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 CSE 590 CB, Autumn 1999
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 Course Info  

Reading and Research in Computational Biology
Wednesdays, 3:30-5:00, 219 Loew

CSE 590 CB is an informal weekly seminar in Computational Biology, open to all graduate students in the computer, biological, and mathematical sciences.
Instructors:  Ruzzo, Tompa
Credit: 1-3 Variable
Grading: Credit/No Credit. Talk to us if you're unsure of our expectations, registrar-wise.
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 Preliminary  Schedule
Date Topic Presenters/Participants Papers/Slides
9/29 Organizational Meeting   
10/06 Splicing Dan, Jed, Ken, Monika; Larry Slides
10/13 Secondary Structure Jeremy, Mathieu, Zasha; Martin  
10/20 Melting & Primers Amy, Isaac, Keunwoo; Benno Papers  Keunwoo's PCR slides 
10/27 Discussion of Splicing Don, Justin, and everybody; Larry Slides
11/3 Guest Speaker David Goodlett  
11/10 Array Applications Tammy, Ka Yee; Rimli Papers 
11/17 DNA Arrays for High Resolution HLA Typing Guest Speaker: Zhen Guo, MBT & FHCRC Abstract & Papers
11/24 Deducing Network Dynamics from Node Activity Traces Guest Speaker: Brendan Mumey, MSU Abstract
12/1 Discussion of Array Design    
12/8 No Meeting??    

 Papers, etc.

10/20:  Primers and Melting

We are planning to discuss three papers. The references are listed below, and papers 2. and 3. are linked as PDF files. If you haven't received a copy of 1. in the last sessions, please feel free to request a PostScript file from Benno.

The first two papers are about the primer design problem that, among other places, occurs in the revolutionary lab technique that has transformed molecular biology in the middle of the previous decade, the polymerase chain reaction (PCR). At the end of this decade, a similarly revolutionary technique is maturing rapidly: DNA microarrays, on which we are planning to spend some more time on in subsequent meetings. We will present the basics of both techniques. For both, secondary structure and the estimation of melting temperature are crucially important topics. We are going to discuss two practical methods for primer design and a method for estimating energy parameters/melting temperatures.

Web links:

References:

  1. Rychlik, W. and Rhoads, R.E., 1989, Computer program for choosing optimal oligonucleotides for filter hybridization, sequencing and in vitro amplification of DNA, Nucl. Acids Res. 17(21), 8543-8551
  2. Haas, S., Vingron, M., Poustka, A. and Wiemann, S., Primer design for large scale sequencing, Nucl. Acids Res. 26(12), 3006-3012.
  3. Peyret, N., Seneviratne, P.A., Allawi, H.T. and SantaLucia, JJr., 1999, Nearest-Neighbor Thermodynamics and NMR of DNA Sequences with Internal A-A, C-C, G-G, and T-T Mismatches, Biochemistry 38, 3468-3477.


11/10:  DNA Microarray Applications

I. Introduction: What are these arrays? (Tammy Williams)

  1. P. O. Brown, D. Botstein, "Exploring the new world of the genome with DNA microarrays", Nature Genetics Supplement, 21:33-37, 1999. [pdf]
  2. R. L. Lipshutz, S. P. A. Fodor, T. R. Gingeras, D. J. Lockhart, "High density synthetic oligonucleotide arrays", Nat. Gen. 21:20-24, 1999. [pdf]
  3. E. Southern, K. Mir, M. Shchepinov, "Molecular interactions on microarrays", Nat. Gen. 21:5-9, 1999. [pdf]
  4. E. S. Lander, "Array of hope", Nat. Gen. 21:3-4, 1999. [pdf]
  5. D. J. Duggan et al. "Expression profiling using cDNA microarrays", Nat. Gen. 21:10-14, 1999. [pdf]
  6. V. C. Cheung et al. "Making and reading microarrays", Nat. Gen. 21:15-19, 1999. [pdf]

