B M I/POP HLTH 451 — INTRODUCTION TO SAS PROGRAMMING FOR POPULATION HEALTH
Use of the SAS programming language for the management and analysis of biomedical data.
B M I/STAT 511 — INTRODUCTION TO BIOSTATISTICAL METHODS FOR PUBLIC HEALTH
Provides breadth in biostatistical methods for public health practitioners. Topics will include research design, data collection methods and database management, statistical computing and programming, descriptive statistics in tables and graphics, introductory statistical methods, and survey sampling. Not open to students who have taken BMI/STAT/B M I 541 or BMI/POP HLTH/B M I 551
B M I/STAT 541 — INTRODUCTION TO BIOSTATISTICS
Course designed for the biomedical researcher. Topics include: descriptive statistics, hypothesis testing, estimation, confidence intervals, t-tests, chi-squared tests, analysis of variance, linear regression, correlation, nonparametric tests, survival analysis and odds ratio. Biomedical applications used for each topic. Students may not enroll if they have completed BMI 511 or BMI 551.
B M I/STAT 542 — INTRODUCTION TO CLINICAL TRIALS I
Intended for biomedical researchers interested in the design and analysis of clinical trials. Topics include definition of hypotheses, measures of effectiveness, sample size, randomization, data collection and monitoring, and issues in statistical analysis. Statistics graduate students should take STAT/B M I 641.
B M I 544 — INTRODUCTION TO CLINICAL TRIALS II
Intended for biomedical researchers, focuses on design, implementation, and conduct of clinical trials. Topics include: regulatory requirements; data collection; data quality and management; budgets; federal, institutional, and sponsor-defined requirements; establishment of research infrastructures; preparation of investigator-INDs; investigator responsibilities.
B M I/STAT 546 — PRACTICUM IN CLINICAL TRIAL DATA ANALYSIS AND INTERPRETATION
Provides practice in analysis and interpretation of existing datasets from national and international clinical trials in a variety of diseases. Students will develop a research question, review clinical protocols, and analyze available data to prepare a report.
B M I/POP HLTH 551 — INTRODUCTION TO BIOSTATISTICS FOR POPULATION HEALTH
Course designed for population health researcher. Topics include descriptive statistics, elementary probability, probability distributions, one- and two-sample normal inference (point estimation, hypothesis testing, confidence intervals), power and sample size calculations, one- and two-sample binomial inference, underlying assumptions and diagnostic work.
B M I/POP HLTH 552 — REGRESSION METHODS FOR POPULATION HEALTH
Introduction to the primary statistical tools used in epidemiology and health services research; multiple linear regression, logistic regression and survival analysis.
B M I/COMP SCI 567 — MEDICAL IMAGE ANALYSIS
Present introductory medical image processing and analysis techniques. Topics include medical imaging formats, segmentation, registration, image quantification, classification. Strongly encourage Matlab experience, such as COMP SCI 310 or 368-Matlab.
B M I/COMP SCI 576 — INTRODUCTION TO BIOINFORMATICS
Algorithms for computational problems in molecular biology. The course will study algorithms for problems such as: genome sequencing and mapping, pairwise and multiple sequence alignment, modeling sequence classes and features, phylogenetic tree construction, and gene-expression data analysis.
B M I/BIOCHEM/BMOLCHEM/MATH 606 — MATHEMATICAL METHODS FOR STRUCTURAL BIOLOGY
Intended to provide a rigorous foundation for mathematical modeling of biological structures. Mathematical techniques include ordinary and partial differential equations, 3D Fourier analysis and optimization. Biological applications include protein folding, molecular dynamics, implicit solvent electrostatics, and molecular interactions.
B M I/BIOCHEM/BMOLCHEM/MATH 609 — MATHEMATICAL METHODS FOR SYSTEMS BIOLOGY
Intended to provide a rigorous foundation for mathematical modeling of biological systems. Mathematical techniques include dynamical systems and differential equations. Applications to biological pathways, including understanding of bistability within chemical reaction systems, are emphasized.
B M I/I SY E/L I S 617 — HEALTH INFORMATION SYSTEMS
Provides grounding in core concepts of health information systems. Major applications include clinical information systems, language and standards, decision support, image technology and digital libraries. Evaluation of IE tools and perspectives designed to improve the quality, efficiency and effectiveness of health information.
B M I/STAT 641 — STATISTICAL METHODS FOR CLINICAL TRIALS
Statistical issues in the design of clinical trials, basic survival analysis, data collection and sequential monitoring. Intended for statistics graduate students; those with medical backgrounds should take STAT/B M I 542.
