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BIOL/CMSI 367-01/HNRS 398-05: Biological Databases

This is the home page for the Fall 2010 Biological Databases course at Loyola Marymount University while the computer science server is down.

You may also want to visit the Dahlquist Lab pages or the Spring 2010 Bioinformatics Lab course pages while you are here.

Week 7 In-class Exercise and Journal Assignment

Background Readings

  1. Brown PO and Botstein D. Exploring the new world of the genome with DNA microarrays. Nat Genet. 1999 Jan;21(1 Suppl):33-7. DOI:10.1038/4462 | PubMed ID:9915498 | HubMed [Paper1]
  2. Chapter 4 of Campbell & Heyer, Discovering Genomics, Proteomics, and Bioinformatics. Available on MyLMUConnect under the "Information" section.


Overview of Microarray Data Analysis

The slides shown in class on 10/12/10 can be found on the MyLMUConnect site under "Information".

This is a list of steps required to analyze DNA microarray data.

  1. Quantitate the fluorescence signal in each spot in the microarray image.
    • Typically performed by the scanner software, although third party software packages do exist.
    • The image of the microarray slide and this quantitation are considered the "raw-est" form of the data.
    • Ideally, this type of raw data would be made publicly available upon publication.
    • In practice, the image data is usually not made available because the raw image file of one slide could be up to 100 MB in size.
    • Also, some journals do not require data deposition as a requirement for publication, so often published data are not actually available anywhere for download.
    • Microarray data is not centrally located in a single database. Some major sources are:
  2. Calculate the ratio of red/green fluorescence
  3. Log2 transform the ratios
  4. Normalize the log ratios on each microarray slide
  5. Normalize the log ratios for a set of slides in an experiment
  6. Perform statistical analysis on the log ratios
  7. Compare individual genes with known data
  8. Look for patterns (expression profiles) in the data (many programs are available to do this; we won't be doing this in class)
  9. Perform Gene Ontology term enrichment analysis (we will use MAPPFinder for this)
  10. Map onto biological pathways (we will use GenMAPP for this)

Analysis of Vibrio cholerae Microarray Data

  • For the next section of the course, you will be introduced to the process we will use for the final projects in the course in a series of in-class and journal assignments where we will first analyze microarray data from Vibrio cholerae, and then learn how to create a Gene Database for this organism.
  • The detailed instructions for the microarray data analysis we will carry out can be found on the Sample Microarray Analysis for Vibrio cholerae page.

Individual Journal Assignment

This journal entry is due on Monday, October 18 at midnight PDT (Sunday night/Monday morning). NOTE that the OpenWetware server records the time as Eastern Daylight Time (EDT), unlike the LMU CS server which was on Greenwich Mean Time (GMT). Therefore, midnight will register as 03:00.

  • Store this journal entry as "username Week 7" (i.e., this is the text to place between the square brackets when you link to this page).
  • Create the following set of links.
    • Link to your journal entry from your user page.
    • Link back from your journal entry to your user page.
    • Link to this assignment from your journal entry.
    • Add the "BIOL367/F10" category to the end of your wiki page.
  • Keep an "electronic lab notebook, containing your methods, results, and interpretations of this week's portion of the Analysis of Vibrio cholerae microarray data project in your "username Week 7" journal page. Although you will have assigned partner(s), you will need to fill out your own individual journal page.

Preparation for Next Week's Journal Club

In preparation for the Journal Club, each individual will do the following assignment on their individual "username Week 7" pages.

