Kara M Dismuke Week 10 Journal: Difference between revisions
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==Introduction== | ==Introduction== | ||
===Regulation of gene expression=== | ===Regulation of gene expression=== | ||
*important process in cell | |||
*takes static information (in DNA) and transmits it into protein molecules (that serve various functions) | |||
*requires recognition of specific promoter sequences | |||
*the effects of transcription change with as the cell changes/develops | |||
===Microarrays=== | |||
*document changes in gene expression over time | |||
**analysis these changes can enable one to see a relationship between genes and their regulators | |||
*use microarray data to track the interaction between genes and their regulators | |||
===Saccharomyces cerevisiae=== | |||
*gene-expression data gathered from genome-wide microarrays | |||
*data analyzed using clustering methods | |||
*data modeled using singular value decomposition | |||
*genes were grouped according to their transcriptional regulatory networks (i.e. relationship between the genes and their respective regulators/promoters) | |||
===Previous Studies=== | |||
*use differential equations to try to develop a linear model that reflects the transcription pattern of each of the genes being studied | |||
*Woolf and Wang: used "fuzzy logic" to try to do this | |||
**Nachman: used kinetic model and Bayesian networks | |||
**Bar-Joseph: used genomic information and analysis of gene expression data | |||
***Wang and Makita: building of Bar-Joseph approach, the looked at the analysis of the promoter sequences and the sigma factor binding sequence motif | |||
===This Paper=== | |||
*alternative method b/c uses a ''nonlinear'' differential equation model | |||
*Procedure | |||
**choose set of all potential regulators (chose pool of 184) | |||
**choose set of target genes of S. cerevisiae (chose 40) | |||
**picks genes from possible regulators and applies model to then compare results to information known about the target gene | |||
***repeated to exhaust all possibilites | |||
***determine which regulators correctly model gene expression model | |||
*compare results and make conclusions using results from other studies & also a comparison of the linear model | |||
*result: this method can correctly identify a target gene's specific regulator and can say whether or not that regulator is an activator or repressor | |||
=Definitions= | =Definitions= |
Revision as of 14:46, 22 March 2015
Outline
Introduction
Regulation of gene expression
- important process in cell
- takes static information (in DNA) and transmits it into protein molecules (that serve various functions)
- requires recognition of specific promoter sequences
- the effects of transcription change with as the cell changes/develops
Microarrays
- document changes in gene expression over time
- analysis these changes can enable one to see a relationship between genes and their regulators
- use microarray data to track the interaction between genes and their regulators
Saccharomyces cerevisiae
- gene-expression data gathered from genome-wide microarrays
- data analyzed using clustering methods
- data modeled using singular value decomposition
- genes were grouped according to their transcriptional regulatory networks (i.e. relationship between the genes and their respective regulators/promoters)
Previous Studies
- use differential equations to try to develop a linear model that reflects the transcription pattern of each of the genes being studied
- Woolf and Wang: used "fuzzy logic" to try to do this
- Nachman: used kinetic model and Bayesian networks
- Bar-Joseph: used genomic information and analysis of gene expression data
- Wang and Makita: building of Bar-Joseph approach, the looked at the analysis of the promoter sequences and the sigma factor binding sequence motif
This Paper
- alternative method b/c uses a nonlinear differential equation model
- Procedure
- choose set of all potential regulators (chose pool of 184)
- choose set of target genes of S. cerevisiae (chose 40)
- picks genes from possible regulators and applies model to then compare results to information known about the target gene
- repeated to exhaust all possibilites
- determine which regulators correctly model gene expression model
- compare results and make conclusions using results from other studies & also a comparison of the linear model
- result: this method can correctly identify a target gene's specific regulator and can say whether or not that regulator is an activator or repressor
Definitions
- transcription
- Transcription is the first step of gene expression, in which a particular segment of DNA is copied into RNA by the enzyme RNA polymerase. Both RNA and DNA are nucleic acids, which use base pairs of nucleotides as a complementary language that can be converted back and forth from DNA to RNA by the action of the correct enzymes. During transcription, a DNA sequence is read by an RNA polymerase, which produces a complementary, antiparallel RNA strand called a primary transcript. As opposed to DNA replication, transcription results in an RNA complement that includes the nucleotide uracil (U) in all instances where thymine (T) would have occurred in a DNA complement. Also unlike DNA replication where DNA is synthesized, transcription does not involve an RNA primer to initiate RNA synthesis.Although Transcription is nice.
- http://www.biology-online.org/dictionary/Transcription
- RNA polymerase
- An enzyme that is responsible for making rna from a dna template. In all cells RNAP is needed for constructing rna chains from a dna template, a process termed transcription. In scientific terms, RNAP is a nucleotidyl transferase that polymerizes ribonucleotides at the 3' end of an rna transcript. Rna polymerase enzymes are essential and are found in all organisms, cells, and many viruses.
- http://www.biology-online.org/dictionary/RNA_polymerase
- promoter
- A site in a DNA molecule at which RNA polymerase and transcription factors bind to initiate transcription of mRNA.
- http://www.biology-online.org/dictionary/Promoter
- activator
- A DNA-binding transcription metabolite that positively modulates an allosteric Enzyme or regulates one or more genes by increasing the rate of transcription.
- http://www.biology-online.org/dictionary/Activator
- repressor
- A regulatory protein that binds to an operator and blocks transcription of the genes of an opreon
- http://www.biology-online.org/dictionary/Repressor
- regulator
- In genetics, a regulator pertains to a gene that codes for substances capable of repressing expression of another gene.
- http://www.biology-online.org/dictionary/Regulator
- mRNA
- Abbreviated form for messenger ribonucleic acid, the type of RNA that codes for the chemical blueprint for a protein (during protein synthesis).
- http://www.biology-online.org/dictionary/Mrna
- gene expression
- The conversion of the information from the gene into mRNA via transcription and then to protein via translation resulting in the phenotypic manifestation of the gene.
- http://www.biology-online.org/dictionary/Gene_Expression
- punative
- Denoting a supposition or inference based on what was commonly believed, reputed, or deemed rather than on a direct evidence
- http://www.biology-online.org/dictionary/Putative
- combinatorial
- Any system using a random assortment of components at any positions in the linear arrangement of atoms, i.e., a combinatorial library of mutations could contain positions where all four bases have been randomly inserted.
- http://www.biology-online.org/dictionary/Combinatorial