No abstract

No abstract

Due to the complexity of HIV/AIDS cutting edge machine learning technologies are used for drug delivery and development. In this review drug delivery methods are discussed with machine learning techniques. Combination of both these computational methods will give new hope to enhance the life of HIV infected persons. As these methods are time consuming and easy to interpret than wet lab techniques.

No abstract

MicroRNAs (miRNA's) constitute a large family of non coding RNAs that function to regulate gene expression.Wet lab experiments usually used to classify the miRNA of plants and animals are highly expensive, labor intensive and time consuming. Thus there arises a need for computational approach for classification of plant and animal miRNA. These computational approaches are fast and economical as compared to wet lab techniques. Here a machine learning approach is used to classify miRNA of HIV, plants and animals. The new SVM learning algorithm called Weka LibSVM has been used for classification of plant and animal and HIVmiRNA. The model has been tested on available data and it gives results with 95% accuracy.