Background

The past 50 years have witnessed a scientific revolution of the first magnitude, a revolution which has transformed our knowledge of the cell from next to nothing, to nearly everything. With the complete sequence of the human and other genomes now elucidated, we will soon a have a complete parts list of the human cell—the precise location and base sequence of every gene in a reference genome. The reference allows us to rapidly characterize polymorphisms across the human population, and it also enables molecular fingerprinting technologies that permit identification of the precursors and consequences of normal and pathological changes in gene expression.

These changes are driving, and coupled to, advances in monitoring and understanding the collective properties of proteins and metabolites, and their modifications under various forms of stress. The full armamentarium of tools and information is profoundly altering biomedical research and the culture of science, and it is destined—during the next 10–20 years—stimulate an explosive growth in diagnostics, prognostics and therapeutics, profoundly altering the practice of medicine. But with this bewildering explosion of information and tools, comes subtle and complex dilemmas of choice, which must be faced collectively by society, and individually by patients and health care professionals. The need for clinically trained leaders, who understand these changes, their origin and their course, and who will play a proactive role in guiding their development, is crucial if the world’s population is to benefit by these remarkable scientific advances.

Goal

To train physician-scientists who will be leaders in applying and stimulating the development of post-genomic technologies to clinical research and the practice of medicine.

Requirements

The master’s degree requires a total of 32 credits. MS candidates must demonstrate mastery of the core subject matter (no lower than a “B” in core courses) and complete a masters research project with a written and oral report which will serve as a masters thesis. Candidates will be expected to develop their ideas to the point of publication.

Core Courses

ENG BF 527: Bioinformatics Applications

This course explores the use of bioinformatics databases and software as research tools. Students will use data mining tools to extract DNA and protein sequences from primary and secondary databases. Software tools will be used to compare and analyze these sequences and construct gene and protein models for solving research problems related to molecular evolution, drug discovery, and genetic bases for development and diseases. (4 credits)

ENG BE 562: Computational Biology: Genomes, Networks, Evolution

The algorithmic and machine learning foundations of computational biology, combining theory with practice are covered. Principles of algorithm design and core methods in computational biology, and an introduction of important problems in computational biology. Hands-on experience analyzing large-scale biological data sets.  (4 credits)

ENG BE 768: Biological Database Analysis

Describes relational data models and database management systems; teaches the theories and techniques of constructing relational databases to store various biological data, including sequences, structures, genetic linkages and maps, and signal pathways. Introduces relational database query language SQL and the ORACLE database management system, with an emphasis on answering biologically important questions. Summarizes currently existing biological databases. Describes Web based programming tools to make databases accessible. Addresses questions in data integration and security. The future directions for biological database development are also discussed. (4 credits)

SPH BS 830: Design and Analysis of Microarray Data

The purpose of this course is to present some of the methods for the analysis of gene expression data measured through microarrays. The course will start with a review of the basic biology of gene expression and an overview of microarray technology. The course will then describe the statistical techniques currently used to compare gene expression across different conditions and it will progress to describe the analysis of more complex experiments designed to identify genes with similar functions and to build models for molecular classification. The statistical techniques described in this course will include regression, discriminant analysis, clustering, classification, and simple graphical models. Methods for computational and biological validation will be discussed. Students will apply these methods in homework assignments and a final project. (4 credits)

GRS BF 821: Bioinformatics Graduate Seminar

Journal club to discuss current issues and research topics in bioinformatics. Student presentations. Faculty involvement to lead discussion. (2 credits)

ENG BF 501: Bioinformatics Research

Participation in a research project under the direction of a faculty advisor. Variable credits (6-10 credits)

Electives

ENG BE 777: Computational Genomics

This course is a sequel of two core computational courses—BE 561 Protein and DNA sequence Analysis and BE 768 Biological Database Analysis. BE 777 is a hands-on course, and the goal is to apply theories and algorithms taught in BE 561 and BE 768 to real-life data sets, such as entire genomes. (4 credits)

ENG BF 501: Principles of Genetics & Genomics

This course will serve as a foundation for understanding the heritable basis of numerous biological traits, the relationships among genes, and the regulation of their expression. We will focus on the ability to use genetic systems to probe these problems, and therefore will heavily explore the experimental aspects of these investigations. In addition, we will discuss the impact of the genome sequences on the practice of modern science. Moreover, we will use a case study approach to investigate the rich variety of scientific insights gained through genetic studies. (4 credits)

SPH EB 703: Biostatistics

Topics include confidence intervals and hypothesis testing; sample size and power considerations; analysis of variance and multiple comparisons; correlation and regression; multiple regression and statistical control of confounding; logistic regression; and survival analysis. This course gives students the skills to perform, present, and interpret basic statistical analyses. For the more advanced topics, the focus is on interpretative skills and critically reading the literature. (4 credits)

GMS GE 702: Advanced Topics in Genetics & Genomics

The Advanced Topics course will focus on the mechanisms of biological processes that influence the inheritance and regulation of genes. In particular, the molecular details of genetic, epigenetic, and genomic processes will be discussed. Both genetic and genomic experimental approaches to these processes will be explored. In addition, we will discuss the possibilities of utilizing these technologies in medical treatments (4 credits)

GMS GE 705: Critical Thinking in Genetics and Genomics

This class is designed to chronologically follow the development of a field of study, the cell cycle, to allow students to explore the logical evolution of a coherent line of scientific inquiry. The individual meetings build on the background studies discussed in previous meetings, examine apparent discrepancies in experimental results, critique the approaches employed by the authors, and consider the logical follow-through experiments for the results at hand. (4 credits)

BF 752: Legal & Ethical Issues of Science & Technology

This course addresses the ethical, legal, and scientific aspects of 21^_st-century genetics. As part of the new technologies, individuals, families, and society as a whole will have to make increasingly difficult decisions that affect us all. Students will analyze cases, question the legal system’s role in regulating this field, and discuss options for present and likely future challenges. Topics include gene therapy, DNA forensics, new reproductive techniques, biotechnology and patenting, transplantation, clinical research, and laboratory ethics. Students participate in a once-weekly discussion class, complete regular online homework assignments, write an opinion paper, formally present a topic to the class, participate in a group case-analysis project, and write a final paper. (4 credits)

GMS BI793: Mass Spectrometry, Proteomics, and Functional Genomics

This course will give investigators the background necessary to effectively design mass spectrometric experiments and interpret data. The instrumentation will be described at a level appropriate to graduate students in biochemistry and the structure of biological macromolecules will be described as it applies to mass spectrometry. Students will leave the course with a full understanding and effective use of mass spectrometric data in their research. Lectures will be devoted to instrumentation, ionization methods, and applications to proteins, lipids, carbohydrates, glycoconjugates, and nucleic acids. The uses of the technology in proteomics, biotechnology and medicine will be covered in detail. (4 credits)