Bioinformatics I
/ PHARM 201
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Overview
Bioinformatics is driven by the need to understand complex biological systems for which data are accumulating at exponential or near exponential rates. Such an understanding relies of the effective representation of these data and the ability to analyze these data. This is a broad topic and we focus on macromolecular structure data, which is suitably complex, to introduce the principles of formal data representation, reductionism, comparison, classification, visualization and biological inference. As such the course also serves as an introduction to Structural Bioinformatics. Assessment
Weekly assignments: On Friday of each week students will receive a question paper on that weeks work which will be due 5pm the following Wed. in class. (50%). Final Exam: Students will be assigned one or more papers which cover a significant amount of the material covered in the course. They will be expected to critique that paper based on what they have learned and propose the next set of experiments (50%). Course Text
Jenny Gu & Philip.Bourne (Eds.) Structural Bioinformatics Second Edition. Wiley 2009 [from Google Books] The text is available for use in our Lab. Library 2011 Skaggs. Printed copies of the slides in notes form will be distributed with each lecture. Schedule
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Topic & Date |
Content |
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Workflow Overview of Course [slides] |
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Lecture 1: 09/30 Know Your Data - Principles of Protein Structure [slides] |
To model and analyze biological data it must first be
understood from a biological perspective. Goal: Refresh or achieve a better understanding of primary,
secondary, tertiary and quaternary protein structure. |
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Lecture 2: 10/02 Know Your Data -Principles of DNA and RNA structure [slides] |
To model and analyze biological data it must first be
understood from a biological perspective. Goal: Refresh or achieve a better understanding of the features
of DNA and RNA structure and its interaction with proteins. |
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Lecture 3:
10/07 Know the Limitations of Your Data - Experimental Methods of Structure Determination [slides] |
To effectively utilize biological data it is necessary to
understand the limitations of the experiments used to determine that data.
Structure determination is a relatively quantitative science and good
statistical measures exist. Goal:
Explore the quantitative and qualitative measures of data quality with
respect to data from X-ray crystallography, NMR and electron microscopy. [Podcast] |
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Lecture 4: 10/09 Know How Best to Represent Your Data - Data Representation [slides] |
Historically the PDB format expresses the Lingua Franca of structural
bioinformatics, but it has serious flaws. These will be explored and
understood in the context of the replacement - mmCIF.
Goal: To understand why good data
representation is important. |
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Lecture 5: 10/14 Data Representation and the PDB [slides] |
How is this data representation
used by the PDB is the question addressed in this lecture. Guest lecturers Drs Peter Rose and
Andreas Prlic. [Podcast] |
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Lecture 6: 10/16 Alternative Forms of
Representation [slides] |
Most protein structure analysis is based upon the
Cartesian atomic coordinates, but there are other forms of representation. We
will consider a representation based on spherical harmonics and how it can be
applied. Guest Lecturer: Dr. Apostol Gramada. [podcast] [Assignment 3] |
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Lecture 7: 10/21 Data Quality: The Annotation and Validation Process [slides] |
Public databases provide rich sources of data for all
aspects of bioinformatics study. Goal:
To understand the quality of these data through annotation and validation
practices using PDB and SwissProt as examples. |
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Lecture 8: 10/23 More on Data Representation – The Gene Ontology [slides] |
While a slight digression from structural bioinformatics, the Gene Ontology (GO) is having a profound impact on bioinformatics research. Goal: To understand the structure and use of GO. Reading: Creating the Gene Ontology Resource: Design and Implementation Genome Research (2001) 11:1425-1433 [podcast] |
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Lecture 09: 10/28 Sequence-Structure-Function Relationships and Associated Reductionism [slides] |
With so much data available it is necessary to produce non-redundant sets for many bioinformatics tasks. However, given the complex relationship between sequence, structure and function, non-redundancy means different things in each case. Goal: Understand this complex relationship and the associated meaning of reductionism. Reading: Chapter 21 [podcast] |
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Lecture 10: 11/03 Reductionism and Classification Require Detailed Comparison [slides] |
3D structure comparison is a difficult problem when trying
to achieve biologically meaning results. Goal:
Understand the problem and the methods used to address it and explore the use
of the distant sequence alignments arising from structure alignment. Reading: Chapter 16. [podcast] |
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Lecture 11: 11/06 [slides] |
Structural Immunology Lecturer: Dr. Julia Ponomarenko [podcast] |
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Lecture 12: 11/10 From Reductionism comes New
Science [slides] |
New Science – traditionally protein structure has been studied through looking at evolution. Most recently evolution has been studied through looking at protein structure. Goal: Provide an appreciation of what protein structure brings to the study of evolution. |
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Lecture 13: 11/13 Saving the Tree of Life [slides] |
Continuing our theme of usuing structure to study evolution we explore the arguments for an against the Tree of Life. Lecturer: Ruben Valas |
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Lecture 14: 11/18 Classification is Always Ambiguous – An Exception to the Rule? [slides] |
Secondary structure assignment may be an exception to the rule. Goal: To explore the Kabsch-Sander algorithm and the impact it has had on the community. Also to explore other methods of secondary structure assignment. Reading: Chapter 19. [podcast] |
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Lecture 15: 11/20 Studying Protein-Ligand Interactions [slides] |
One specific methodology for describing and searching for protein-ligand binding sites will be described along with how it is being used to study side effects and repositioning of existing pharmaceuticals. [Assignment 8] [Podcast] |
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Lecture 16: 11/25 Molecular visualization
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Discussion about the history of molecular visualization and a comparison of various tools.[Podcast] |
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Lecture 17 12/2: Protein-protein interactions [slides] |
Goal: Understand the importance of the study of protein-protein interactions at the structural level. Consider one method in detail. [Podcast] |
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Lecture 18: 12/4 Future Challenges [slides] |
Discussion of some of the outstanding problems in bioinformatics and biomedical informatics Guest Lecturer: Lucila Ohno-Mechado [Podcast] |
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Finals 12/7-12 |
[Final] |