Minor Degree Course List

RRSCS Minor Program Courses                             [Click here for a printable list of courses]

Capital UniversityCentral State UniversityColumbus State Community CollegeKent State UniversityMiami UniversityThe Ohio State UniversityOhio UniversityOwens Community College Sinclair Community CollegeStark State Community College • University of CincinnatiWittenberg UniversityWright State University

Capital University

CSAC 225 Calculus & Modeling for Biology
Capital University
Mathematics, Computer Science, and Physics
Fall semester 2010
Credit Hours: 4
Distance Learning: No

Prerequisites: MATH 121 or placement into 225

Description: introduction to mathematical modeling and calculus with applications to biology
Topics include discrete-time dynamical systems, limits, continuity, derivatives, optimization, stability of equilibria, definite and indefinite integrals, and differential equations. Students will employ computational software to solve problems and to analyze models of various biological processes.

Instructor:
Paula Federico
(614) 236-6121
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CSAC 245 Introduction to Computational Science
Capital University
Mathematics, Computer Science, and Physics
Fall 2010 and Spring 2011 semesters
Credit Hours: 3
Distance Learning: No

Prerequisites: None

Description: An introduction to the problems and solution methodologies in computational science. Computational tools such as a computer algebra system, a high performance computing engine, visualization software and Internet resources will used to explore and solve mathematical problems drawn from various fields of science.

Instructor:
Paula Federico
(614) 236-6121
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CSAC 392 Computational Biology
Capital University
Mathematics, Computer Science, and Physics
Spring 2011 semester
Credit Hours: 3
Distance Learning: No

Prerequisites: MATH 121 or 130

Description: An exploration of bioinformatics and mathematical biology. Topics include sequence alignment and analysis of DNA and proteins, modeling the physiology of the heart, statistical analysis of biology data and the use of web-based databases.

Instructor:
Karl Romstedt
(614) 236-6817
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CSAC 435 Computational and Numerical Methods
Capital University
Mathematics, Computer Science, and Physics
Spring 2011 semester
Credit Hours: 3
Distance Learning: No

Prerequisites: CSAC/CS 245, MATH 231. Recommended: CSAC 335/MATH335.

Description: Students explore the solution methodology of problems in computational science with an emphasis on numerical techniques. Topics include error analysis, numerical integration and differentiation, FFTs, solutions of linear systems, and numerical solutions of ODEs

Instructor:
Paula Federico
(614) 236-6121
Academic calendar


Central State University

CPS3465 Introduction to Parallel Computing
Central State University
Department of Mathematics & Computer Science
Spring 2011 semester
Credit Hours: 3
Distance Learning: No

Prerequisites: CPS331 Numerical Methods, or permission of instructor.

Description: Fundamentals of parallel computing including shared memory paradigm, semaphores, and dead lock; distributed memory paradigm including point-to-point and collective message passing constructs in MPI, parallel I/O, vector and structure derived data types; speed-up and scalability, check-point restart, parallel debugging; techniques, performance profiling, graphical and visualization techniques; parallel libraries, and systems modeling applications in high performance computing.

Instructor:
Robert L. Marcus

(937) 376-6262
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Kent State University

BSCI 70195, BSCI 40195/ BTEC-40220 Bioinformatics
Kent State University
Biological Sciences
Fall semester 2010
Credit Hours: 3
Distance Learning: Yes

Prerequisites: Eighteen hours of biology and permission of instructor.

Description: Learn to use GenBank, Ensembl and other genomic databases, Construct multiple sequence alignments, Phylogenetic tree reconstruction, Comparative and evolutionary genomics, Microarray data analysis, Protein structure prediction and much more…

Instructor:
Helen Piontkivska
(330) 672-3620
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Miami University

CSE 273 Optimization Modeling (3) MPT
Miami University
Computer Science & Systems Analysis
Winter semester 2011
Credit Hours: 3
Distance Learning: No

Prerequisites: MTH 251

Description: Use of deterministic models and computers to study and optimize systems. Includes an introduction to modeling, calculus-based models, financial models, spreadsheet models, and linear-programming models.

Instructor:
Mufit Ozden
(513) 529-0787
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CSE 443 High Performance Computing & Parallel Programming (3)
Miami University
Computer Science & Systems Analysis
Winter semester 2011
Credit Hours: 3
Distance Learning: No

Prerequisites: CSE 278 or equivalent

Description: Introduction to practical use of multi-processor workstations and supercomputing clusters. Developing and using parallel programs for solving computationally intensive problems. The course builds on basic concepts of programming and problem solving.

