, Networks, Function

Faculty: Dennis Vitkup
Department: Biomedical Informatics and Biochemistry and Molecular Biophysics
Description: Structural and functional proteomics and cellular network biology

 

 

Design Principles for Biological Circuits

Faculty: Guillermo Cecchi and Yuhai Tu
Department: Electrical Engineering
Description: Biological networks from an engineering perspective

 

 

Genomics of Gene Expression

Faculty: Harmen J. Bussemaker
Department: Biological Sciences
Description: Introduction to key technologies for probing the regulatory network of the cell using microarrays and next-generation sequencing. Strategies for interpreting and integrating these data using statistics, biophysics, and genetics. Students will learn the basics of the R language and perform analyses of real regulatory genomics data.

 

 

Introduction to Biophysical Modeling

Faculty: Chris Wiggins
Department: Applied Physics and Applied Mathematics
Description: Modeling of biological systems using physical and informatic methods

 

 

Introduction to Genomic Information Science and Technology

Faculty: Vinay Varadan
Department: Electrical Engineering
Description: An introduction to the bioinformatics for both life scientists and computer scientists/engineers.

 

 

Molecular Biophysics

Faculty: Barry Honig - with Wayne Hendrickson, Arthur Palmer, and Arthur Karlin
Department: Biochemistry and Molecular Biophysics
Description: Methods and principles involved in studying the structure and function of proteins, nucleic acids, membranes and their macromolecular assemblies

 

 

Quantitative and Computational Aspects of Infectious Disease

Faculty: Raul Rabadan
Department: Biomedical Informatics
Description: This course is an overview of different theoretical tools that can be used to elucidate the different aspects of the evolution of infectious diseases, and, in particular, RNA viruses.

 

 

Statistical Issues in Microarray Data

Faculty: Iuliana Ionita-Laza
Department: Biostatistics
Description: Statistics of genome-wide association studies.

 

 

Statistical Methods and Genomics

Faculty: Dana Pe'er
Department: Biological Sciences/C2B2
Description: The statistical foundations of genomics.

 

 

Topics In Computer Science, I (Computational Methods for High Throughput Sequencing)

Faculty: Itsik Pe'er
Department: Computer Science
Description: Computational methods and applications of high-throughput genome sequencing. Students of either computational or biological background would qualify. The class will also include a "blitz"-mode project: instead of the last month of weekly meetings, we'll have 2-3 concentrated days of the entire ~15 class participants working together, on campus, on a big project.

 

Related Courses

 

Brain Circuits and Information

Faculty: Aurel A Lazar
Department: Electrical Engineering
Description: Encoding with Neural Circuits

 

 

Chemical Biology

Faculty: Virginia W Cornish and Brent R Stockwell
Department: Biological Sciences
Description: Approaches for discovering and optimizing chemical tools for measuring and perturbing biological systems. Topics include high-throughput assay development, chemical and genomic screening, protein microarrays, and the druggable genome.

 

 

Chemical Genomics

Faculty: Brent Stockwell
Department: Biological Sciences
Description: Approaches for discovering and optimizing chemical tools for measuring and perturbing biological systems. Topics include high-throughput assay development, chemical and genomic screening, protein microarrays, and the druggable genome.

 

 

Computational Neuroscience I: Circuits in the Brain

Faculty: Aurel A Lazar
Department: Electrical Engineering
Description: The theoretical foundation of computational neuroscience

 

 

Design Principles for Biological Circuits

Faculty: Predrag R Jelenkovic
Department: Electrical Engineering
Description: Biological networks from an engineering perspective

 

 

Genetic Analysis Laboratory

Faculty: David Greenberg
Department: Biostatistics
Description: A laboratory in statistical genetics

 

 

Introduction to Computer Applications in Health Care and Biomedicine

Faculty: David Vawdrey and the faculty of the Department of Biomedical Informatics
Department: Biomedical Informatics
Description: An introduction to the applications of informatic methods in biology, health care, and public health.

 

 

Massively Parallel Neural Computation

Faculty: Aurel A. Lazar
Department: Electrical Engineering
Description: Emulation of mental processes on cluster computers.

 

 

Methods in Biomedical Informatics I: Symbolic Methods

Faculty: Chunhua Weng
Department: Biomedical Informatics
Description: Fundamental symbolic methods for health care and biological research decision support systems. Logic, controlled terminologies, knowledge representation, and natural language processing.

 

 

Methods in Biomedical Informatics II: Computational Methods

Faculty: Noemie Elhadad
Department: Biomedical Informatics
Description: Probabilistic and machine learning methods with application to the analysis of biomedical data

 

 

Methods of Computational Neuroscience

Faculty: Aurel A Lazar
Department: Electrical Engineering
Description: Formal methods in computational neuroscience including methods of signal processing, communications theory, information theory, systems and control, system identification and machine learning.

 

 

Neural Encoding and Computation in Sensory Systems

Faculty: Aurel A. Lazar
Department: Electrical Engineering
Description: Models of neural encoding in sensory systems, including Vision, hearing, and smell. Spike Processing. Memory.

 

 

Neural Modeling and Neuroengineering

Faculty: Paul Sajda
Department: Biomedical Engineering
Description: Mathematical models of spiking neurons, neural dynamics, neural coding, and biologically-based computational learning. Architectures and learning principles underlying both artificial and biological neural networks.

 

 

Proteomics Laboratory

Faculty: Lewis Brown
Department: Biological Sciences
Description: This course deals with the proteome. Emphasis will be on mastery of practical techniques of MALDI-TOF mass spectrometry and database searching for identification of proteins separated by gel electrophoresis.

 

 

Seminar In Systems Biology: Representation and Processing of Olfactory Information

Faculty: Aurel A Lazar
Department: Electrical Engineering
Description: Smell from an engineering perspective

 

 

Statistical Aspects of Human Population Genetics

Faculty: Prakash Gorroochurn
Department: Biostatistics
Description: Statistical population genetics, with a focus on human populations, using John Gillespie's 'Population Genetics: A Concise Guide' (Johns Hopkins: Baltimore)

 

 

Statistical Methods in Genetic Epidemiology Journal Club

Faculty: Susan Hodge and David A. Greenberg
Department: Biostatistics
Description: Discussion of important recent papers in genetic epidemiological statistics

 

 

Theoretical Genetic Modeling

Faculty: Susan E. Hodge
Department: Biostatistics
Description: The theoretical foundations underlying models and techniques used in mathematical genetics and genetic epidemiology, with emphasis on likelihood-based methods and reasoning

 

 

Web enHanced Information Management

Faculty: Gail Kaiser
Department: Computer Science
Description: Evolving Web protocols, formats, computation and interaction models. Novel application domains enabled by the Web. Web-inspired concepts applied to non-Web venues.