Quantitative and Computational Biology Jump To: Jump To: Program Offerings Certificate Offering type Certificate The Program in Quantitative and Computational Biology is offered by the Lewis-Sigler Institute for Integrative Genomics and its affiliated departments. The program is designed to instruct students in the theory and practice of using big data sets to achieve a quantitative understanding of complex biological processes. Examples of ongoing research include organizational principles of metabolic networks, quantitative modeling of cell biological processes, the genetic basis of complex behavior, comparative genomics of regulatory networks, quantitative analysis of gene-environment interactions, evolution of gene regulation and circuitry driving aging. At the core of the curriculum is independent research initiated in the fall of sophomore or junior year, in which students participate in the design, execution and analysis of experiments in a host laboratory of their choice. The required courses provide a strong background in modern methodologies in data analysis, interpretation and modeling. A certificate in quantitative and computational biology is awarded to students who successfully complete the program requirements. Goals for Student Learning The Lewis-Sigler Institute for Integrative Genomics (LSI) awards the certificate in Quantitative and Computational Biology to undergraduate students who satisfactorily complete a multidisciplinary curriculum and relevant independent work. Through its prerequisite courses, students learn fundamental principles in the natural sciences and tools of computer science, mathematics and statistics, with a strong emphasis on creative application of many of those basic concepts to novel questions in the life sciences. Intermediate-level electives taught by LSI faculty introduce students to theories and practices that use big data sets to quantitatively understand complex biological processes. Students are encouraged to dive into interdisciplinary literature on genomics and systems biology, and to engage with expertise and ideas from a variety of backgrounds in order to hone their research questions. At the core of the curriculum is independent research initiated in the fall of sophomore or junior year, in which students participate in the design, execution and analysis of experiments in a host laboratory of their choice. High-level electives expose students to an even greater range of contemporary methodologies in data analysis, interpretation and modeling across biophysics, molecular biology and biochemistry. Successful completion of the certificate requirements prepares students well for careers in industries related to the life sciences and propels curious minds into relevant academic fields. Prerequisites Integrated science or three foundational classes from the lists below.ISC 231-234 An Integrated, Quantitative Introduction to Life Sciences (counts as three foundational classes)Or the following: Foundation in Computer Science. The following course or approved equivalent:COS 126/EGR 126 Computer Science: An Interdisciplinary ApproachFoundation in Biology. One of the following courses or approved equivalent:MOL 214/EEB 214/CBE 214 Introduction to Cellular and Molecular BiologyEEB 211 Life on Earth: Mechanisms of Change in NatureFoundation in Math or Statistics. One of the following courses or approved equivalent:200-level math course (or higher)ORF 245/EGR 245 Fundamentals of Statistics Admission to the Program Students are admitted to the program after they have chosen a major, joined a research lab and identified a project (with the help of the program committee as needed) and submitted a complete application by September 1 of their junior year. Although students are encouraged to find a lab on their own, the program committee will, if necessary, assist students in selecting a laboratory for their junior independent and senior thesis work. Students must have identified a lab and research project by the first day of their junior year fall semester. Admission requires the completion of prerequisites listed above. Program electives are chosen in consultation with the adviser. Program of Study From the two lists of approved electives below, students must complete at least one from each list. Students may be permitted to take a graduate-level course not listed below to fulfill the elective requirement, but only with permission of the program director. Computational Methods and Quantitative ModelingCOS 343 Algorithms for Computational BiologyCOS 557 Analysis & Visualization of Large-Scale Genomic