Graduate Studies
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Courses Electives

CHM 542: Principles of Macromolecular Structure

Principles of Macromolecular Structure: Protein Folding, Structure and Design

Michael H. Hecht

This course will be taught from the scientific literature. We will begin the semester with several classic papers on protein folding. As the semester progresses, we will read about protein structure, stability, and folding pathways. The latter part of the semester will focus on recent papers describing new research aimed toward the construction of novel proteins from "scratch." These papers will cover topics ranging from evolution in vitro to computational and rational design. The course will end by discussing the possibility of creating artificial proteomes in the laboratory, and further steps toward synthetic biology.


 

COS 557/MOL 557 - Analysis and Visualization of Large-Scale Genomic Data Sets

Faculty

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Introduces students to computational issues involved in analysis and display of large-scale biological data sets. Algorithms covered will include clustering and machine learning techniques for gene expression and proteomics data analysis, biological networks, joint learning from multiple data sources, and visualization issues for large-scale biological data sets. No prior knowledge of biology or bioinformatics is required; and introduction to bioinformatics and the nature of biological data will be provided. In depth knowledge of computer science is not required, but students should have some understanding of programming and computation.

CHM541/QCB541 Chemical Biology II

Faculty Muir | Rabinowitz

A chemically and quantitatively rigorous treatment of metabolism and protein synthesis, with a focus on modern advances and techniques. Topics include metabolic pathways and their regulation; metabolite and flux measurement; mathematical modeling of metabolism; amino acid, peptide and protein chemistry; protein engineering and selected applications thereof.

QCB511/CBE511 Modeling Tools for Cell and Developmental Biology

Faculty Shvartsman

Mathematical models of complex natural phenomena can organize large amounts of data, provide access to properties that are difficult or impossible to measure experimentally, and suggest new experimental tests of proposed regulatory mechanisms. Participants will demonstrate these ideas in the context of cell and developmental biology. Using a number of well-established experimental systems, such as dynamic instability of microtubules and circadian clocks, course introduces stochastic and deterministic models of reaction and diffusion processes and computational methods for their analysis.

CBE538/MOL538 Biomolecular Engineering

Faculty Link

A study of the design and engineering of biomacromolecules. After a brief review of protein and nucleic acid chemistry and structure, course will delve into rational, evolutionary, and computational methods for the design of these molecules. Specific topics to be covered include aptamers, protein and RNA-based switches and sensors, unnatural amino acids and nucleotides, enzyme engineering, and the integration of these parts via synthetic biology efforts.

MOL 523 Molecular Basis of Cancer

The course is designed to explore the molecular events that contribute to the onset and progression of human cancer.

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Lewis Thomas Laboratory at Princeton University

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