B M I/STAT 642 — STATISTICAL METHODS FOR EPIDEMIOLOGY
Methods for analysis of case-control, cross sectional, and cohort studies. Covers epidemiologic study design, measures of association, rates, classical contingency table methods, and logistic and Poisson regression.
B M I/POP HLTH 651 — ADVANCED REGRESSION METHODS FOR POPULATION HEALTH
Extension of regression analysis to observational data with unequal variance, unequal sampling and propensity weights, clusters and longitudinal measurements, using different variance structures, mixed linear models, generalized linear models and GEE. Matrix notation will be introduced and underlying mathematical and statistical principles will be explained. Examples use data sets from ongoing population health research.
B M I/POP HLTH 652 — TOPICS IN BIOSTATISTICS FOR EPIDEMIOLOGY
Each module will adopt an in-depth focus on a biostatistical method of particular relevance to epidemiology such as measurement error, missing data, intermediate variables, complex study designs, meta-analysis, splines, propensity scores, causal inference, spatial statistics and resampling. One or more modules will be offered every spring semester.
B M I 699 — INDEPENDENT STUDY
Directed study to pursue knowledge beyond curriculum.
B M I/STAT 741 — SURVIVAL ANALYSIS THEORY AND METHODS
Theory and practice of analytic methods for censored survival data, including nonparametric and parametric methods, the proportional hazards regression model, and a review of current topics in survival analysis.
B M I/COMP SCI 767 — COMPUTATIONAL METHODS FOR MEDICAL IMAGE ANALYSIS
Study of computational techniques that facilitate automated analysis, manipulation, denoising, and improvement of large-scale and high resolution medical images. Design and implementation of methods from computer Vision and Machine Learning to efficiently process such image data to answer biologically and clinically meaningful scientific questions. Students are strongly encouraged to have programming skills and basic proficiency in calculus and linear algebra, such as MATH 340.
B M I/STAT 768 — STATISTICAL METHODS FOR MEDICAL IMAGE ANALYSIS
Introduce key statistical methods and concepts for analyzing various medical images. Analyze publicly available and student/instructor supplied imaging data using the most up-to-date methods and tools. Aimed at graduate student and researchers with strong quantitative background. The course is self-contained. The knowledge of calculus and linear algebra is needed
B M I 773 — CLINICAL RESEARCH INFORMATICS
Course will familiarize students with basic informatics principles and techniques to support clinical research. Content includes information systems for protocol design; regulatory compliance; approaches for patient recruitment; efficient protocol management; data collection and acquisition; data security, storage, transfer, processing and analysis.
B M I/COMP SCI 776 — ADVANCED BIOINFORMATICS
Advanced course covering computational problems in molecular biology. The course will study algorithms for problems such as: modeling sequence classes and features, phylogenetic tree construction, gene-expression data analysis, protein and RNA structure prediction, and whole-genome analysis and comparisons.
B M I 826 — SPECIAL TOPICS IN BIOSTATISTICS AND BIOMEDICAL INFOMATICS
Covers advanced topics in the areas of biostatistics and biomedical informatics. Includes reading and discussion of original literature and individual student projects.
B M I/COMP SCI/PSYCH 841 — COMPUTATIONAL COGNITIVE SCIENCE
Studies the biological and computational basis of intelligence, by combining methods from cognitive science, artificial intelligence, machine learning, computational biology, and cognitive neuroscience. Requires ability to program.
B M I/STAT 877 — STATISTICAL METHODS FOR MOLECULAR BIOLOGY
Develop statistical problems in gene mapping, high throughputomic data analysis, phylogenetics and sequence analysis. Introduce ideas of key methods using published data. Statisticians learn statistical basis for research methodology. Collaboration among students and with biologists is encouraged through projects. GENETICS 466 or equiv strongly recommended
B M I 899 — PRE-DISSERTATOR RESEARCH
Pre-dissertator Research. Course is open to pre-dissertator students only.
B M I/B M E/BIOCHEM/CBE/COMP SCI/GENETICS 915 — COMPUTATION AND INFORMATICS IN BIOLOGY AND MEDICINE
Participants and outside speakers will discuss current research in computation and informatics in biology and medicine. This seminar is required of all CIBM program trainees.
B M I/MEDICINE 918 — HEALTH INFORMATICS FOR MEDICAL STUDENTS
Explore medical informatics as a new way to practice medicine with applications to patient care, electronic medical records, and patient safety.
B M I 990 — DISSERTATOR RESEARCH
Dissertator Research. Course is open to dissertators only.