BIOINFORMATICS
TECHNOLOGIES
LFSC520
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█ Course Objectives: Upon completion of this course, the student should be able to:
- Identify a variety
of mathematical and computational applications arising in research
problems in bioinformatics at a variety of hierarchical levels from
molecular through ecosystem.
- Demonstrate an overall
understanding of the basic terminology of the mathematics and
computational aspects of these applications.
█ Course Description: LFSC520: Bioinformatics Technologies. One semester course; 1 lecture hour. 2 credits. Prerequisites: LFSC510 Integrative Life Sciences I:
Biological Complexity or permission of instructor. Introduction to the hardware
and software used in computational biology, proteomics, genomics, mathematical
modeling and simulation, network analysis, image processing, biostatistics,
eco-informatics, and other areas of data analysis in the life sciences. The
course will also introduce students to data mining, the use of databases,
meta-data analysis, and techniques to access information. One of the main
missions of this course is to provide a timely orientation to the tools and
sources of expertise available to the research students at VCU so that they can
develop and carry out their dissertation research projects.
█ Major Course Units:
1)
Basics
2)
Biostatistics/Data
Mining/Neural Networks
3)
Image Processing
4)
Omic Analysis
5)
Visualization and
Graphics
6)
Molecular Modeling and
Computational Chemistry
7)
Network and Systems
Analysis
8)
Multi-scale Modeling
and Simulation
9)
Eco-Informatics, GIS,
and Spatial Data Analysis
█ Course Meeting Information: LFSC 520 is scheduled to
meet on Mondays from
█
Reasonable Accommodation: Section 504 of the Rehabilitation Act of 1973 and
the Americans with Disabilities Act of 1990 requires VCU to provide academic
adjustments or accommodations for students with documented disabilities.
Students seeking academic adjustments or accommodations must self-identify with
the Coordinator of Services for Students with Disabilities. After meeting with
the Coordinator, students are encouraged to meet with their instructors as
early in the semester as possible to discuss their needs. Details on the Office
of Disability Support Services may be found at:
█ Academic Integrity Policy: Students in this course are expected to abide by the policies of the VCU Honor System. These policies are published annually in the University Resource Guide
and
can be found at: 
█ 
Required TextS:
1)
Bergeron, B. (2002). Bioinformatics Computing. Prentice
Hall-PTR:
2)
Gibas C. & Jambeck, P.
(2001). Developing Bioinformatics
Computer Skills. O’Reilly & Associates, Inc.:
█ Required
█
Recommended/Supplemental
website on a regular basis.
Barnes, M.R. and Gray, I.C. (eds.) (2003). Bioinformatics for Geneticists. John
Wiley & Sons:
█
Literature Resource List:
- Baxevanis, A.D. and Ouellette, B.F.F. (eds.) (2001). Bioinformatics: A Practical Guide to the Analysis of Genes and
Proteins. John Wiley & Sons:
- Schulze-Kremer, S. (1996). Molecular
Bioinformatics: Algorithms and Applications. Walter de Gruyter:
- Sensen, C.W. (2002). Essentials of
Genomics and Bioinformatics. Wiley-VCU:
█ Library
Library resources for undergraduate and
professional students can be found at:
█ 
Email
Requirement: All students in LFSC520 are
required to have a valid email address during the entire period of the course.
VCU offers student email addresses. To obtain a student email account visit:
You are expected to abide by the Student Email
policy found at:
█ Pagers,
Beepers, and Cell Phones: If you carry a cell
phone or a beeper, please set them to vibrate mode before you enter the class.
█
Food: You
may not eat or drink in the BCCL
laboratory/class. 
█ Attendance and
Participation: You are expected to attend
each class, arrive on time, and remain for the entire class. You are expected
to come to class prepared to discuss the readings and to ask questions on the
scheduled topic material. However, if you are unable to attend a class, please
inform the class coordinator in advance if possible. You are responsible for
arranging to make up missed content. Attendance and participation is an
important requirement for this class, but is not part of your grade. Because
there is much learning to be had, both in class and in the lab experiences, any
student missing more than two classes may see their absences reflected in their
final grade.
█ Course
Format: A heavy emphasis will be placed on integrating your
research interests with the material presented in this course. It is expected
that students will attend each class, remain for the entire class period, and
be prepared to discuss weekly readings and to ask questions as needed. No
question is considered stupid in this class. Help a neighbor, ask your
question. It is also expected that students will come to class having read the
materials for the class. This does not mean that you will be expected to
understand the material. It means that you will have a degree of awareness of
the material and that you will know what it is that you need help with.
Lectures may deviate from the schedule or may contain material not necessarily
covered in any of the readings. In addition to the primary lecturer, there may
be invited speakers who will lecture on special topics. There may also be trips
to various places, for the purpose of seeing realworld application of the
classroom discussion.
