Quantitative Biosciences and Engineering
Advising Faculty
Joel Bach, Emeritus Associate Professor of Mechanical Engineering
Parisa Bazazi, Assistant Professor of Petroleum Engineering
Cecilia Diniz Behn, Professor of Applied Mathematics & Statistics
Nanette Boyle, Department Head and Professor of Chemical and Biological Engineering
Kevin Cash, Director of the QBE Graduate Program and Associate Professor of Chemical and Biological Engineering
Anuj Chauhan, Professor of Chemical and Biological Engineering
Dylan Domaille, Associate Professor of Chemistry
Linda Figueroa, Professor of Civil and Environmental Engineering
Christopher Higgins, Professor of Civil and Environmental Engineering
Katie Knaus , Assistant Professor of Mechanical Engineering
Melissa Krebs, Associate Professor of Chemical and Biological Engineering
Ramya Kumar, Assistant Professor of Chemical and Biological Engineering
Terry Lowe, Research Professor of Materials and Metallurgical Engineering
David Marr, Professor of Chemical and Biological Engineering
Junko Munakata Marr, Professor of Civil and Environmental Engineering
Alexander Pak, Assistant Professor, Chemical and Biological Engineering
Steve Pankavich, Department Head and Professor of Applied Mathematics & Statistics
Anthony Petrella, Department Head and Professor of Mechanical Engineering
Yamuna Phal, Assistant Professor of Electrical Engineering
Matthew Posewitz, Professor of Chemistry
James Ranville, Professor of Chemistry
Jonathan Sharp, Associate Department Head and Professor of Civil and Environmental Engineering
Anne Silverman, Professor of Mechanical Engineering
E. Dendy Sloan, Emeritus Professor of Chemical and Biological Engineering
John Spear, Professor, Civil and Environmental Engineering
Jeff Squier, Professor of Physics
Amadeu Sum, Professor of Chemical and Biological Engineering
Brian Trewyn, Department Head and Professor of Chemistry
Shubham Vyas, Professor of Chemistry
Xiaoli Zhang, Professor of Mechanical Engineering
Teaching Faculty
Linda Battalora, Teaching Professor of Petroleum Engineering
Suzannah Beeler, Associate Director of the QBE Undergraduate Program and Teaching Associate Professor of Chemical and Biological Engineering
Christian Beren, Director of the QBE Undergraduate Program and Teaching Associate Professor of Chemistry
Kristine Csavina, Teaching Professor of Mechanical Engineering
Duncan Davis-Hall, Teaching Assistant Professor of Engineering, Design, & Society
Alina Handorean, Teaching Professor of Engineering, Design & Society
Jenny Ketterling, Teaching Associate Professor of Chemical and Biological Engineering
Josh Ramey, Teaching Associate Professor of Chemical and Biological Engineering
Justin Shaffer, Associate Dean of Undergraduate Students and Teaching Professor of Chemical and Biological Engineering
Quantitative Biosciences and Engineering (QBE) Program Requirements
For admission, students may enter with biology or health-related undergraduate degrees or with a technical degree, e.g., in engineering, mathematics, or computer science.
Current Mines undergraduate students have the option to apply to the Office of Graduate Studies for the combined program while pursuing their undergraduate degree (see information below).
Each of the three degrees (non-thesis Master of Science, thesis-based Master of Science, and Doctor of Philosophy) require the successful completion of four core courses for a total of 13 credits, as detailed below.
| QBE Core Courses | ||
| BIOL500 | CELL BIOLOGY AND BIOCHEMISTRY | 4.0 |
| BIOL510 | BIOINFORMATICS | 3.0 |
| BIOL520 | SYSTEMS BIOLOGY | 3.0 |
| CHGN535 | PHYSICAL BIOCHEMISTRY | 3.0 |
| Total Semester Hrs | 13.0 | |
QBE Graduate Seminar
Full-time graduate students in the QBE program are expected to maintain continuous enrollment in BIOL 590, QBE Graduate Seminar, a 1 credit course. A maximum of 2 credits will be granted toward the MS degree requirements while a maximum of 4 credits will be granted toward PhD requirements, as shown below. Students who are concurrently enrolled in a different degree program that also requires seminar attendance may have this requirement waived at the discretion of the QBE Program Director.