Instructor:
Michael Zmuda
(513) 529-0788
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CSE 466/566 Bioinformatics Computing Skills (3)
Miami University
Computer Science & Systems Analysis
Fall Semester 2010
Credit Hours: 3
Distance Learning: No

Prerequisites: Programming course and BOT 116, or BOT 342, or permission of instructor. Cross-listed with BOT/MBI/ZOO 466/566.

Description: Programming in Perl and MatLab. Use of BLAST, BioPerl, BioPHP, and MatLab Bioinformatics Toolbox. Emphasis placed on biological database design, implementation, management, and analysis.

Instructor:
Chun Liang
(513) 529-2336
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The Ohio State University

CSE 541 Elementary Numerical methods
The Ohio State University
Computer Science and Engineering
Fall quarter 2010 & Winter and Spring quarter 2011
Credit Hours: 3
Distance Learning: No

Prerequisites: 221/H221 or 230 or 502; Math 153

Description: Survey of basic numerical methods; number systems and errors of finite representation, solution of a single non-linear equation, interpolation, numerical integration, and solution of linear systems

Fall Quarter Instructor:
Jin He

Winter Quarter Instructor:
David Lee
(614) 688-3502
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Chem 644 Computational Chemistry
The Ohio State University
Chemistry
Fall quarter 2011
Credit Hours: 3
Distance Learning: No

Prerequisites: Prerequisites: Chem 252 (Organic Chemistry II)

Description: To provide a practical introduction to the theory and methods of molecular modeling and computational chemistry, focusing on its use for experimentalists. Hands-on experience will be obtained by all attendees in doing molecular mechanics, semi-empirical, ab initio quantum chemistry, density functional theory and modeling dynamic systems (molecular dynamics and kinetics).This is meant to be an introduction to molecular modeling for undergraduates, not a course on Quantum Mechanics.

Instructor:
Dr. Richard Spinney
614-247-6847
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MG660 Integrated molecular and cellular biology for non-biologists I
The Ohio State University
Molecular Genetics
Fall quarter 2011
Credit Hours: 3
Distance Learning: No

Prerequisites: Bio 101 or permission of instructor. Not open to students with credit for Mol Gen 500 or 605 or 606.

Description: Overview of molecular and cellular biology, focusing on molecular biology, biochemistry and genetics of single cells.

Instructors:
Erich Grotewold
(614) 292-2483
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Ohio University

CS 690 Exploring Bioinformatics
Ohio University
Computer Science
Fall quarter 2010
Credit Hours: 4
Distance Learning: No

Description: The course consists of weekly discussion-oriented meetings. All students are exposed to important issues in bioinformatics research via answering a series questions posed by the professor. Individual grades for in-class activities are based on each student’s presence, participation, and preparation.

Instructor:
Dr. Lonnie Welch
(740) 593-1575
Academic Calendar


CS 691 Exploring Bioinformatics
Ohio University
Computer Science
Winter quarter 2011
Credit Hours: 4
Distance Learning: No

Description: The course consists of weekly discussion-oriented meetings. All students are exposed to important issues in bioinformatics research via answering a series questions posed by the professor. Individual grades for in-class activities are based on each student’s presence, participation, and preparation.

Instructor:
Dr. Lonnie Welch
(740) 593-1575
Academic Calendar


PBIO 313 Bioinformatics
Ohio University
Computer Science and Plant Biology
Fall quarter 2010
Credit Hours: 5
Distance Learning: No

Instructor:
Sarah Wyatt
(740) 593-1133
Academic Calendar


CS 412 Parallel Computing
Ohio University
Computer Science and Plant Biology
Winter quarter 2011
Credit Hours: 5
Distance Learning: No

Prerequisites: CS 361 Data Structures

Description: This course is a practical-oriented introduction to Parallel Computing. It aims to teach students an understanding of the complex interactions between software and hardware in parallel and distributed system. Upon completion of this course, the student should be familiar with fundamental aspects of parallel and distributed systems, taxonomies, performance measures, and theoretical limitations of parallel systems. Students will understand parallel programming languages and middleware, and will be able to design and implement efficient parallel applications on a variety of parallel architectures. The course will be accompanied by a number of programming projects and exercises including, but not limited to, bioinformatics applications and case studies.

Instructor:
Dr. Frank Drews
(740) 593-1248
Academic Calendar


CS 512 Parallel Computing
Ohio University
Computer Science and Plant Biology
Winter quarter 2011
Credit Hours: 5
Distance Learning: No

Prerequisites: CS 561 Data Structures

Description: This course is divided into two parts. The first familiarizes students with the variety of approaches to parallel computing and the strengths and weaknesses of each. The second part introduces some of the methods for developing parallel algorithms and analyzes their performance. Different methods for mapping algorithms onto several different parallel architectures and the advantage and disadvantage of each are studied. Algorithms discussed include parallel sorting, searching, and matrix operations.

Instructor:
Dr. Frank Drews
(740) 593-1248
Academic Calendar


EE 663 Architecture of Parallel Computers
Ohio University
Department of Electrical Engineering and Computer Science
Winter quarter 2011
Credit Hours: 5
Distance Learning: No

Prerequisites: EE 561A or any basic computer architecture course. For more information, please contact the instructor.

Description: EE 663 is intended to provide graduate students with an in-depth study of high-performance computing (HPC) systems that exploit parallelism. Topics covered include (1) Introduction to Parallel Processing & Flynn's Classification, (2) Shared Memory Multiprocessors, (3) New Processor Architectures, and (4) Network-on-Chip (NoC) paradigms.

Instructor:
Avinash Karanth Kodi
(740) 597-1481
Academic Calendar


PHYS 303/503 Computational Physics
Ohio University
Department of Electrical Engineering and Computer Science
Winter quarter 2011
Credit Hours: 5
Distance Learning: No

Prerequisites: EE 561A or any basic computer architecture course. For more information, please contact the instructor.

Description: The course intends to show how numerical methods are used to solve the problems physicists face. The students are introduced to the process of approaching problems from a computational point of view:

  • understanding the physics and describing it in mathematical terms
  • manipulating the mathematics to the point where a numerical method can be applied
  • obtaining a numerical solution, and
  • understanding the physical problem in term of the numerical solution that has been generated.

    During the course the students will be introduced to the different computational facilities available in the department and learn their elementary use.

Instructor:
Charlotte Elster
(740) 593-1697
Academic Calendar


Owens Community College

To be announced


Sinclair Community College

PHY 211Introduction to Computational Methods
Sinclair Community College
Physics
Fall quarter 2010
Credit Hours: 5
Distance Learning: Yes

Prerequisites:  None

Description: Introduction to Computational Methods is an introductory course in engineering and science statistics that emphasize its practical use as an investigative tool in support of the scientific method. Major topics addressed include:

  • the scientific method
  • the nature and behavior of statistical data, and
  • the proper acquisition of statistical data and analysis of it.

Analytical tools include exploratory data analysis, hypothesis testing, statistical process control (SPC), analysis of variance (ANOVA) and design of experiments (DOE). This course is project based and is excellent preparation to employment as a technician or for additional university studies. Click here for more details.

Instructor:
Art Ross & Bob Chaney
art.ross@sinclair.edu
(937) 512-2236
Academic Calendar


PHY 212 Introduction to Modeling and Simulation
Sinclair Community College
Physics
Winter Quarter 2011
Credit Hours: 5
Distance Learning: Yes

Prerequisites:  None

Description: A variety of scientific problems will be analyzed by developing representative models, implementing the models, verifying and validating the model, reporting on the models in oral and written form, and by changing the models to reflect corrections, improvements and enhancements.  Systems to be modeled include first and second order dynamic systems and random processes that utilize Monte Carlo simulations, random walk simulations and cellular automation simulations.

Instructor:
Art Ross & Bob Chaney
art.ross@sinclair.edu
(937) 512-2236
Academic Calendar


PHY 220 Introduction to Computational Physics
Sinclair Community College
Physics
Spring Quarter 2011
Credit Hours: 5
Distance Learning: Yes

Prerequisites:  PHY 201 and MAT 201 or equivalent

Description: Mathematical models of physical systems will be developed and simulations will be constructed using Matlab and Vensim.  Explorations of complex systems will be conducted and results will be presented in oral and written form.  Activities include the study of projectile motion, harmonic motion of mass-spring systems, LRC circuits, Fourier analysis of signals, modeling empirical data, assessment of numerical techniques, and the survey of Monte Carlo techniques in physics.

