Epigenetic targets are of significant importance in drug discovery research, as demonstrated by the eight approved epigenetic drugs for treatment cancer and increasing availability chemogenomic data related to epigenetics. This represents many structure-activity relationships that have not been exploited thus far develop predictive models support medicinal chemistry efforts. Herein, we report f...

When manufacturing machine parts using additive 3D technologies, we are faced with the task of choosing a specific technology, material, and settings for printing process. These factors affect time, cost, accuracy, strength other criteria performance parts. Based on this, purpose study is to develop recommendations optimizing models printing.
 The describes main approaches three-dimensiona...

The current state-of-the-art deep neural networks (DNNs) for Alzheimer's Disease diagnosis use different biomarker combinations to classify patients, but do not allow extracting knowledge about the interactions of biomarkers. However, improve our understanding disease, it is paramount extract such from learned model. In this paper, we propose a Deep Factorization Machine model that combines abi...

Air temperature is an essential climatic component particularly in water resources management and other agro-hydrological/meteorological activities planning This paper examines the prediction capability of three machine learning models, least square support vector (LSSVM), group method data handling neural network (GMDHNN) classification regression trees (CART) air forecasting using monthly Ast...