Master of Science in Quantitative Biosciences and Engineering (Non-Thesis Option)
The Master of Science Non-Thesis (MS-NT) degree requires a minimum of 30 credits of acceptable coursework.
| QBE Core Courses | 13.0 | |
| QBE Electives (see list below) | 15.0 | |
| BIOL590 | QUANTITATIVE BIOSCIENCES & ENGINEERING GRADUATE SEMINAR (*) | 2.0 |
| Total Semester Hrs | 30.0 | |
*While full-time MS-NT students are expected to maintain continuous enrollment in BIOL 590, the QBE Graduate Seminar; a maximum of 2 credits will be granted toward the MS-NT degree requirements.
Master of Science in Quantitative Biosciences and Engineering (Thesis Option)
The thesis-based Master of Science (MS-T) requires a minimum of 30 semester hours of acceptable coursework and thesis research credits. Students conduct an in-depth research project with one of the participating faculty members who are currently accepting masters degree students. The student must also submit a thesis and pass the thesis defense examination before the thesis committee.
| QBE Core Courses | 13.0 | |
| QBE Elective | 3.0 | |
| BIOL590 | QUANTITATIVE BIOSCIENCES & ENGINEERING GRADUATE SEMINAR (*) | 2.0 |
| BIOL707 | GRADUATE THESIS / DISSERTATION RESEARCH CREDIT | 12.0 |
| Total Semester Hrs | 30.0 | |
*While full-time MS-T students are expected to maintain continuous enrollment in BIOL 590, the QBE Graduate Seminar; a maximum of 2 credits will be granted toward the MS-T degree requirements.
Doctor of Philosophy in Quantitative Biosciences and Engineering
The Doctor of Philosophy (PhD)degree requires a minimum of 72 hours of course and research credit including at least 24 credits in coursework and at least 24 credits in research. Doctoral students must also pass a qualifying examination and thesis-proposal defense, complete a satisfactory thesis, and successfully defend their thesis.
| QBE Core Courses | 13.0 | |
| QBE Electives | 11.0 | |
| BIOL590 | QUANTITATIVE BIOSCIENCES & ENGINEERING GRADUATE SEMINAR (*) | 4.0 |
| BIOL707 | GRADUATE THESIS / DISSERTATION RESEARCH CREDIT | 24.0 |
| QBE Electives or BIOL707 Research | 20.0 | |
| Total Semester Hrs | 72.0 | |
*While full-time PhD students are expected to maintain continuous enrollment in BIOL 590, the QBE Graduate Seminar, a maximum of 4 credits will be granted toward the PhD degree requirements.
QBE Elective Courses:
The current list of available electives is shown below. Because course options are continually expanding, additional complementary courses (beyond those listed here) may be approved on an ad hoc basis by the advisor in consultation with the program director.
| BIOL599 | INDEPENDENT STUDY | 0.5-6 |
| CBEN505 | NUMERICAL METHODS IN CHEMICAL ENGINEERING | 3.0 |
| CBEN511 | NEUROSCIENCE, MEMORY, AND LEARNING | 3.0 |
| CBEN531 | IMMUNOLOGY FOR SCIENTISTS AND ENGINEERS | 3.0 |
| CBEN532 | TRANSPORT PHENOMENA IN BIOLOGICAL SYSTEMS | 3.0 |
| CBEN570 | INTRODUCTION TO MICROFLUIDICS | 3.0 |
| CBEN624 | APPLIED STATISTICAL MECHANICS | 3.0 |
| CBEN625 | MOLECULAR SIMULATION | 3.0 |
| CBEN670 | ADVANCED MICROSCOPY FOR RESEARCH | |
| CEEN501 | LIFE CYCLE ASSESSMENT | 3.0 |
| CEEN550 | PRINCIPLES OF ENVIRONMENTAL CHEMISTRY | 3.0 |
| CEEN551 | ENVIRONMENTAL ORGANIC CHEMISTRY | 3.0 |
| CEEN560 | MOLECULAR MICROBIAL ECOLOGY AND THE ENVIRONMENT | 3.0 |
| CEEN562 | ENVIRONMENTAL GEOMICROBIOLOGY | 3.0 |
| CEEN566 | MICROBIAL PROCESSES, ANALYSIS AND MODELING | 3.0 |
| CEEN570 | WATER AND WASTEWATER TREATMENT | 3.0 |
| CHGN509 | BIOLOGICAL INORGANIC CHEMISTRY | 3.0 |
| CHGN507 | ADVANCED ANALYTICAL CHEMISTRY | 3.0 |
