Improving promoter prediction Improving promoter prediction for the NNPP2.2 algorithm: a case study using Escherichia coli DNA sequences | Zendy

Sandy Burden | Zendy; YanXia Lin | Zendy; R. Zhang | Zendy

Open Access

Improving promoter prediction Improving promoter prediction for the NNPP2.2 algorithm: a case study using Escherichia coli DNA sequences

Author(s) -

Sandy Burden,

YanXia Lin,

R. Zhang

Publication year - 2004

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/bti047

Subject(s) - promoter , false positive paradox , escherichia coli , computational biology , algorithm , gene , dna , coding (social sciences) , gene prediction , computer science , biology , genetics , artificial intelligence , mathematics , genome , gene expression , statistics

Although a great deal of research has been undertaken in the area of promoter prediction, prediction techniques are still not fully developed. Many algorithms tend to exhibit poor specificity, generating many false positives, or poor sensitivity. The neural network prediction program NNPP2.2 is one such example.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research