  1. Make a list of at least 10 biological terms for which you did not know the definitions when you first read the article. Define each of the terms. You can use the glossary in any molecular biology, cell biology, or genetics text book as a source for definitions, or you can use one of many available online biological dictionaries. Cite your sources for the definitions by providing the proper citation (for a book) or the URL to the page with the definition for online sources.
  2. Write an outline of the article. The length should be the equivalent of 2 pages of standard 8 1/2 by 11 inch paper. Your outline can be in any form you choose, but you should utilize the wiki syntax of headers and either numbered or bulleted lists to create it. The text of the outline does not have to be complete sentences, but it should answer the questions listed below and have enough information so that others can follow it. However, your outline should be in YOUR OWN WORDS, not copied straight from the article.
    • What is the main result presented in this paper? (Hint: look at the last sentence of the introduction and restate it in plain English.)
    • What is the importance or significance of this work?
    • What were the limitations in previous studies that led them to perform this work?
    • What were the methods used in the study?
    • Briefly state the result shown in each of the figures and tables.
    • How do the results of this study compare to the results of previous studies (See Discussion).
  3. Upload your completed PowerPoint slides to your journal page by the Week 7 journal deadline (you may make changes before your presentation Tuesday afternoon, but we will be evaluating the presentation you upload.)
    • For your PowerPoint presentation, you need to show each of the figures and tables in your article as part of your presentation. Do not have a separate section of your presentation for Methods. Instead, show each of the results (figures/tables) and just explain the methods used to obtain those results on that slide.
    • The length of your presentation should be about 15 minutes.

Journal Club Articles

  1. Salomonis N, Hanspers K, Zambon AC, Vranizan K, Lawlor SC, Dahlquist KD, Doniger SW, Stuart J, Conklin BR, and Pico AR. GenMAPP 2: new features and resources for pathway analysis. BMC Bioinformatics. 2007 Jun 24;8:217. DOI:10.1186/1471-2105-8-217 | PubMed ID:17588266 | HubMed [Paper1]
  2. Doniger SW, Salomonis N, Dahlquist KD, Vranizan K, Lawlor SC, and Conklin BR. MAPPFinder: using Gene Ontology and GenMAPP to create a global gene-expression profile from microarray data. Genome Biol. 2003;4(1):R7. PubMed ID:12540299 | HubMed [Paper2]
  3. Heidelberg JF, Eisen JA, Nelson WC, Clayton RA, Gwinn ML, Dodson RJ, Haft DH, Hickey EK, Peterson JD, Umayam L, Gill SR, Nelson KE, Read TD, Tettelin H, Richardson D, Ermolaeva MD, Vamathevan J, Bass S, Qin H, Dragoi I, Sellers P, McDonald L, Utterback T, Fleishmann RD, Nierman WC, White O, Salzberg SL, Smith HO, Colwell RR, Mekalanos JJ, Venter JC, and Fraser CM. DNA sequence of both chromosomes of the cholera pathogen Vibrio cholerae. Nature. 2000 Aug 3;406(6795):477-83. DOI:10.1038/35020000 | PubMed ID:10952301 | HubMed [Paper3]
  4. Merrell DS, Butler SM, Qadri F, Dolganov NA, Alam A, Cohen MB, Calderwood SB, Schoolnik GK, and Camilli A. Host-induced epidemic spread of the cholera bacterium. Nature. 2002 Jun 6;417(6889):642-5. DOI:10.1038/nature00778 | PubMed ID:12050664 | HubMed [Paper4]

All Medline abstracts: PubMed | HubMed


  • Rich Brous, Andrew Herman, Jennifer Okonta
  • Claudia Campos, Salomon Garcia, Theresa Graebner
  • Margie Doyle, Andrew Forney
  • Evan Montz, Zeb Russo

Shared Journal Assignment

  • Store your journal entry in the shared BIOL367/F10:Class Journal Week 7 page. If this page does not exist yet, go ahead and create it.
  • Link to the shared journal entry from your user page.
  • Link the shared journal page to this assignment page.
  • Sign your portion of the journal with the standard wiki signature shortcut (~~~~).
  • Add the "BIOL367/F10" category to the end of the wiki page (if someone has not already done so).


  • How do you think biotechnology like whole genome sequencing and microarrays will affect your future?
    • How will it affect your career?
    • How will it affect your personal life?
    • What pitfalls can you forsee and how would you suggest avoiding them?
  • Please feel free to respond or comment on your classmates' reflections.