II. Array Applications part I: Clustering and Motif Finding (Emily Rocke)

  1. T. J. Aitman et al. "Identification of Cd36 (Fat) as an insulin-resistance gene causing defective fatty acid and glucose metabolism in hypertensive rats", Nat. Gen. 21:76-83, 1999. [pdf]
  2. S. Tavazoie et al. "Systematic determination of genetic network architecture", Nat. Gen. 22:281-285, 1999. [pdf]
  3. X. Wen, S. Fuhrman et al. "Large-scale temporal gene expression mapping of central nervous system development", PNAS 95:334-339, 1998. [pdf]
  4. S. Chu, J. DeRisi, et al. "The transcriptional program of sporulation in budding yeast", Science 282:699-705, Oct. 1998.
  5. Chen, Y., Dougherty, E., Bittner, M., "Ratio-Based Decisions and the Quantitative Analysis of cDNA Microarray Images," J. Biomed. Optics 2(4), 364-374, Oct. 1997.

III. Array Applications part II: Cancer Classification (KaYee Yeung)

  1. T. R. Golub, D. K. Slonim et al. "Molecular classification of cancer: class discovery and class prediction by gene expression monitoring", Science 286:531-537, Oct. 1999.
    [This was also supplemented with a tech report on related material, with more algorithmic details, reachable here.]


11/17:  DNA Arrays for High Resolution HLA Typing

Overview

Zhen Guo will be the next speaker in our 590CB seminar, his talk describing his research on an oligonucleotide array system for genotyping the human leukocyte antigen (HLA) complex of genes. This group of genes plays an important role in our immune system, and therefore in many medical applications. You can find a little background on the HLA (or "MHC") complex under http://www.britannica.com/bcom/eb/article/xref/0,5716,16530,00.html
          --- Benno

Abstract: DNA Arrays for High Resolution HLA Typing

Zhen Guo, Ph.D
Department of Molecular Biotechnology University of Washington &
Division of Clinical Research, Fred Hutchinson Cancer Research Center

The HLA genes are among the most polymorphic genes known in the human genome. Genes in HLA regions encode proteins that are critical in controlling T-cell recognition and determining histocompatibility in bone marrow transplantation procedure. The methodology and applications of DNA array technology in HLA tissue typing will be reviewed. An oligonucleotide array system for high-resolution typing of classical HLA alleles will be described. Applications of PCR arrays in HLA polymorphism study will be evaluated. Important issues in array technology, such as DNA surface density, hybridization kinetics, mismatch discrimination, will be discussed.

References

  1. Dawkins, R., C. Leelayuwat, S. Gaudieri, G. Tay, J. Hui, S. Cattley, P. Martinez and J. Kulski (1999) Genomics of the Major Histocompatibility Complex: Haplotypes, Duplication, Retroviruses and Disease. Immunological Reviews 167: 275-304
  2. Guo, Z, R.A. Guilfoyle, A. Thiel, R. Wang and L. Smith (1994) Direct Fluorescence Analysis of Genetic Polymorphisms by Hybridization with Oligonucleotide Arrays on Glass Support. Nucleic Acids Research 22:5456-5465.
  3. Guo, Z., Q. Liu and L. Smith. (1995) Enhanced Discrimination of Single Nucleotide Polymorphisms by Artificial Mismatch Hybridization. Nature Biotechnology 15:331-335.


11/24:  Deducing Network Dynamics from Node Activity Traces

Prof. Brendan Mumey
Department of Computer Science
Montana State University

In this talk I will describe an approach to detect and represent important aspects of the dynamics of networks. We have two principal areas of application in mind. Interest in the problem of discovering and representing the important aspects of the dynamics of gene regulatory networks has elevated in the last several years due to the ability to collect large quantities of gene expression data using DNA microarrays. A problem from neurobiology that bears a surprising amount of resemblance is that of detecting information coding and flow in a sensory neural system from neural activity trace data. We describe both problems and how our core methodology is adapted to deal with each. An important feature of our approach is that it permits the modeling of feedback loops.

Joint work with Tomas Gedeon, Dept. of Mathematics, Montana State University


 Resources CSE 590 CB, Spring, 1999.
CSE 590 CB, Winter, 1999.
CSE 590 CB, Autumn, 1998.
Lecture notes from the two offerings of CSE 590 BI (Computational Biology).


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