DNAPred_Prot
| dc.contributor.author | Syed Ali Hassan | |
| dc.date.accessioned | 2025-10-29T13:00:19Z | |
| dc.date.available | 2025-10-29T13:00:19Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | In the field of genome annotation identification of DNA binding protein is one the critical challenge. DNA act as a blueprint for the cell in which all necessary information for building and maintaining the trait of an organism. It is DNA which makes the living thing, a living thing. Protein interaction with DNA performs a vital role in regulating DNA functions such as DNA repair, transcription and regulation. Identification of these proteins is an essential task for understanding the regulation of genes. Several methods have been developed to identify the binding sites of DNA and protein depending upon the structures and sequences, but they were costly and time-consuming. Therefore, we propose a methodology named "DNAPred_Prot", which makes use of features gained from position-relative-incidence-matrix (PRIM) that helps in training for efficient and effective prediction of DNA-binding proteins. Using testing techniques like 10-fold cross-validation and jackknife testing an accuracy of 94.95% and 95.11% was yielded respectively. The robustness of the model has been tested by using independent dataset PDB186 and an accuracy of 91.47% achieved by it. From these results, it can be predicted that suggested methodology performs better than other extant methods for identification of DNA-binding Protein. | |
| dc.identifier.uri | https://escholar.umt.edu.pk/handle/123456789/9741 | |
| dc.language.iso | en | |
| dc.publisher | UMT, Lahore | |
| dc.title | DNAPred_Prot | |
| dc.title.alternative | A computational approach for the identification of DNA binding proteins | |
| dc.type | Thesis |