Protein engineers conventionally use tools such as Directed Evolution to find new proteins
with better functionalities and traits. More recently, computational techniques and especially …

The post-genomic era has raised a growing demand for efficient procedures to identify
protein functions, which can be accomplished by applying machine learning to the …

The paper identified the predictors of student attrition in the Higher Education Institution
(HEI) through predictive analytics approach. The prediction model used in the study includes …

With the recent advances of genomic sequencing techniques, the number of protein
sequences available for analysis has increased greatly. Wet-lab processes to predict the …

ABSTRACT Support Vector Machine (SVM) is a supervised learning algorithm widely used
in data classification problems. However, the quality of the solution is related to the chosen …

Improving accuracy of a prediction model is an ongoing subject of research in the field of
information technology. Improved efficiency of prediction model helped an organization in …

A panel of large number of common Single Nucleotide Polymorphisms (SNPs) distributed
across an entire porcine genome has been widely used to represent genetic variability of …

Predicting protein function is a latent problem and a challenge in the field of Bioinformatics.
Over the years, several computational approaches have been proposed for this purpose …

Many approaches have been proposed to enhance the accuracy of protein structural class.
However, such approaches did not cover the low-similarity sequences which are proved to …

Prediction helps organizations in their decision-making activities for the improvement of the
different functions, services, and even their income. The C4. 5 algorithm is the most …