Despite several accomplishments in addressing malnutrition, the issue of food scarcity remains a persistent concern all over the globe, particularly in the South Asian region. One recommended solution to address this situation involves advocating for further liberalization of global food trading and opening employment opportunities. In this context, using panel data spanning 2000-2019, this study makes a novel attempt to quantify the impact of agricultural trade openness and agricultural employment on food security in countries belonging to the South Asian region while controlling the tariff and agricultural production.
View Article and Find Full Text PDFMotivation: Extracting useful feature set which contains significant discriminatory information is a critical step in effectively presenting sequence data to predict structural, functional, interaction and expression of proteins, DNAs and RNAs. Also, being able to filter features with significant information and avoid sparsity in the extracted features require the employment of efficient feature selection techniques. Here we present PyFeat as a practical and easy to use toolkit implemented in Python for extracting various features from proteins, DNAs and RNAs.
View Article and Find Full Text PDFDrug target interaction prediction is a very labor-intensive and expensive experimental process which has motivated researchers to focus on in silico prediction to provide information on potential interaction. In recent years, researchers have proposed several computational approaches for predicting new drug target interactions. In this paper, we present CFSBoost, a simple and computationally cheap ensemble boosting classification model for identification and prediction of drug-target interactions using evolutionary and structural features.
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