Team I Gene Prediction Group: Difference between revisions
Jump to navigation
Jump to search
| Line 6: | Line 6: | ||
*Prokaryotic genes have a relatively well-understood promoter sequence, such as a regulatory sequence, which can regulate the transcription of the gene into an mRNA. | *Prokaryotic genes have a relatively well-understood promoter sequence, such as a regulatory sequence, which can regulate the transcription of the gene into an mRNA. | ||
*Each prokaryotic gene has open reading frames(ORF) which start with start codons and end with end codons with no interruptions(end-codons) in-between, so it can provide a good, but not assured prediction of the protein-coding regions. | *Each prokaryotic gene has open reading frames(ORF) which start with start codons and end with end codons with no interruptions(end-codons) in-between, so it can provide a good, but not assured prediction of the protein-coding regions. | ||
===Gene Prediction=== | |||
Gene prediction or gene finding is a process of identifying the regions of genomic DNA that encode genes. It is devised two-classes of methods that use similarity-based(homology) searches and ab initio prediction to capture the compositional differences among coding regions which will be translated into protein and noncoding DNA which can be translated into tRNAs and rRNAs. | |||
Revision as of 14:53, 4 March 2020
Members: Maria Ahmad, Hira Anis, Jessica Mulligan, Priya Narayanan, Aaron Pfennig, Winnie Zheng
Introduction
Prokaryotic Gene Feature
- Prokaryotic genes have a relatively well-understood promoter sequence, such as a regulatory sequence, which can regulate the transcription of the gene into an mRNA.
- Each prokaryotic gene has open reading frames(ORF) which start with start codons and end with end codons with no interruptions(end-codons) in-between, so it can provide a good, but not assured prediction of the protein-coding regions.
Gene Prediction
Gene prediction or gene finding is a process of identifying the regions of genomic DNA that encode genes. It is devised two-classes of methods that use similarity-based(homology) searches and ab initio prediction to capture the compositional differences among coding regions which will be translated into protein and noncoding DNA which can be translated into tRNAs and rRNAs.