Evan Montz Week 7

10 Biological Term Definitions

1. Gene expression- The process by which the inheritable information in a gene, such as the DNA sequence, is made into a functional gene product, such as protein or RNA.

http://en.mimi.hu/biology/gene_expression.html

2. Morphogenesis- Differentiation of cells and tissues in the early embryo which resultsin establishing the form and structure of the various organs and parts of the body.

http://medical-dictionary.thefreedictionary.com/morphogenesis

3. Hexokinase- Any group of enzymes that accelerate the phosphorylation of hexoses (as in the formation of glucose-6-phosphate from glucose and ATP) in carbohydrate metabolism.

http://www.merriam-webster.com/medical/hexokinase

4. Directed acyclic graph- A directed graph with no path that starts and ends at the same vertex.

http://xw2k.nist.gov/dads//HTML/directAcycGraph.html

5. Ontology- A branch of metaphysics concerned with the nature and relations of being.

http://www.merriam-webster.com/dictionary/ontology

6. Spliceosome- A ribonucleoprotein complex that is the site in the cell nucleus where introns are excised from precursor messenger RNA and exons are joined together to form functional messenger RNA.

http://www.merriam-webster.com/medical/spliceosome?show=0&t=1287369260

7. Mitotic cell cycle- A mitotic cell cycle is one which canonically comprises four successive phases and includes replication of the genome and the subsequent segregation of chromosomes into daughter cells.

http://www.yeastgenome.org/cgi-bin/GO/goTerm.pl?goid=0000080

8. Protein biosynthesis- The process in which cells build proteins.

http://www.wordiq.com/definition/Protein_biosynthesis

9. TGFβ signaling- the prototype of a large family of secreted peptide growth factors in metazoans.

http://www.wormbook.org/chapters/www_tgfbsignal/tgfbsignal.html

10. Glycolysis- the catabolism of carbohydrates, as glucose and glycogen, by enzymes, with the release of energy and the production of lactic or pyruvic acid.

http://dictionary.reference.com/browse/glycolysis

Outline: MAPPFinder: using Gene Ontology and GenMAPP to create a global gene-expression profile from microarray data

• Outline
  • MAPPFinder is a tool that has the capability of organizing genes according to their GO identification and is able to compare to other GO terms
    • MAPPFinder integrates the Gene Ontology (GO) Project with GenMAPP
    • Capable of comparing an experimental GO term to a control term
    • Rapidly Generates a graphical representation of thousands of genes in their representative pathways as well as how they are regulated
  • No tool prior to MAPPFinder could link gene term expression data to the Gene Ontology hierarchy.
    • MAPPFinder can be effectively used in combination with GenMAPP, a gene pathway profiler
    • It was determined that pathway profiling should be an automated process in order to quickly explore all possible pathways.
    • GenMAPP currently utilizes 50 MAPPs (Microarray Pathway Profiles)
      • This is insufficient to manage all species
    • MAPPFinder was created in order to interconnect the GenMAPP and GO Project and to quickly compare their contents and to utilize the information provided by both sources
  • The GO consortium consists of a created list of formal biological definitions
    • Definitions include biological processes, cellular components, and molecular functions
    • MAPPFinder calculates percentage of genes measured that match the criterion of the user.
    • Using this percentage in conjunctions with a z-score, MAPPFinder can rank the GO terms by amounts of change in gene expression in comparison to the control
      • A z-score is a rating of confidence that considers whether the change was by chance or not
      • Also determines whether data is up regulated or down regulated.
  • Figure 1: How MAPPFinder Works
    • Figure graphically demonstrates the process that MAPPFinder goes through in order to identify GO terms and use GenMAPP to graphically display data
  • Article performed and example case to demonstrate the advantages of MAPPFinder and how it can be used
    • The example analyzed publicly available mouse microarray data on cardiac development in 12.5 day old mouse embryo and compared it to adult mouse heart cells as the control
    • Program automatically locates genes from microarray and finds the GO terms that are associated with those genes
  • Table 1: Genes found by MAPPFinder
    • Gives data on the amount of genes measured, and more data indicating what database source the genes came from.
    • Yields amount of genes that are known to be associated with the biological processes, cellular components, as well as the molecular function.
    • Also displays amount of genes changed and whether they increased or decreased
  • Table 2: Text representation of showing MAPPFinder results
    • Displays a text version of the data that shows all genes significantly increased and separates the genes by processes, components, and functions.
    • Gives values of percent present, percent changed and a z-score
  • Figure 2: Graphical representation of the MAPPFinder data in the MAPPFinder browser
    • Demonstrates how MAPPFinder uses GO data and graphically displays them
  • Figure 3a: Shows how different pathways can be simply clicked and demonstrate the child terms associated with them
  • Figure 3b
    • Shows graphical representation of what information is seen when a child term is clicked on
  • Figure 3c
    • Demonstrates the graphical representation of Figure 3b when coupled with GenMAPP software
  • MAPPFinder key results from example
    • Highest up regulation was found in cell division and growth pathways
    • Highest down regulation was found in energy metabolism
    • Global view of gene expression changes allow to be put into the context of other regulatory and developmental processes
  • MAPPFinder navigation functions
    • Capable of searching for exact GO term matches
    • Can also search by gene identifier to find GO terms
    • User can also search GO tree to automatically show all nodes that fit the requirement of a minimum number of genes, minimum percent of genes meeting criterion, or minimum z-score
  • Conclusion
    • MAPPFinder is an extremely effective tool that is capable of rapidly comparing microarray data to create a global gene expression profile
    • MAPPFinder is capable of yielding important statistical data such as up regulation, down regulation, and z-scores

Powerpoint Link

MAPPFinder Powerpoint

Evan Montz 02:54, 18 October 2010 (EDT)