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Courses listed below are divided into two sections:
BCB 444X/544X. Introduction to Bioinformatics
(Fall)
Broad overview of bioinformatics with a significant problem-solving component, including hands-on practice using computational tools to solve a variety of biological problems. Topics include: database searching, sequence alignment, gene prediction, RNA and protein structure prediction, construction of phylogenetic trees, comparative and functional genomics.
BCB 490. Independent Study with BCB Lab (Fall, Spring, Summer)
BCB 538. Computational Genomics & Evolution (Not offered Spring 2009)
Introduction to evolutionary sequence analysis at the genome level. Topics include sequence alignment, phylogenetic inference, molecular clock analysis, ancestral state inference, sequence/structure relation, functional divergence and prediction, evolutionary development, genome duplication, and comparative genomics. Focus will be on data analysis and biological interpretation.
BCB 539. Statistical Methods for Computational Biology (Spring 2010) Advanced discussion about statistical modeling of DNA and amino acid sequences, microarray expression profiles and other genome-wide data.
BCB 542. Introduction to Molecular Biology Techniques (Fall Spring Summer)
Workshops in basic molecular biology techniques and related procedures. Offered on a satisfactory-fail grading basis only. A. DNA Techniques. Includes genetic engineering procedures, sequencing, PCR, and genotyping.
BCB 549. Advanced Algorithms in Computational Biology (Not offered Spring 2009) Design and analysis of algorithms for applications in computational biology, pairwise and multiple sequence alignments, approximation algorithms, string algorithms including in-depth coverage of suffix trees, semi-numerical string algorithms, algorithms for selected problems in fragment assembly, phylogenetic trees and protein folding. No background in biology is assumed. Also useful as an advanced algorithms course in string processing.
BCB 550. Evolutionary Problems for Computational Biologists (Fall - Not offered Fall, 2008)
Discussion and analysis of basic evolutionary principles and the necessary knowledge in Computational Biology to solve "real world" problems. Topics include Character- and distance-based methods, phylogenetic tree distances, and consensus methods, and approaches to extract the necessary information from sequence-databases to build phylogenetic trees.
BCB 551. Computational Techniques for Genome Assembly and Analysis (Fall - Not offered Fall, 2008) (Same as Com S 551) (3-0) Cr. 3. F. Introduction to practical sequence assembly and comparison techniques. Topics include global alignment, local alignment, overlapping alignment, banded alignment, linear-space alignment, word hashing, DNA-protein alignment, DNA-cDNA alignment, comparison of two sets of sequences, construction of contigs, and generation of consensus sequences. Focus on development of sequence assembly and comparison programs.
BCB 565. Professional Practice in the Life Sciences (Spring)
Professional discourse on the ethical and legal issues facing life science researchers. Offered in modular format; each module is four weeks. Modules A and B will be offered in Spring 2007. Grading: A-F A Professional Practices in Research. This 8-hour, 0.5 credit module is designed for students in the life sciences who are considering careers in research. It covers topics such as honesty, objectivity (the impact of self-delusion on experimental design and data interpretation), confidentiality, effective record keeping, plagiarism, authorship practices, and the exchange of research reagents. Real as well as developed case studies are used to help students learn to think critically about ethical dilemmas they will likely face during their professional careers. B Intellectual Property and Industry Interactions. This 8-hour, 0.5 credit module is specifically designed for students in the life sciences interacting with or anticipating interaction with industry. It covers topics such as: why and how universities interact with industry, assistance available for researchers working with industry, and the real meaning of terms such as intellectual property, freedom to operate, and confidentiality. It also covers research contracts and license agreements and how they impact university research. The focus will be on practical information that will help students successfully interact with industry both before and after graduation. C Life Science Ethics. The Life Science Ethics module has been replaced by Philosophy 550X. The one-credit course will be taught spring semester
by Dr. Clark Wolf, Director of the Bioethics Program. It will be offered 5:10 - 6:00 PM on Mondays in 1420 Molecular Biology Building. A description of the
course follows.
BCB 567. Bioinformatics I. (Fundamentals of Genome Informatics) (Fall)
Biology as an information science. Review of algorithms and information processing. Generative models for sequences. String algorithms. Pairwise sequence alignment. Multiple sequence alignment. Searching sequence databases. Genome sequence assembly.
