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BIET 369: Philosophy of Medicine
3.00 Credits
Loyola University Chicago
The culture and practice of medicine raises many philosophical issues which are not confined to medical ethics. This course explores (1) the ¿epistemology¿ of medicine, (2) the notion of ¿professionalism,¿ (3) issues of medical technology, and (4) the goals of medicine.
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BIET 369 - Philosophy of Medicine
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BIET 393: Seminar:
3.00 Credits
Loyola University Chicago
See THEO 393
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BIET 393 - Seminar:
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BIET 395: Special Topics
3.00 Credits
Loyola University Chicago
This interdisciplinary team-taught course examines a topic in bioethics from both scientific and ethical points of view. Topics may include: biotechnologies, concepts of race and gender, the environment, reproduction, and others. Outcomes: Students will be able to understand the relevant scientific concepts, techniques, and methods, recognize ethical issues raised by the topic, and use ethical reasoning and ethical judgement (concepts, theories, methods) to discuss the topic.
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BIET 395 - Special Topics
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BIET 398: Seminar in Contemporary Philosophy
3.00 Credits
Loyola University Chicago
See PHIL 393
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BIET 398 - Seminar in Contemporary Philosophy
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BIOI 300: Directed Readings
1.00 - 3.00 Credits
Loyola University Chicago
Readings from the scientific literature in any focused area of bioinformatics agreed upon by the student and the supervising faculty member. Outcome: Students will gain knowledge, journal reading expertise, and scientific writing skills.
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BIOI 300 - Directed Readings
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BIOI 337: Quantitative Methods in Bioinformatics
4.00 Credits
Loyola University Chicago
Prerequisite: STAT 203 or 335 This course develops the mathematical and statistical methods necessary to analyze and interpret genomic and proteomic data, including signal analysis, sequence alignment methods, data-base search methods useful in bioinformatics and data mining. Outcome: Students will obtain the quantitative skills used in BLAST, including inference, stochastic processes and hidden Markov models, random walks, microarray analysis and biological sequence analysis.
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BIOI 337 - Quantitative Methods in Bioinformatics
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BIOI 353: Database Programming
3.00 Credits
Loyola University Chicago
Prerequisite: COMP 271 This course introduces relational and object databases to support database creation and application development. Use of commercial database products will give a practical orientation. Outcome: Students will learn SQL, database design and application development using the latest software tools. Students will also learn techniques for web based data retrieval and manipulation.
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BIOI 353 - Database Programming
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BIOI 363: Desgn and Analysis Computer Algorithms
3.00 Credits
Loyola University Chicago
Prerequisites: Comp 163 & Comp 271 and (Math 131 or Math 161) Theoretical design and analysis of computer algorithms may be supplemented by small amounts of programming. Outcome: The ability to design and analyze efficient algorithms; understanding of the necessary models and mathematical tools; understanding of a variety of useful data structures and fundamental algorithms; exposure to the classification of computational problems into different complexity classes.
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BIOI 363 - Desgn and Analysis Computer Algorithms
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BIOI 366: Biochemistry
3.00 Credits
Loyola University Chicago
An introduction to biochemical principles as they relate to major biological themes such as the relationship between cellular structure and function, metabolism, thermodynamics, regulation, information, pathways, and evolution. Outcome: Students will study the basic concepts of biochemistry and will understand how thermodynamics govern biochemical processes. Catalytic strategies, as well as the major pathways of both anabolism and catabolism, will also be learned.
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BIOI 366 - Biochemistry
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BIOI 383: Computational Biology
3.00 Credits
Loyola University Chicago
Prerequisite: Biol 388, Comp 163, and Comp 271. This course presents an algorithmic focus to problems in computational biology. It is built on earlier courses on algorithms and bioinformatics. Problems and solutions covered in this course include gene hunting, sequence comparison, multiple alignment, gene prediction, trees and sequences, databases, and rapid sequence analysis. Outcome: Students will learn, in detail, foundational methods and algorithms in bioinformatics.
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BIOI 383 - Computational Biology
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