Bioinformatics is an exciting field which marries biology, computer science and information technologies. A bioinformaticist is an individual who has the skills of a biotechnologist and the ability to apply computer technologies to address biological problems. While the name bioinformatics is somewhat new, the field has been around since the early days of biotechnology and as developed along with advances in computer hardware and software.
This 2 credit course is intended to provide an overview of Bioinformatics for those who are either curious about what this exciting field entails or about whether bioinformatics represents a sound career path. Pursuant to this goal we will touch upon many subjects but will not explore any one in particular detail. Nevertheless I welcome suggestions from anyone regarding projects you may want to pursue outside of class in order to gain a deeper understanding of any aspect of bioinformatics that you find of personal interest.
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Bioinformatics
Bioinformatics will introduce students to the analysis of genetic sequences. Emphasis will be placed on genetic information derived from the human genome project but findings from genomes of other model systems will be presented. Lectures will discuss available computational tools for extracting biological information from nucleotide and protein sequences. The computer-based laboratory will utilize bioinformatics software to demonstrate how to manage, search and analyze genetic sequences. Laboratory sessions will cover gene prediction programs, DNA fragment assembly, multiple sequence analysis, secondary structure predictions, phylogenetic constructions and web-access to public databases.
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Genomics
Genomics will introduce students to the analysis of complex genomes. Emphasis will be on genetic information derived from the human genome project, but advances with genomes of other model systems will be discussed. Lectures will cover scientific techniques used to map and sequence the human genome as well as strategies for identification of disease susceptibility genes. The wet-bench laboratory will utilize an automated DNA sequencer to demonstrate the acquisition of genetic sequences. Laboratory sessions will emphasize cycle sequencing of cloned DNA fragments using an automated fluorescent DNA sequencer and mapping tactics using radiation hybrid cell panels.
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Introduction to Bioinformatics Computing
This course will focus on the Computer Science/Information Technology aspects of Bioinformatics. Students will learn about the algorithms and performance issues related to computational genomics in a theoretical and practical (lab-based) study of computational genomics. This is the first of two courses covering the advanced algorithms used in the field of Bioinformatics. Algorithm development, performance analysis, and techniques for proving correctness are emphasized. This course will be listed as both an undergraduate and a graduate course. Undergraduates will be enrolled in sections designed for them. Graduate students, either in the traditional 2 year MS program or those in the 4+1 program, will be taught in separate sections which will include discussions of the primary scientific literature and an assigned project designed to integrate salient principles in each course.
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Advanced Bioinformatics Computing
Students will build on their experiences in Introduction to Bioinformatics Computing and learn about advanced issues in bioinformatics and computational genomics. This course will provide an in-depth exposure to advanced techniques in computational genomics.
The significant growth of biomolecular data has created demand for the use and development of new techniques for extracting "knowledge" from the data. This course will explore several established and new computational approaches to data mining and present these techniques in the specific context of biomolecular data. This course will be listed as both an undergraduate and a graduate course. Undergraduates will be enrolled in sections designed for them. Graduate students, either in the traditional 2 year MS program or those in the 4+1 program, will be taught in separate sections which will include discussions of the primary scientific literature and an assigned project designed to integrate salient principles in each course.
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High Performance Computing for Bioinformatics
Bioinformaticists are starting to use parallel and distributed computing solutions to solve computationally challenging problems. The purpose of this course is to introduce parallel and distributing computing so that students can; understand the basics of this technology, determine the type of high-performance hardware and software that would be required in their work, effectively evaluate commercially available hardware and software systems, and be able to use and develop software that takes advantage of high-performance systems. This course will be listed as both an undergraduate and a graduate course. Undergraduates will be enrolled in sections designed for them. Graduate students, either in the traditional 2 year MS program or those in the 4+1 program, will be taught in separate sections which will include discussions of the primary scientific literature and an assigned project designed to integrate salient principles in each course.
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Molecular Modeling and Proteomics
The course will explore two facets of protein molecules: their structure and their expression. The structure component will build upon information from the Bioinformatics course and will add further sophistication with analysis of inter-molecular interactions and ligand/receptor pairing. Software that permits molecular docking experiments will be employed. Tissue-specific protein expression will be addressed in lectures with description of micro-array technology and, in the laboratory, with two-dimensional protein gel electrophoresis. Provide an advanced course in modeling of DNA and protein structures, and their interactions. Enable students to computationally construct small ligands for biologically important molecules. Also, introduce the students to the newly emerging field of proteomes: study of expressed gene products. This course will be listed as both an undergraduate and a graduate course. Undergraduates will be enrolled in sections designed for them. Graduate students, either in the traditional 2 year MS program or those in the 4+1 program, will be taught in separate sections which will include discussions of the primary scientific literature and an assigned project designed to integrate salient principles in each course.
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Cell and Molecular Genetics I
This course will introduce cellular and molecular biology to graduates students with limited background in the biological sciences. The text book adopted was developed with the inexperience, fledgling biologist in mind. The approach to be taken entails the use of empirical data to support the basic concepts presented so that upon completion of this course students will not only be familiar with cellular and molecular biology but will also be acquainted with modern laboratory techniques.
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Cell and Molecular Genetics II
This course will introduce cellular and molecular biology to graduates students with limited background in the biological sciences. The text book adopted was developed with the inexperience, fledgling biologist in mind. The approach to be taken entails the use of empirical data to support the basic concepts presented so that upon completion of this course students will not only be familiar with cellular and molecular biology but will also be acquainted with modern laboratory techniques.
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Bioinformatics Seminar
Sufficient opportunities will be afforded for students and faculty to interact while discussing current trends and developments in bioinformatics. Material for this course will be drawn from the current scientific literature including, but not limited to, journals such as Bioinformatics, Genome Research, and the Journal of Computational Biology, among others.
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Ethics in Bioinformatics
The objectives of this course are to expose students to the ethical issues associated with bioinformatics research and the application of bioinformatics to product development and commercialization. This course will be presented in a seminar format in order to engender and facilitate discussion, among faculty and students, of the issues presented.
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MS Thesis
This course represents the capstone experience for students in our Bioinformatics MS program. It will give them an opportunity to synthesize the information learned through the other courses they have taken during their graduate studies. Additionally, the experience gained through this course will provide the student with experience managing a project, engaging in effective oral and written communications and prepare the student to better compete and thrive in the job market.
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Statistical Analysis for Bioinformatics
An introduction to the probabilistic models and statistical techniques used in computational molecular biology. Probabilistic and/or statistical techniques will be presented which are needed for the understanding of pairwise and multiple sequence alignment methods, gene and protein classification methods, and phylogenetic tree construction.
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