BCB 568. Bioinformatics II. (Advanced Genome Informatics) (Spring)
BCB 569. Bioinformatics III. (Structural Genome Informatics) (Fall) Algorithmic and statistical approaches in structural genomics including protein, DNA and RNA structure. Structure determination, refinement, representation, comparison, visualization, and modeling. Analysis and prediction of protein secondary and tertiary structure, disorder, protein cores and surfaces, protein-protein and protein-nucleic acid interactions, protein localization and function.
BCB 570. Bioinformatics IV. (Computational Functional Genomics
Cross-listed with COM S, GDCB, STAT, CPR E. (3-0) Cr. 3. S. Prereq: BCB 567, Biol 315, Com S 311 and either 208 or 228, Gen 411, Stat 430. Algorithmic and statistical approaches in computational functional genomics and systems biology. Analysis of high throughput gene expression, proteomics, and other datasets obtained using system-wide measurements. Topological analysis, module discovery, and comparative analysis of gene and protein networks. Modeling, analysis, simulation and inference of transcriptional regulatory modules and networks, protein-protein interaction networks, metabolic networks, cells and systems: Dynamic systems, Boolean, and probabilistic models. Ontology-driven, network based, and probabilistic approaches to information integration.
BCB 590. Special Topics (Fall Spring Summer) Summer 2008 offering...
BCB 593. Workshop in Bioinformatics and Computational
Biology
(Not offered Fall 2008) Current topics in bioinformatics and computational biology research. Lectures by off-campus experts. Students read background literature, attend preparatory seminars, attend all lectures, meet with lecturers.
BCB 596. Genomic Data Processing (Fall - not offered Fall 2008)
Cross-listed with COM S, GDCB. (3-0) Cr. 3. F. Prereq: Some knowledge of programming. Study the practical aspects of genomic data processing with an emphasis on hand-on projects. Students will carry out major data processing steps using bioinformatics tools. Topics include base-calling, raw sequence cleaning and contaminant removal; shotgun assembly procedures and EST clustering methods; genome closure strategies and practices; sequence homology search and function prediction; annotation and submission of GenBank reports; and data collection and dissemination through the Internet. Useful post-genomic topics like microarray design and data analysis will also be covered.
BCB 597. Introductory Computational Structural Biology (Spring)
Mathematical and computational approaches to protein structure prediction and determination. Topics include molecular distance geometry, potential energy minimization, and molecular dynamics simulation.
BCB 599. Creative Component (Fall Spring)
BCB 690. Student Seminar in Bioinformatics and Computational Biology (Spring)
BCB 691H. Faculty Seminar in Bioinformatics and Computational Biology (Fall)
Faculty research series.
BCB 697. Graduate Research Rotation (Fall Spring Summer)
Cr. var
Core Course in Molecular Genetics: Gen 511. (Cross-listed with MCDB). (3-0) Cr. 3. S. Prereq: Biol 313 and BBMB 405. The principles of molecular genetics: gene structure and function at the molecular level, including regulation of gene expression, genetic rearrangement, and the organization of genetic information in prokaryotes and eukaryotes. (An equivalent or more advanced course may be substituted with approval of student's POS Committee. Core Courses in Computational Biology: BCB 567. Bioinformatics I (Fundamentals of Genome Informatics). (Cross-listed with COM S, CPR E.) (3-0) Cr. 3. F. Prereq: Com S 208; Com S 330; Stat 341; credit or enrollment in Biol 315, Stat 401, and Stat 432. Potential Instructors: Srinivas Aluru; David Fernandez-Baca; Oliver Eulenstein. Catalog description: Biology as an information science. Review of algorithms and information processing. Generative models for sequences. String algorithms. Pairwise sequence alignment. Multiple sequence alignment. Searching sequence databases. Genome sequence assembly. Expanded description: Biology as an information science. Review of algorithms and information processing: design of algorithms; space and time complexity analysis of algorithms; basic search algorithms; branch and bound search; dynamic programming. Generative models for sequences: multinomial models; Markov models. String algorithms: exact string matching; suffix trees and suffix arrays; approximate string matching (k mismatches, k differences). Pairwise sequence alignment: amino acid substitution scoring matrices; local and global alignment. Multiple sequence alignment: progressive alignment; word-based methods; local multiple alignment (sequence profiles and