█ Course
Supplies: You will need the following
items: some CD’s and/or zip-disks for program storage and work. Other supplies may
become necessary depending upon the choices of projects that you make
throughout the semester.
█ Software Downloads and
Purchase. As part of the coursework, you will be required to
download various freeware packages and to purchase (either in groups or
individually) certain software. Here is a partial list of freeware you will
need for this class. DO NOT download any software to the BCCL laboratory
systems without first consulting the course coordinator.
Detailed Course Syllabus
|
Week |
General Topic Area
|
Details
|
Lab |
|
1 |
§
Administrative matters §
Overview of course material §
Introductory remarks §
Introduction to Computing at VCU |
§
Resources at VCU (VCU IT Pages, Getting Software at VCU, etc.) §
Computing and Operating Systems (Desktop, workstation, server,
Windows, MacOS, Unix, Linux, other; Hardware,
memory, speed, form factors) §
Networking (Ethernet, fiber, switches, latency, hubs, T1/OC3,
backbones, VCU Network and other networks, Grid) §
Programming Languages (C, C++, Fortran, Pascal, Java, Perl, Python,
other) §
Databases/Database Languages (Flat files, folders, directories,
database types, access, MySQL, Sybase, Oracle, etc)
(Daniela) §
Research Methods (Highwire, My Library,
E-journals, etc.) (Tarynn) |
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2 |
§
Statistical Analysis §
Data Mining §
Neural Networks |
§
Introduction to Statistical Packages o
S+, R, SPSS, SAS, EpiInfo o
Applications (Data Mining, Microarray Analysis, Statistical
Analysis, etc.) §
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3 |
§
Statistical Analysis §
Data Mining §
Neural Networks |
§
Introduction to Statistical Packages o
S+, R, SPSS, SAS, EpiInfo o
Applications (Data Mining, Microarray Analysis, Statistical
Analysis, etc.) |
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4 |
§
Image Processing |
§
Image Processing Software (UT Image Tool, IfranView,
R, MatLab, NIH-J, etc) §
Image Formats (Tiff, Gif, etc) §
Applications (Image Processing, Microarray Analysis) |
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5 |
§
“Omic” Analysis 1 |
§
Programs and Protocols for Genomic Analysis (Jeff, Paul Fawcett, §
Programs and Protocols for Proteomic and Protein Sequencing
(Galina, Lambert Ngoka) |
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6 |
§
“Omic” Analysis 2 |
§
Programs and Protocols for Transcriptome
and Metabolome (???) §
Programs for Phylogenetics (Clint Turbeville, Greg Plunkett) |
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7 |
§
“Omic” Analysis 3 |
§
Programs for Population Genetics (Rodney, Bonnie Brown) |
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8 |
§
Molecular Modeling §
Computational Chemistry |
§
Introduction to Molecular Modeling and Computational Chemistry §
Some Sample Programs and What They Can Do |
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9 |
§
Networks and Systems Analysis |
§
Introduction to Network and Systems Analysis (Danail Bonchev) §
Software (Pajek, Path Assist, etc)
(Danail) §
Celllular Automata (Monty)
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10 |
§
Scientific Visualization §
Graphics §
Animation §
Information Presentation |
§
Scientific Data Plots and Data Representation §
Software (SigmaPlot, SAS Graph, IDL,
Origin, etc) §
Scientific Visualization (1)
High Dimensional Data |
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11 |
§
GIS 1 §
Eco-informatics §
Spatial Data Analysis |
§
Introduction to GIS – Components of geographic data, spatial
relationships, map projections, global positioning systems; §
GIS spatial modeling techniques with emphasis on using real-world
datasets to perform database queries, analyses, and presentation of
ecological data |
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12 |
§
GIS 2 §
Eco-informatics §
Spatial Data Analysis |
§
Remote Sensing – An introduction to remote sensing and the
relationship of raster data in GIS. The concepts of change detection,
converting vector data to raster data and virtual GIS will be examined §
Eco-data and Information Exchange – An introduction to information
exchange in the ecological community including ecological metadata and
ecological data management policies and practices |
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13 |
§
GIS 3 §
Eco-informatics §
Spatial Data Analysis |
§
Advanced Materials – Concepts of how ecologists store ecological data
including taxonomic databases, collections databases, and interfacing
ecological databases with the Internet; §
statistical analysis of ecological data including types of software
available and an introduction to data presentation and organization as related
to ecological data; §
use of graphical software to produce publication-ready products |
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14 |
§
Multi-scale and High Performance Computing and
Modeling |
§
Vector and Parallel Computing, Cluster Computing, The Grid and Grid
Computing §
Examples of HPC Modeling §
Software (Maple, Mathematica, etc) |
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15 |
§
Closing Review §
Administrative Matters Final Project Presentations |
(1) Review
of course a) Topics
covered b) Methods
discussed c) Take
home message (2) Course
evaluation (3) Final
project papers due Project presentations |
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