| CSCI562 | APPLIED ALGORITHMS AND DATA STRUCTURES | 3.0 |
| CSCI/DSCI575 | ADVANCED MACHINE LEARNING | 3.0 |
| DSCI503 | ADVANCED DATA SCIENCE | 3.0 |
| DSCI570 | INTRODUCTION TO MACHINE LEARNING | |
| EBGN525 | BUSINESS ANALYTICS | 3.0 |
| EBGN553 | PROJECT MANAGEMENT | 3.0 |
| MATH530 | INTRODUCTION TO STATISTICAL METHODS | 3.0 |
| MATH/DSCI560 | INTRODUCTION TO KEY STATISTICAL LEARNING METHODS I | |
| MATH572 | MATHEMATICAL AND COMPUTATIONAL NEUROSCIENCE | 3.0 |
| MEGN532 | EXPERIMENTAL METHODS IN BIOMECHANICS | 3.0 |
| MEGN535 | MODELING AND SIMULATION OF HUMAN MOVEMENT | 3.0 |
| MEGN536 | COMPUTATIONAL BIOMECHANICS | 3.0 |
| MTGN570 | BIOCOMPATIBILITY OF MATERIALS | 3.0 |
| MTGN572 | BIOMATERIALS | 3.0 |
Mines' Combined Undergraduate / Graduate Degree Program
Students enrolled in Mines’ combined undergraduate/graduate program may double count up to 6 credits of graduate coursework to fulfill requirements of both their undergraduate and graduate degree programs. These courses must have been passed with B- or better, not be substitutes for required coursework, and meet all other university, department, and program requirements for graduate credit.
Students are advised to consult with their undergraduate and graduate advisors for appropriate courses to double count upon admission to the combined program.
BIOL500. CELL BIOLOGY AND BIOCHEMISTRY. 4.0 Semester Hrs.
This graduate-level course offers an in-depth exploration of the biochemical processes governing cellular function, structure, and metabolism. Bridging molecular structure with system-level function, students will examine critical topics including cell components, membrane dynamics, gene expression, signal transduction and metabolic pathways. Through rigorous literature analysis and reviewing biochemistry, cell and molecular biology techniques, this course prepares students for future research careers, exploring complex mechanisms behind apoptosis and cancer biology. The course includes a 3-credit hour lecture section and a 1 credit hour practicum section.
View Course Learning Outcomes
- Relate 3D structure of biological macromolecules to their functional roles in cellular processes.
- Describe the molecular mechanisms governing eukaryotic gene expression, including transcription, RNA processing, and translation.
- Describe major metabolic pathways and how they are regulated under different physiological conditions and in diseases.
- Analyze the mechanisms of intracellular communication and signaling cascades that regulate cell growth, survival, and death.
- Describe the molecular and genetic basis of tumorigenesis, including the role of oncogenes, tumor suppressors, and altered metabolic states in cancer cells.
- Integrate knowledge of molecular mechanisms to understand complex, system-level functions, such as cell-to-cell communication and tissue-level responses.
- Critically analyze and interpret primary literature in biochemistry, cell and molecular biology to evaluate scientific findings.
- Review and explain the theory behind modern research techniques used to study cell components, such as mass spectrometry, imaging, and molecular cloning.
- Develop original research questions and propose appropriate experimental approaches to test them.
- Prepare for future research careers by understanding the methodologies used in current cancer biology and cell biology research.
- Present complex scientific information, techniques, and experimental findings in various formats.
BIOL501. ADVANCED BIOCHEMISTRY. 3.0 Semester Hrs.
