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.

Program Content:
The Boston University Graduate Program in Bioinformatics consists of more than 50 faculty from the Colleges of Arts and Science, Medicine and Dentistry, Engineering and Law. The doctoral program which was approved by the Board of Trustees in 1999, and currently includes 68 students co-mentored by a combination of advisors—experimental, clinical, and computational. Some fifty students are currently enrolled in the Sloan Foundation supported Professional MS Program. Multidisciplinary laboratories with trainees form diverse backgrounds (mathematics, biology, chemistry etc) and levels (form undergraduate through post-doctoral) common. Collaborations between laboratories is also common, with joint seminars, research papers and grant proposals central to the Program.

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.

Contact Information:
For additional information, please contact Dr. Avrum Spira, Co-Director, at 617-638-4860 or email

Core Courses:
ENG BF527: 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 BE561: Protein and DNA Sequence Analysis
The goal of this course is to teach the mathematical and computational techniques to make biological inferences from the DNA and protein sequences. Pairwise sequence comparison is studied in detail. The algorithm is extended to deal with more general cases and applied to RNA structure prediction. Multiple sequence alignment and conserved sequence pattern recognition (sequence profile analysis) are studied extensively. Methods of using phylogenetic trees to study the molecular evolution are described.
Methods of identifying coding regions in genomic data are considered. Mathematical models and computational algorithms for genetic regulation are described. An introduction to protein 3-dimentional structure prediction is given. (4 credits)

ENG BE768: Biological Database Systems
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 BS920: Statistical Methods in Functional Genomics
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 BF821: Bioinformatics Gradute Seminar
Journal club to discuss current issues and research topics in bioinformatics. Student presentations. Faculty involvement to lead discussion. (2 credits)

ENG BF501: Bioinformatics Research
Participation in a research project under the direction of a faculty advisor. Variable credits (6-10 credits)

Electives:
ENG BE777: Comutational Genomics
This course is a sequel of two core computational courses - "BE561 Protein and DNA sequence Analysis" and "BE768 Biological Database Analysis". BE777 is a "hands-on" course, and the goal is to apply theories and algorithms taught in BE561 and BE768 to real-life data sets, such as entire genomes. (4 credits)

ENG BF501: 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 EB703: 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 GE702: 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 GE705: 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)

LAW JD933: Biotechnology Law and Ethics
This seminar is focused on individual and organizational responsibility in biotechnology research, developmental and commercial contexts. Issues to be discussed from legal and ethical perspectives include property rights, privacy and discrimination, the federal regulatory role, self-regulatory safeguards, liability implications for individual/organizational behavior, and policy responses to societal concerns in the U.S. and abroad. Materials will present cases involving gene therapy, cloning, and biomaterials in the medical and health sector, and farming and crop modification in the agricultural sector. Term paper. (3 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)