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Course Summary

Course Description

Advances in biology, medicine and health care have come to rely to a large measure on techniques, technologies and systems to harness and make sense of data and information. Students choosing the BHI concentration will be able to understand, design and manage these techniques, technologies and systems.

Career Possibilities

  • Hospital Manager
  • Government Analyst
  • Actuary
  • Care Delivery Coordinator
  • Clinical Informatics Director
  • Bioinformatics Scientist

Major Foundation Requirements

CS300 / Solving Problems with Algorithms

Learn how to design and analyze algorithms used to address complex problems. Solve problems ranging from logistics to route optimization to robotic arm control using algorithms such as hashing, searching, sorting, graph algorithms, dynamic programming, greedy algorithms, divide and conquer, backtracking, random number generation, and randomized algorithms.

CS301 / Bayesian Statistics in Practice

Bayes’ Theorem is a framework for combining prior information with new information to compute a posterior probability distribution. Gain insights into the differences between frequency-based statistics and Bayesian statistics by examining practical cases borrowed from such diverse fields as criminal justice, computer security and epidemiology. Also learn how to apply Bayesian approaches to learning from data

CS302 / Decision Science

Apply formal models of decision making to practical problems involving uncertainty, competition, complex systems, risk aversion, decision biases, and multiple objectives. Follow one principal case study throughout the course — for example, the decisions involved in pursuing the development of a drug. The case study incorporates decision trees, risk-adjusted calculations, optimization, and other methods.

Concentration Core Requirements

CS350 / Bioinformatics

Computational methods dominate much of molecular biology, genetics and studies of evolution. These methods include database searching (for example, GenBank, PDB and BLAST), pairwise sequence alignment using dynamic programming (GAP and BestFit), gene finding, and phylogenetics. Apply these techniques and software tools to the exploration of genetic data related to a disease.

CS411 / Building Useful and Usable Database Systems

Use data models, data description languages, query methods such as relational algebra and SQL, data normalization, and transaction and security protocols to design an efficient and secure database system for a real-world example. Also explore new trends in databases to sketch out what databases of the future may look like. For example, students examine how graph databases can be leveraged to process social network data or discover relationships between entities, with applications to biological and health care databases.

CS550 / Biological Networks and Systems Biology

Combine concepts and methods from multiple disciplines (biology, computer science, mathematics, and physics) to examine the emergence of higher-level properties of complex biological systems. Discover how current software tools have been developed and how they function in systems biology. Students become familiar with network and pathway analysis using "omics" data and are able to use high-throughput data to identify biologically significant features using systems biology approaches

Concentration Electives

CS352 / Biomedical Computing

Analyze health care data (clinical data, electronic medical records, genetic data, public health data, hospital data, and claims data). Understand the relationships between different types of data (for example, between clinical and genetic data) and how to design and build health care information systems. Activities include designing and developing a prototype of a system for diagnosis decision support, creating a chronic disease management information system, and designing the roadmap for a national epidemiology and bio-surveillance system.

CS413 / Privacy and Security in the Real World

In the first part of the course, learn how to use techniques for manipulating information without releasing personal identifiable information. Examine existing practices concerning consumer data, search data, health care data, and geolocation data, and then design possible solutions. In the second part of the course, manage a portfolio of security approaches (risk analysis, cryptography, identification and authentication systems, security protocols, intrusion detection systems, data obscurity, and firewalls) to protect a system from worms and denial-of-service attacks while maintaining privacy.

CS452 / Biophysics

Research the tools used to characterize biological molecules and biophysical processes — electron and atomic force microscopy, nuclear magnetic resonance, x-ray diffraction, and other light scattering methods. Study recent advances in the use of optical tweezers in the measurement of piconewton forces, and discuss centrifugation, electrophoresis and dielectrophoresis. Also exploit structural databases and explore the hydrodynamics of biological macromolecules, viscosity, translational and rotational diffusion, chromatography, conductance, water (as a solvent), polyelectrolytes, and Debye-Hückel theory.

CS551 / Synthetic Biology

Discover how to design a plausible and compelling synthetic biological system, develop a detailed design plan and construction roadmap, and then evaluate ownership, commercial and ethical aspects of the project.

CS552 / Causal Inference

Apply methods for establishing causation — from randomized controlled experiments to statistical approaches to infer causation from observational studies (matching methods and regression adjustments). Critically examine claims of causal links in such varied contexts as clinical trials (does a drug work better than a placebo?), economics (do incentives cause the desired behavior?), social sciences (does a friend’s happiness cause someone to be happy?), and program evaluation (do microloans reduce poverty?). Students conduct their own analysis on a topic of their choosing.

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