Advanced study of the major molecules of biochemistry: amino acids, proteins, enzymes, nucleic acids, lipids, and saccharides- their structure, chemistry, biological function, biosynthesis, and interaction. Stresses bioenergetics and the cell as a biological unit of organization. Advanced discussion of the intertwining of molecular genetics, biomolecule synthesis, and metabolic cycles. Prerequisites: CHGN428 or BIOL500.
View Course Learning Outcomes
- Demonstrate a broad knowledge of the fundamental introductory concepts of Chemistry, Biology and Physics
- Demonstrate a thorough knowledge of the intersection between the disciplines of Biology and Chemistry.
- Locate, critically analyze, interpret and discuss data, hypotheses, results, theories, and explanations found in the primary literature, applying knowledge from Chemistry and Biology.
- Appreciate the way in which practitioners in the disciplines of Biology and Chemistry intersect and bring their expertise to bear in solving complex problems involving living systems.
BIOL510. BIOINFORMATICS. 3.0 Semester Hrs.
Bioinformatics is a blend of multiple areas of study including biology, data science, mathematics and computer science. The field focuses on extracting new information from massive quantities of biological data and requires that scientists know the tools and methods for capturing, processing and analyzing large data sets. Bioinformatics scientists are tasked with performing high-throughput, next-generation sequencing. They analyze DNA sequence alignment to find mutations and anomalies and understand the impact on cellular processes. The bioinformatician uses software to analyze protein structure and its impact on cell function. Learning how to design experiments and perform advanced statistical analysis is essential for anyone interested in this field, which is main goal of this course. Prerequisite: CSCI102.
View Course Learning Outcomes
- 1. knowledge and awareness of the basic principles and concepts of biology, computer science and mathematics;
- 2. existing software effectively to extract information from large databases and to use this information in computer modeling;
- 3. problem-solving skills, including the ability to develop new algorithms and analysis methods;
- 4. an understanding of the intersection of life and information sciences, the core of shared concepts, language and skills;
- 5. the ability to speak the language of structure-function relationships, information theory, gene expression, and database queries.
BIOL520. SYSTEMS BIOLOGY. 3.0 Semester Hrs.
This course provides students an introduction to the emerging field of systems biology. It will consist of lectures, group discussion sessions, and problem-solving sessions and/or computational labs. Students will learn strategies and tools to interrogate biological systems using mathematical modeling. Topics of the course will come from typical aspects of biomathematical modeling including, but not limited to: the choice of a modeling framework from various approaches; the design of interaction diagrams; the identification of variables and processes; the design of systems models; standard methods of parameter estimation; the analysis of steady states, stability, sensitivity; numerical evaluations of transients; phase-plane analysis; simulation of representative biological scenarios. All theoretical concepts are exemplified with applications.
View Course Learning Outcomes
- At the completion of the course, students will be able to:1. Describe and understand important types of quantitative/mathematical models used in the field of systems biology
- 2. Explain the basic strengths and limitations of quantitative/mathematical modeling of biological systems
- 3. Design and implement quantitative/mathematical models of biological systems
- 4. Apply appropriate techniques for steady-state and dynamical analysis of models
- 5. Utilize different modeling tools for the analysis of models and their output
- 6. Assimilate current systems biology literature, extend it in a final project, and communicate results professionally and effectively
BIOL590. QUANTITATIVE BIOSCIENCES & ENGINEERING GRADUATE SEMINAR. 1.0 Semester Hr.
(I,II) The Quantitative Biosciences and Engineering (QBE) Graduate Seminar provides a forum for QBE graduate students to participate in seminars given by QBE professionals, develop an enhanced understanding of the breadth of quantitative bioscience disciplines, and present their research projects. Grade is based on attendance over the semester. Full-time graduate students must enroll in the Graduate Seminar course every semester that they are enrolled at Mines. Repeatable; maximum 2 credits granted towards MS degree requirements and 4 credits maximum granted towards PhD Requirements.
BIOL707. GRADUATE THESIS / DISSERTATION RESEARCH CREDIT. 1-15 Semester Hr.
(I, II, S) Research credit hours required for completion of a Masters-level thesis or Doctoral dissertation. Research must be carried out under the direct supervision of the student's faculty advisor. Variable class and semester hours. Repeatable for credit.
