University of Pittsburgh

A. Department of Biological Sciences

BIOSC 1280, Microbial Genetic Engineering

This course will consist of a series of lectures discussing the molecular genetics of prokaryotic and eukaryotic microbes and ways in which they can be genetically engineered. It includes: (1) the genome structures of microbes, (2) classic methods for genetic exchange, (3) current approaches to genetic engineering, (4) applications of genetic engineering to human disease. Visits to the Computer Lab will introduce Web-based analysis of microbial genome sequences.

BIOSC 1540, Computational Biology

This is an upper-level course designed to give students a broad understanding of how computational approaches can be used to solve problems in biology. Current computational techniques will be covered in depth, including sequence analysis and alignment, the construction of phylogenies, and comparison-based prediction of function and structure. The course will also provide survey-level coverage of new and specialized techniques, in the form of brief introductions and case studies. Both the biological and computational underpinnings of the methods will be addressed, and a substantial amount of hands-on experience will be provided.

BIOSC 1940, Molecular Biology

This course will examine the molecular basis of life processes, with a primary emphasis on genes (what they are, what they do, how they determine the properties of an organism). Topics covered will include replication of DNA, transcription of DNA into RNA, and translation of RNA into protein. Much of the course will be concerned with how these processes are regulated in response to changes in the environment, and how this regulation relates to the observed properties and behavior of the organism.

BIOSC 1980, Molecular Biophysics

This is an advanced level course that introduces students to the physical chemistry of biological macromolecules and the methods used to study their structure, interactions, and function. Concepts of positional and structural information will be integrated with those of thermodynamics, statistical mechanics, and kinetics. We will focus on the enzyme RNAse-A, a paradigm for the study of the physico-chemical properties and mechanism of function of proteins.

B. Department of Chemistry

CHEM 1460, Computational Methods in Chemistry

An introduction to computational methods in Chemistry simulation methods with emphasis on modeling chemical systems. The students will become familiar with mathcad, a user friendly, mathematical spreadsheet-type program, which makes it easy to conduct computer experiments. A student should have completed at least two semesters of calculus.

C. Department of Computer Science

CS 1501, Data Structures and Algorithms

All problem-solving methods of computer science involve the manipulation of data. Some of the tools, called data structures, used in storing and manipulating data are studied in this course. Among these data structures are lists and trees. Problem solving methods investigated include: divide and conquer techniques, greedy methods, and dynamic programming. Various sorting and searching methods will also be studied. Finally, students in this course will be introduced to methods of analyzing the efficiency of an algorithm.

CS 1510, Design and Analysis of Algorithms

This course will cover methods and strategies that are useful for the design on nonnumeric algorithms. Students are expected to design their own algorithms.

CS 1566, Introduction to Computer Graphics

The basic concepts, tools and techniques of computer graphics and multi-media are described. The fundamental transformations of scaling, translation, rotation, windowing and clipping are presented. Primary emphasis is on 2-D effects and animation that can be created. Multi-media databases are also discussed. Students will be expected to develop graphic applications in java for the web.

Carnegie Mellon University

A. Department of Biological Sciences

03-439, Introduction to Biophysics

This course introduces the use of physical methods in the study of biological systems. The biological systems to which the methods are applied will be surveyed and current interpretations of their structure and function will be discussed. Biological systems that have been discussed in recent years include membranes, nerves, muscle, photosynthetic systems and visual systems; not all these topics can be treated, and the particular selection can be influenced by student interest. The treatment of biophysical methods will be based on physical principles, which will be treated with appropriate mathematics when necessary. The biophysical methods will be selected from among the techniques of x-ray and neutron diffraction, light scattering, birefringence, microscopy, Raman and IR spectroscopy, dielectric response and calorimetry.

03-510, Computational Biology

This course covers a range of applications of computers to solve problems in biology and medicine. Specific topics covered are computational molecular biology (analysis of protein and nucleic acid sequences), biological modeling and simulation (including computer models of single and multiple neuron behavior, biochemical kinetics, and simulation of mutation), graphics and statistics, and biological imaging. Course work will include use of software packages for these applications, reading of scientific papers, and programming assignments.

03-533, NMR in Biomedical Sciences

The aim of this course is to introduce the students to new advances in the field of NMR in biomedical sciences. This one semester course covers the following topics: (1) fundamentals of NMR; (2) new techniques such as NMR imaging and in vivo spectroscopy as well as pulse techniques and NMR microscopy; and (3) applications of NMR to investigate macromolecular structures, interactions, and dynamics. This course is open to graduate and advanced undergraduate students. Graduate students are expected to carry out an independent project in addition to fulfilling the usual requirements of the course.

B. Department of Chemistry

09-560, Computational Chemistry

Computer modeling is playing an increasingly important role in chemical research. This course provides an overview of computational chemistry techniques including molecular mechanics, molecular dynamics and both semi-empirical and ab initio electronic structure theory. Sufficient theoretical background is provided for students to understand the uses and limitations of each technique. An integral part of the course is hands on experience with state-of-the-art computational chemistry tools running on graphics workstations.

C. Department of Computer Science

15-211, Fundamental Data Structures and Algorithms

Fundamental programming concepts are presented together with supporting theoretical bases and practical applications. This course emphasizes the practical application of techniques for writing and analyzing programs: data abstraction, program verification, and performance analysis. These techniques are applied in the design and analysis of fundamental algorithms and data structures. The course is currently taught in Java.

15-462, Computer Graphics 1

This course provides a comprehensive introduction to computer graphics modeling, animation, and rendering. Topics covered include basic image processing, geometric transformations, geometric modeling of curves and surfaces, animation, 3-D viewing, visibility algorithms, and shading. Students gain experience producing simple animations.

15-463, Computer Graphics 2

More advanced computer graphics. The goal is to teach students to understand how graphics algorithms work, and how to develop their own, rather than on the use of commercial software systems. Topics include: image filtering, Fourier transforms, image warping, parametric surfaces, spatial data structures, animation, antialiasing, recursive ray tracing, radiosity, and volume rendering.

D. Department of Physics

33-241, Introduction to Computational Physics

The course emphasizes the formulation of physical problems for machine computation with exploration of alternative numerical methods. Work will be done on arange of computers from workstations to high performance computing platforms.

33-456, Advanced Computational Physics

This course will emphasize application of practical numerical techniques to the type of problems which are encountered by practicing physicists. The student will be expected to understand the principles behind numerical methods such as SVD decomposition, chi-squared minimization, and Fast Fourier Transform and Monte Carlo simulation of experiments. Applications will include data analysis and eigenvalue problems. Emphasis will be placed on the ability to implement complex algorithms accurately by devising methods of checking results and debugging code. The students will be expected to become proficient in Fortran or C programming.

Duquesne University

A. Department of Chemistry and Biochemistry

CHEM 121, 122, General Chemistry

The fundamental principles and concepts of chemistry are presented from the standpoint of atomic and molecular structure with illustrative examples from descriptive chemistry. The basic concepts of thermodynamics, chemical kinetics and equilibrium are introduced. The laboratory portion of the first semester illustraties physical and chemical properties in a quantitative manner, and the laboratory portion of the second semester illustrates the principle of ionic equilibria including quantitative inorganic analysis.

CHEM 321, 322, Physical Chemistry

A study of the structure and properties of the various states of matter, thermodynamics, thermochemistry, kinetics and an introduction to quantum chemistry.