QCB Graduate Program RequirementsSee QCB Student Handbook for program details. Core courses QCB 515 Method and Logic in Quantitative BiologyQCB 537 (fall term) and QCB 538 (spring term): Current Research Topics in the Quantitative Life SciencesCOS/QCB 551 Introduction to Genomics and Computational Molecular BiologyThree elective courses from the lists below, including at least one from the Quantitative course list and one from the Biological course listTrainings: QCB 501 Topics in Ethics in Science, our Responsible Conduct of Research (RCR) courseMOL 550 The Graduate PrimerParticipation in our Graduate ColloquiumResearch rotations in your first year (three required)General exam (taken in January of your second year)Teaching (usually completed in fourth year of study)Annual thesis committee meetingsDissertation defenseThe course of study for each student must be approved by the Director of Graduate Studies in the beginning of their first year, and course substitutions are possible with the permission of the DGS. Core Courses QCB 515: Method and Logic in Quantitative Biology Close reading of published papers illustrating the principles, achievements, and difficulties that lie at the interface of theory and experiment in biology. Two important papers, read in advance by all students, will be considered each week; the emphasis will be on discussion with students as opposed to formal lectures. Topics include: cooperativity, robust adaptation, kinetic proofreading, sequence analysis, clustering, phylogenetics, analysis of fluctuations, and maximum likelihood methods. A general tutorial on Matlab and specific tutorials for the four homework assignments will be available. COS/QCB 551: Introduction to Genomics and Computational Molecular Biology This interdisciplinary course provides a broad overview of computational and experimental approaches to decipher genomes and characterize molecular systems. We focus on methods for analyzing "omics" data, such as genome and protein sequences, gene expression, proteomics and molecular interaction networks. We cover algorithms used in computational biology, key statistical concepts (e.g., basic probability distributions, significance testing, multiple hypothesis correction, data evaluation), and machine learning methods which have been applied to biological problems (e.g., hidden Markov models, clustering, classification techniques). QCB 537/538 Current Research Topics in the Quantitative Life SciencesMandatory first-year graduate course centered around the weekly QCB seminar series, intended to help develop competency in critical reading and assessment of academic literature across subfields early in graduate training. Class meetings comprise student-driven presentations and discussions surveying research topics relevant to upcoming talks, with an emphasis on latest methodologies and debates. Assessment includes seminar and class attendance, in-class and in-seminar participation, and peer evaluation. Participation in our LSI Graduate Colloquium LSI Graduate Colloquium QCB students are required to attend the LSI Graduate Colloquium during the fall and spring terms, usually held on Thursday afternoons. Second year students will give research talks in the fall term and fourth year students will present their work in the spring term. The series will end with first-year students giving short presentations on the work they have done in one of their rotations. Responsible Conduct of Research QCB 501: Topics in Ethics in Science Discussion and evaluation of the role professional researchers play in dealing with the reporting of research, responsible authorship, human and animal studies, misconduct and fraud in science, intellectual property, and professional conduct in scientific relationships. Participants are expected to read the materials and cases prior to each meeting. Successful completion is based on regular attendance and active participation in discussion. This half-term course is designed to satisfy federal funding agencies' requirements for training in the ethical practice of scientists. Required for graduate students and post-docs. Quantitative Courses (must take at least one)APC 524 /MAE 506/AST 506 Software Engineering for Scientific Computing CBE 517 Soft Matter Mechanics Fundamentals & Applications CHM 503/CBE 524/MSE 514 Introduction to Statistical Mechanics CHM 515 Biophysical Chemistry I CHM 516 Biophysical Chemistry II CHM 542 Principles of Macromolecular Structure: Protein Folding, Structure, and DesignCOS 511 Theoretical Machine LearningCOS 513 Foundations of Probabilistic ModelingCOS 524/COS 424 Fundamentals of Machine LearningCOS 557 Artificial Intelligence for Precision HealthCOS 597D Advanced Topics in Computer Science: Advanced Computational GenomicsCOS 597F Advanced Topics in Computer Sci: Computational Biology of Single CellsCOS 597G Advanced Topics in Computer Science: Understanding Large Language ModelsCOS 597O Advanced Topics in Computer Science: Deep Generative Models: Methods, Applications & Societal Considerations ELE 535 Machine Learning and Pattern Recognition MAE 550/MSE 560 - Lessons from Biology for Engineering Tiny Devices MAE 567/CBE 568 Crowd Control: Understanding and Manipulating Collective Behaviors and Swarm Dynamics MAT 586/APC 511/MOL 511/QCB 513 Computational Methods in Cryo-Electron Microscopy MOL 518 Quantitative Methods in Cell and Molecular Biology MSE 504/CHM 560/PHY 512/CBE 520 Monte Carlo and Molecular Dynamics Simulation in Statistical Physics & Materials Science NEU 437/537 Computational Neuroscience NEU 501 Cellular and Circuits Neuroscience NEU 560 Statistical Modeling and Analysis of Neural Data ORF 524 Statistical Theory and MethodsPHY 561/2 BiophysicsQCB 505/PHY 555 Topics in Biophysics and Quantitative Biology QCB 508 Foundations of Statistical Genomics Biological Courses (must take at least one) CHM 403 Advanced Organic Chemistry CHM/QCB 541 Chemical Biology II EEB 504 Fundamental Concepts in Ecology, Evolution, and Behavior II EEB 522 Colloquium on the Biology of Populations MAE 566 Biomechanics and Biomaterials: From Cells to Organisms MAE 567/CBE 568 Crowd Control: Understanding and Manipulating Collective Behaviors and Swarm Dynamics MOL 504 Cellular Biochemistry MOL 506 Cell Biology and Development MOL 518 Quantitative Methods in Cell and Molecular Biology MOL 521 - Systems Microbiology and Immunology (half-term course) MOL 523 Molecular Basis of Cancer MOL 559 Viruses: Strategy & Tactics QCB 490 Molecular Mechanisms of Longevity QCB 535 Biological networks across scales: Open problems and research methods of systems biology QCB 570 Biochemistry of Physiology and Disease Selected undergraduate courses of interest (note: these do not count towards course requirements) APC 350 Introduction in Differential Equations COS 226 Algorithms and Data Structures COS 343 Algorithms for Computational Biology EEB 324 Theoretical Ecology MOL/QCB 485 Mathematical Models in Biology ORF 309/MAT 380 Probability and Stochastic Systems QCB 302 Research Topics in QCB QCB 311 Genomics Please visit Course Offerings to see the most up-to-date course information.
