Spring 2012

 

ENG BF 690: Bioinformatics Challenge Project

Small teams of students working on open-ended research projects that involve bioinformatics as a key element, and which use large data sets to make predictions about molecular function that can subsequently be tested in wet-lab experiments. A faculty member serves as an advisor of each group. Professor Benson, Thurs, 11:00-12:30 p.m.

ENG BF 752: Legal & Ethical Issues of Science and 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. Professor Yashon, Tues, 9:30-11:30 a.m.

ENG BE 768: Biological Database Analysis

Describes relational data models and database management systems. Teaches the theories and techniques of constructing relational databases with emphasis on those aspects needed for various biological data, including sequences, structures, genetic linkages and maps, and signal pathways. Introduces relational database query language SQL. Summarizes currently existing biological databases and the Web-based programming tools for their access. Object-oriented modeling is introduced primarily as a design aid for dealing with the particular complexities of biological information in standard RDB design. Emphasis will be on those problems associated with dealing with data whose nomenclature and interrelationships are undergoing rapid change. Prereq: CAS CS 112 or CAS CS 113, graduate standing, or consent of instructor. Background knowledge of biochemistry and genetics. Professor Benson. Tues, Thurs, 4–6 p.m.

ENG BF 778: Physical Chemistry for Systems Biology

This course introduces students to quantitative modeling in bioinformatics and systems biology. We begin with basic principles of statistical thermodynamics, chemical kinetics, with selected applications in biomolecular systems. Next, we describe molecular driving forces in biology, and computation with biomolecular structures. Finally, we discuss quantitative models of biomolecular networks, and design principles of biological circuits. Professor Xia. Mon, 1–4 p.m.

ENG BF 810: PhD Laboratory Rotation System

This course is for PhD students to take part in a laboratory rotation system. Students will become familiar with research activity in Bioinformatics labs. These rotations will help students identify the laboratory in which they will perform their dissertation research. Post-bachelor PhD students must complete one 9-week rotation in their first semester of matriculation and two in their second semester. PhD standing, 1 credit per rotation. Professors Mohr and Segre.

ENG BF 821: Bioinformatics Graduate Seminar

In this course, the students present advanced papers in Computational Biology and Bioinformatics. The papers are chosen to cover recent breakthroughs in genomics, computational biology, high-throughput biology, analysis methods, computational modeling, databases, theory and bioinformatics. 2 credits. Professor Xia. Wed, 1–3 p.m.

Fall 2012 Courses

 

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 cr. Prereq: Fundamentals of programming and algorithm design (EK 127 or equivalent), basic molecular biology (BE 209 or equivalent), statistics and probability (BE 200 or equivalent), or consent of instructor. Professor Galagan. Tues, Thurs, 2–3:30, Fri, 10–11 a.m.

ENG BF 690: Bioinformatics Challenge Project

Project course for first-year Bioinformatics graduate students. Open-ended problems will involve bioinformatics as a key element, typically requiring the use of large data sets and computational analysis to make predictions about molecular function, molecular interactions, regulation, etc. Projects will be proposed by the Bioinformatics program faculty and selected by students in teams of three. The end result will be a set of predictions, some of which can be validated retrospectively using data available through online sources and some of which will require experimental validation. During the last 2 months of the academic year, teams will design feasible validation experiments in consultation with the experimental faculty. Professor Benson. Wed, 12–1:30 p.m.

ENG BF 751: Molecular Biology and Biochemistry: Molecules and Processes

Seminar course consisting of two modules: (1) “Molecules”—an introduction to the molecular makeup of living organisms, including the mechanisms of action of key players in metabolism and other dynamic functions of cells; and (2) “Processes”—a survey of biochemical and cellular functions at the systems-biology level. Each week, fundamental information about the makeup and properties of biological components at the molecular and supramolecular levels will be presented and discussed in the first of two 2-hour classes. The second class will involve presentations by training faculty about exemplary systems cognate to the material presented earlier that week. In most cases these presentations will start at the level of physiological function and “drill down” into the molecular details. The “Processes” module will include introductions to metabolic and signaling networks, sub-networks, and control processes. Two class sessions will be devoted to student reports on topics covered in weeks 1–6. Professors Mohr and Segrè (lecturers, coordinators), and various training faculty. Tues, Thurs, 10:00-12:00 p.m.

ENG BE 777: Computational Genomics

A case-study approach to current topics in computational genomics. Mathematical and engineering tools for analyzing genomic data are reviewed. The relationships between sequence, structure, and function in complex biological networks are studied using quantitative modeling. Whole genome analysis is performed. Completion of a series of projects emphasizing real-life data, integrated approaches, practical applications, hands-on analysis, and collaboration. Course projects aim at improving current approaches and involve C and/or PERL programming to interface with existing software packages. The course will be offered in a computer laboratory equipped with one laptop per student. Prereq: ENG BE 561 or consent of instructor. Professor Xia. Mon, Wed, 10 a.m–12 p.m.

ENG BF 810: PhD Laboratory Rotation System

This course is for PhD students to take part in a laboratory rotation system. Students will become familiar with research activity in Bioinformatics labs. These rotations will help students identify the laboratory in which they will perform their dissertation research. Post-bachelor PhD students must complete one 9-week rotation in their first semester of matriculation and two in their second semester. PhD standing, 1 credit per rotation. Professors Mohr and Segre.

ENG BF 820: Research Opportunities in Bioinformatics

Presentations by Bioinformatics faculty members that focus on research projects being investigated in their laboratories. Emphasis is placed on the description of collaborative projects involving experimental and computational approaches to bioinformatics research problems. Instructor TBA

ENG BF 821: Bioinformatics Graduate Seminar

Students read, present, and discuss assigned advanced papers in bioinformatics and computational biology. The papers are chosen to cover recent breakthroughs in genomics, computational biology, high-throughput biology, analysis methods, computational modeling, databases, theory, and bioinformatics. Trainees are required to take the seminar course twice. Professor Segre.