title: ANN modeling of DNA sequences: new strategies using DNA shape code.
abstract: Two new encoding strategies, namely, wedge and twist codes, which are based on the DNA helical parameters, are introduced to represent DNA sequences in artificial neural network (ANN)-based modeling of biological systems. The performance of the new coding strategies has been evaluated by conducting three case studies involving mapping (modeling) and classification applications of ANNs. The proposed coding schemes have been compared rigorously and shown to outperform the existing coding strategies especially in situations wherein limited data are available for building the ANN models.
authors.affiliation: Chemical Engineering Division, National Chemical Laboratory, Pune, India.
authors.forename: R V
authors.initials: RV
authors.lastname: Parbhane
authors.forename: S S
authors.initials: SS
authors.lastname: Tambe
authors.forename: B D
authors.initials: BD
authors.lastname: Kulkarni
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D004247:DNA / Q000737:chemistry* / Q000235:genetics*; D016571:Neural Networks, Computer; D009690:Nucleic Acid Conformation; D011401:Promoter Regions, Genetic; D017422:Sequence Analysis, DNA / Q000379:methods* / Q000706:statistics & numerical data
chemical_list: D004247:DNA