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Codon Usage Bias Database (CUB-DB)

Codon Usage Bias Database (CUB-DB). The Codon Usage Bias Database is a showcase for my bias measures, modified Self-Consistent Codon Index (mSCCI) and a direct search approach for codon adaptiveness (weights) using a genetic algorithm (GA). The first modifies the Carbone et al. Algorithm to direct it toward translational efficiency bias instead of the dominant bias ( mSCCI, Raiford et al. This is the bias measure that I recommend you use if you wish to measure adherence to translational efficiency bias.

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Codon Usage Bias Database (CUB-DB) | web-dev.cs.umt.edu Reviews

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Codon Usage Bias Database (CUB-DB). The Codon Usage Bias Database is a showcase for my bias measures, modified Self-Consistent Codon Index (mSCCI) and a direct search approach for codon adaptiveness (weights) using a genetic algorithm (GA). The first modifies the Carbone et al. Algorithm to direct it toward translational efficiency bias instead of the dominant bias ( mSCCI, Raiford et al. This is the bias measure that I recommend you use if you wish to measure adherence to translational efficiency bias.

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Codon Usage Bias Database (CUB-DB) | web-dev.cs.umt.edu Reviews

https://web-dev.cs.umt.edu

Codon Usage Bias Database (CUB-DB). The Codon Usage Bias Database is a showcase for my bias measures, modified Self-Consistent Codon Index (mSCCI) and a direct search approach for codon adaptiveness (weights) using a genetic algorithm (GA). The first modifies the Carbone et al. Algorithm to direct it toward translational efficiency bias instead of the dominant bias ( mSCCI, Raiford et al. This is the bias measure that I recommend you use if you wish to measure adherence to translational efficiency bias.

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web-dev.cs.umt.edu

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Codon Usage Bias Database (CUB-DB)

http://web-dev.cs.umt.edu/future.shtml

Future plans for the CUB-DB. What's in and out of the DB. The big thing slowing down the process is making sure we have a good backup process for the database. It doesn't seem very efficient to shut-down the DB every night and spend an hour or more dumping all of the data into a monolithic backup. When the DB is only 50Meg, then a mysqldump works just find. But 40Gig? I want to add strand criterion to my measures. This will require knowledge of where the chromosomal replication origin site. It currently ...

2

Codon Usage Database

http://web-dev.cs.umt.edu/content/helpMethods.php

Click a method to be see the article describing its calculation. Frequency of Preferred Codons (FOP). Determine which codons are preferred in a set of highly expressed genes, and then calculate the frequency of preferred codons (pref/(pref nonpref) for each gene. Major Codon Usage (MCU). Use multivariate analysis to first identify the axis of greatest variance in 59-dimensional codon usage frequency data (RSCU), then identify which codons contribute positively to this trend. Codon Adaptation Index (CAI).

3

Codon Usage Bias Database (CUB-DB)

http://web-dev.cs.umt.edu/index.shtml

Codon Usage Bias Database (CUB-DB). The Codon Usage Bias Database is a showcase for my bias measures, modified Self-Consistent Codon Index (mSCCI) and a direct search approach for codon adaptiveness (weights) using a genetic algorithm (GA). The first modifies the Carbone et al. Algorithm to direct it toward translational efficiency bias instead of the dominant bias ( mSCCI, Raiford et al. This is the bias measure that I recommend you use if you wish to measure adherence to translational efficiency bias.

4

Codon Usage Bias Database (CUB-DB)

http://web-dev.cs.umt.edu/tutorial.shtml

Codon Usage Bias Tutorial. Methods for Isolating Translational Efficiency Bias. Frequency of usage of optimal codons (FOP). This frequency was found to be highly correlated with protein abundance. All the rules except tRNA availability were the same from species to species and the translational efficiency attained through tRNA abundance was presumed to be the driving force behind the correlation. Codon Adaptation Index (CAI). Methods for Simply Measuring the Degree of Bias. Effective Number of Codons (Nc).

5

Codon Usage Database

http://web-dev.cs.umt.edu/lsdb.php

Deinococcus soli' Cha et al. 2014. Acetobacter pasteurianus IFO 3283-01. Acetobacter pasteurianus IFO 3283-01-42C. Acetobacter pasteurianus IFO 3283-03. Acetobacter pasteurianus IFO 3283-07. Acetobacter pasteurianus IFO 3283-12. Acetobacter pasteurianus IFO 3283-22. Acetobacter pasteurianus IFO 3283-26. Acetobacter pasteurianus IFO 3283-32. Acetobacter pasteurianus NBRC 101655. Acetobacter sp. SLV-7. Acetobacterium woodii DSM 1030. Acetohalobium arabaticum DSM 5501. Acidaminococcus fermentans DSM 20731.

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Codon Usage Bias Database (CUB-DB)

Codon Usage Bias Database (CUB-DB). The Codon Usage Bias Database is a showcase for my bias measures, modified Self-Consistent Codon Index (mSCCI) and a direct search approach for codon adaptiveness (weights) using a genetic algorithm (GA). The first modifies the Carbone et al. Algorithm to direct it toward translational efficiency bias instead of the dominant bias ( mSCCI, Raiford et al. This is the bias measure that I recommend you use if you wish to measure adherence to translational efficiency bias.

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