Data SetsEEB 325 Mathematical Modeling in Biology and MedicineENV 302/CEE 302/EEB 302 Practical Models for Environmental SystemsMAT 321/APC 321 Numerical MethodsMOL 485/QCB 485 Mathematical Models in BiologyNEU 314 Mathematical Tools for NeuroscienceNEU 437/MOL 437/PSY 437 Computational NeuroscienceNEU 499/PSY 499 The Computational Basis of Natural Intelligence in the Human BrainORF 350 Analysis of Big DataQCB 505/PHY 555 Topics in Biophysics and Quantitative Biology: Statistical Mechanics for Biological NetworksCBE 422 Molecular Modeling MethodsGenomics, Chemical, and Systems BiologyCBE 433/MSE 424 Introduction to the Mechanics and Dynamics of Soft Living MatterCHM 301 Organic Chemistry I: Biological EmphasisCHM 302 Organic Chemistry II: Biological EmphasisCHM 337 Organic Chemistry: Bioengineering EmphasisCHM 541/QCB 541 Chemical Biology IIEEB 309 Evolutionary BiologyEEB 324 Theoretical EcologyEEB 388 Genomics in the Wild (Note: This course is offered as part of the semester abroad program in Kenya)MAE 344/MSE 364 Biomechanics and Biomaterials: From Cells to OrganismsMOL 415 Modern Biophysics and Systems BiologyNEU 427 Systems NeuroscienceQCB 302 Research Topics and Analytical Approaches in Quantitative Biology (recommended)QCB 408 Foundations of Statistical GenomicsQCB 455/MOL455/COS 551 Introduction to Genomics and Computational Molecular BiologyQCB 490/MOL 490 Molecular Mechanisms of Longevity: The Genetics, Genomics, and Cell Biology of AgingQCB 515/PHY 570/EEB 517/CHM 517/MOL 515 Method and Logic in Quantitative Biology Independent Work Junior and Senior Independent Work: Junior and senior independent work must show adequate quantitative and computational biology content and expand upon the existing field. Certificate of Proficiency Students who fulfill the requirements of the program receive a certificate of proficiency in quantitative and computational biology upon graduation. Additional Information Applications for program admission must be submitted by September 1 of junior year and should include the following information: prerequisite courses, plans for courses in the junior and senior years, and independent work plans. Program courses cannot be taken pass/D/fail.At least two classes taken to meet the requirements of the certificate must not count toward the student’s major requirements.Students who pursue a certificate in quantitative and computational biology may not also receive a certificate in biophysics. Faculty Director of Undergraduate Program Brittany Adamson Executive Committee Brittany Adamson, Molecular Biology Thomas Gregor, Physics Coleen T. Murphy, Molecular Biology Joshua D. Rabinowitz, Chemistry Joshua W. Shaevitz, Physics Olga G. Troyanskaya, Computer Science For a full list of faculty members and fellows please visit the department or program website. Courses ISC 231 - An Integrated, Quantitative Introduction to Life Sciences I (also CHM 231/MOL 231/PHY 231) Fall QCR or SEL The four-course sequence ISC 231-234 integrates introductory topics in calculus-based physics, chemistry, molecular biology, and scientific computing with Python, with an emphasis on laboratory experimentation, quantitative reasoning, and data-oriented thinking. It best suits students interested in complex problems in living organisms and prepares them for interdisciplinary research in the life sciences. The fall courses ISC 231 and 232 must be taken together. See ISC website for details on course equivalencies and recommended academic paths from ISC. M. Wühr, T. Gregor, B. Zhang ISC 232 - An Integrated, Quantitative Introduction to Life Sciences I (also CHM 232/MOL 232/PHY 232) Fall QCR or SEL The four-course sequence ISC 231-234 integrates introductory topics in calculus-based physics, chemistry, molecular biology, and scientific computing with Python, with an emphasis on laboratory experimentation, quantitative reasoning, and data-oriented thinking. It best suits students interested in complex problems in living organisms and prepares them for interdisciplinary research in the life sciences. The fall courses ISC 231 and 232 must be taken together. See ISC website for details on course equivalencies and recommended academic paths from ISC. B. Adamson, M. Skinnider, J. Gadd-Reum QCB 455 - Introduction to Genomics and Computational Molecular Biology (also COS 455/MOL 455) Fall QCR 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 testing correction, performance evaluation), and machine learning methods which have been applied to biological problems (e.g., classification techniques, hidden Markov models, clustering). J. Akey, M. Singh