motifs). Sequence database search: dot matrix methods; heuristic methods; statistics of database searches; Introduction to genome sequence assembly. BCB 568. Bioinformatics II (Advanced Genome Informatics). (Cross-listed with GDCB, STAT, COM S.) (3-0) Cr. 3. S. Prereq: BCB 567, BBMB 301, Biol 315, Stat 401, Stat 432, credit or enrollment in Gen 411. Potential Instructors: Volker Brendel; Karin Dorman; Xun Gu. Catalog description: Advanced sequence models. Basic methods in molecular phylogeny. Hidden Markov models. Genome annotation. DNA and protein motifs. Introduction to gene expression analysis. Expanded description: Applications of sequence models: codon usage; discrete and continuous models of nucleotide substitution; synonymous and nonsynonymous nucleotide substitutions. Basic methods in molecular phylogeny: phylogenetic trees; distance matrix methods; maximum parsimony methods; maximum likelihood methods. Advanced sequence models: Random walks; score-based sequence analysis; Interpolated Markov Models; Markov Random Fields; applications to genome annotation; genome rearrangements. Hidden Markov Models: theory; training; applications to gene structure annotation, sequence alignment, and protein classification. DNA and protein motifs: weight matrices; word-based methods; EM algorithm, Gibbs sampling, and simulated annealing; Bayesian methods. Introduction to gene expression analysis, mRNA and protein expression data analysis, multiple comparisons. BCB 569. Bioinformatics III (Structural Genome Informatics). (Cross-listed with BBMB, COM S, MATH, CPR E.) (3-0) Cr. 3. F. Prereq: BCB 567, Gen 411, Stat 401, Stat 432. Potential Instructors: Bob Jernigan, Guang Song, Zhijun Wu Catalog description: Algorithmic and statistical approaches in structural genomics including protein, DNA and RNA structure. Structure determination, refinement, representation, comparison, visualization, and modeling. Analysis and prediction of protein secondary and tertiary structure, disorder, protein cores and surfaces, protein-protein and protein-nucleic acid interactions, protein localization and function. Expanded description: Algorithmic and statistical approaches in structural genomics including: Protein, DNA and RNA structure; Protein and Nucleic acid databases; Computational problems in structure determination including structure representation, transformation between coordinate systems, structure comparison (using RMS and distance matrix based methods) and visualization, structure determination with NMR derived distances, Distance-based structure modeling, energy minimization methods for structure refinement, protein structure modeling using threading and homology based methods. Analysis and prediction of protein secondary structure and tertiary structure, ordered and disordered regions, structural domains, 3-dimensional structural motifs, protein cores and surfaces, structural classes, protein function from primary, secondary, or tertiary structure, protein-protein, protein-RNA and protein-DNA interfaces; analysis and prediction of RNA structure. BCB 570. Bioinformatics IV (Computational Functional Genomics and Systems Biology). (Cross-listed with COM S, GDCB, STAT, CPR E.) (3-0) Cr. 3. S. Prereq: BCB 567, Biol 315, Com S 363, Gen 411, Stat 401, Stat 432. Potential Instructors: Julie Dickerson, Vasant Honavar, Karin Dorman, Steve Proulx Catalog description: Algorithmic and statistical approaches in computational functional genomics and systems biology. Biological Information Integration – knowledge (ontology) driven and statistical approaches. Qualitative, probabilistic, and dynamic network models. Modeling, analysis, simulation and inference of transcriptional regulatory modules and networks, protein-protein interaction networks. Metabolic networks; cells and systems. Recommended (not required) Courses It is recommended that all BCB graduate students who have not had laboratory experience in biological sciences take at least two 1-credit modules of BCB 542 (Introduction to Molecular Biology Techniques). Similarly, BCB graduate students who come in with a biology undergraduate degree take at least two modules of Introduction to Bioinformatics Tools (including modules on Sequence Analysis, Microarray Data Analysis, Protein Structure Analysis, Phylogenetics etc. to be developed and offered by the Baker Center). Prior to Fall, 2006, the below courses were identified as courses which fulfilled Advanced Group Requirements. Students entering Fall 2006 and later may now select appropriate electives to fulfill BCB course requirements in consultation with their POS Committee who oversee their degree program. Animal Science
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