A Support Vector Machine Based Method to Predict Success for Polymerase Chain Reactions.

Abstract:

Polymerase chain reaction (PCR) is one of the most popular molecular biological techniques and has been widely applied in many areas. However, PCR still faces challenges nowadays. During recent decades, the experimental procedure of PCR, including the primer design, was always the focus of attention, while little attention was paid to the analysis of the PCR template, and still nobody can accurately predict whether or not a DNA sequence can be simply amplified using conventional Taq DNA polymerase-based PCR protocol. In this study, we focus on the DNA template, the subject of PCR experiment, and introduce a support vector machine (SVM) based method to help evaluate PCR result. Through the Jackknife cross-validation test, our method achieves an accuracy of 92.06%, with 93.62% sensitivity and 90.53% specificity.

Polymerases:

Topics:

Status:

new topics/pols set partial results complete validated

Results:

No results available for this paper.

Entry validated by:

Log in to edit reference All References

Using Polbase tables:

Sorting:

Tables may be sorted by clicking on any of the column titles. A second click reverses the sort order. <Ctrl> + click on the column titles to sort by more than one column (e.g. family then name).

Filtering:

It is also possible to filter the table by typing into the search box above the table. This will instantly hide lines from the table that do not contain your search text.