Instructor:
Art Ross
(937) 512-2236
Academic Calendar


Stark State Community College

CST120 Computational Science Methods
Stark State Community College
Fall semester 2010 & Winter 2011
Credit Hours: 3
Distance Learning: No

Prerequisites: None

Description:  Develop the necessary computational skills to model and simulate a broad set of deterministic and stochastic systems including the modeling of empirical data. Integrated problem solving methods found in modern research facilities and high technology workplaces will be utilized.

Instructor:
Robert Berens
330-494-6170
Academic Calendar


CST121 Introduction to Modeling and Simulation
Stark State Community College
Fall semester 2010 & Winter 2011
Credit Hours: 3
Distance Learning: No

Prerequisites: None

Description: A variety of scientific problems will be analyzed by developing representative models, implementing the models, verifying and validating the model, reporting on the models in oral and written form, and by changing the models to reflect corrections, improvements and enhancements.  Systems to be modeled include first and second order dynamic systems and random processes that utilize Monte Carlo simulations, random walk simulations and cellular automation simulations.

Instructor:
Richard Hartmann
(330) 494-6170
Academic Calendar


CST221 Computational Biology
Stark State Community College
Fall semester 2010 & Winter 2011
Credit Hours: 3
Distance Learning: No

Prerequisites: None

Description: A variety of scientific problems will be analyzed by developing representative models, implementing the models, verifying and validating the model, reporting on the models in oral and written form, and by changing the models to reflect corrections, improvements and enhancements.  Systems to be modeled include first and second order dynamic systems and random processes that utilize Monte Carlo simulations, random walk simulations and cellular automation simulations.

Instructor:
Jean Zorko
(330) 494-6170
Academic Calendar


University of Cincinnati

CHEM 801 Advanced Computational Chemistry I
University of Cincinnati
Fall quarter 2010
Credit Hours: 3
Distance Learning: No

Prerequisites: Permission of Instructor

Description: Discusses the chemistry, biophysics, and statistics behind computational methods used to predict the structure and function of proteins and RNA molecules from sequence information. Applications of bioinformatic packages to biophysics problems and development of analysis tools will be emphasized.

Instructor:
Ruxandra Dima
(513) 556-3961
Academic Calendar


CHEM 802 Advanced Computational Chemistry II
University of Cincinnati
Fall quarter 2010
Credit Hours: 3
Distance Learning: No

Prerequisites: Permission of Instructor

Description: ocuses on the application of computer simulations to the study of biological systems. discusses concepts in classical mechanics, thermodynamics and statistical mechanics and their application to Monte Carlo and molecular dynamics methods. The use of molecular modeling programs will be illustrated using specific biomolecular systems.

Instructor:
George Stan
(513) 556-3049
Academic Calendar


Wittenberg University

COMP 260 Computational Models and Methods
Wittenberg University
Computer Science
Fall semester 2010
Credit Hours: 3
Distance Learning: No

Prerequisites: 1. MATH 131 or MATH 201. 2. COMP 150 or previous programming experience with discretion of the instructor. The student will be expected to be familiar with the use of a scientific graphing calculator. This course is cross-listed as MATH 260. Students may enroll in either COMP 260 or MATH 260, but not both. Mathematical-reasoning intensive.

Description: Computational science is the field of study that integrates natural science, computer science and applied mathematics. This course is an introduction to the principles and approaches of computational science. This includes the understanding, development, and use of mathematical models as well as their effective computer implementation using languages such as Mathematica®, C/C++ and FORTRAN. It is specifically designed to be accessible to a wide range of students, especially those with an interest in biology, chemistry, geology, physics or psychology. A spectrum of problems taken from these sciences will be addressed. Topics include: using Mathematica®, Sources of Errors, The Experimental Method, Types of Science Models, Formula Evaluation, Dimensional Analysis, Model Sensitivity, Visualization Methods, Solving Equations, Computer Simulation, Floating-Point Arithmetic, Limits of Computation, Data Fitting, Optimization Methods and Ethical Issues. Each student will undertake a realistic modeling project in one of the sciences. Computer laboratory required.

Instructor:
Eric A. Stahlberg
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Computational Science Course Info


CHEM 380 Computational Chemistry
Wittenberg University
Computer Science
Fall semester 2010
Credit Hours: 2-4
Distance Learning: No

Prerequisites: Permission of the instructor

Description: Selected topics of current interest in various areas of chemistry.

Instructor:
Justin Houseknecht
Academic calendar
Computational Science Course Info


Wright State University

To be announced