A Novel Approach to Predict the Origin of Replication

dc.contributor.authorPromi, Mashiyat Alam
dc.date.accessioned2021-06-16T07:31:59Z
dc.date.available2021-06-16T07:31:59Z
dc.date.issued2021-01-15
dc.description.abstractIn the genome of every species, there exists an origin, known as the origin of replication (ORI), from where the genome starts to replicate itself during the process of cell division. Finding out this origin; is therefore a very prime and demanding problem in bioinformatics research, as this is the main responsible key-factor for the replication process of DNA. In this study, we start off by choosing a benchmark dataset of a yeast named Saccharomyces cerevisiae, generate simple and inexpensive sequence based features, label and prepare the features for computation, feed them to 10 basic machine learning algorithms, compare the results, and finally propose a novel approach, to help predict the Origin of Replication by achieving 98.15% of accuracy by implementing Logistic Regression classifier with 10 fold cross validation. Here in this study, we also represent a comparison table containing the results for all 10 experimented classifiers, to showcase the clear distinction and success of our proposed approach, from that of others.en_US
dc.identifier.urihttp://dspace.uiu.ac.bd/handle/52243/2123
dc.language.isoen_USen_US
dc.subjectMachine Learningen_US
dc.subjectBioinformaticsen_US
dc.subjectOrigin of Replication in Genomeen_US
dc.titleA Novel Approach to Predict the Origin of Replicationen_US
dc.typeThesisen_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
A_Novel_Approach_to_Predict_the_Origin_of_Replication.pdf
Size:
619.76 KB
Format:
Adobe Portable Document Format
Description:

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
1.62 KB
Format:
Item-specific license agreed upon to submission
Description: