Quantitative and Computational Biology

An integrated, mathematically and computationally sophisticated introduction to physics, chemistry, molecular biology, and computer science. Alternative to the combination of PHY 103-104, CHM 201-202, MOL 214 and COS 126. Students must enroll in ISC231 and ISC232 in the fall and ISC233 and ISC234 in the spring. Prerequisites: familiarity with calculus at the level of MAT103/104 or Advanced Placement Calculus BC, solid high school physics and chemistry courses. Five lectures, one three-hour laboratory, one three-hour computational laboratory, one evening problem session.

An integrated, mathematically and computationally sophisticated introduction to physics, chemistry, molecular biology, and computer science. Alternative to the combination of PHY 103-104, CHM 201-202, MOL 214 and COS 126. Students must enroll in ISC 231 and ISC 232 in the fall and ISC 233 and ISC 234 in the spring. Prerequisites: familiarity with the calculus at the level of MAT 103-104 or Advanced Placement Calculus BC, solid high school physics and chemistry courses. Five lectures, one three-hour laboratory, one three-hour computational laboratory, one evening problem session.

An integrated, mathematically and computationally sophisticated introduction to physics and chemistry, drawing on examples from biological systems. Alternative to the combination of PHY 103-104, CHM 201-202, MOL 214, and COS 126. Students must enroll in ISC 231 and ISC 232 in the fall and ISC 233 and ISC 234 in the spring. Prerequisites: familiarity with the calculus at the level of MAT 103-104 or Advanced Placement Calculus BC, solid high school physics and chemistry courses. Five lectures, one three-hour laboratory, one three-hour computational laboratory, one evening problem session.

An integrated, mathematically and computationally sophisticated introduction to physics and chemistry, drawing on examples from biological systems. Alternative to the combination of PHY 103-104, CHM 201-202, MOL 214 and COS 126. Students must enroll in ISC 231 and ISC 232 in the fall and ISC 233 and ISC 234 in the spring. Prerequisites: familiarity with the calculus at the level of MAT 103-104 or Advanced Placement Calculus BC, solid high school physics and chemistry courses. Five lectures, one three-hour laboratory, one three-hour computational laboratory, one evening problem session.

Introduction to computational and genomic approaches used to study molecular systems. Topics include computational approaches to sequence similarity and alignment, phylogenetic inference, gene expression analysis, structure prediction, comparative genome analysis, and high-throughput technologies for mapping genetic networks. Two lectures, one preceptorial.

Analysis of recent work on quantitative, theoretically grounded approaches to the phenomena of life. Topics rotate from year to year, spanning all levels of biological organization, including (as examples) initial events in photosynthesis, early embryonic development, evolution of protein families, coding and computation in the brain, collective behavior in animal groups. Assumes knowledge of relevant physics and applicable mathematics at advanced undergraduate level, with tutorials on more advanced topics. Combination of lectures with student discussion of recent and classic papers.

This course establishes a foundation in applied statistics and data science for those interested in pursuing data-driven research. The course may involve examples from any area of science, but it places a special emphasis on modern biological problems and data sets. Topics may include data wrangling, exploration and visualization, statistical programming, likelihood based inference, Bayesian inference, bootstrap, EM algorithm, regularization, statistical modeling, principal components analysis, multiple hypothesis testing, and causality. The statistical programming language R is extensively used to explore methods and analyze data.

Using a number of real biological systems, course demonstrates how mathematical models of complex natural systems 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. For QCB program students, quantitatively inclined molecular biology students, and physics, chemistry and engineering students interested in quantitative biology. An extension of MOL 510.

This course focuses on computational methods in cryo-EM, including three-dimensional ab-initio modelling, structure refinement, resolving structural variability of heterogeneous populations, particle picking, model validation, and resolution determination. Special emphasis is given to methods that play a significant role in many other data science applications. These comprise of key elements of statistical inference, image processing, and linear and non-linear dimensionality reduction. The software packages RELION and ASPIRE are routinely used for class demonstration on both simulated and publicly available experimental datasets.

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.