IEEE/ACM transactions on computational biology and bioinformatics
Jun 5, 2023
The intermolecular interactions between proteins and ligands occur through site-specific amino acid residues in the proteins, and the identification of these key residues plays a critical role in both interpreting protein function and facilitating dr...
IEEE/ACM transactions on computational biology and bioinformatics
Jun 5, 2023
The recognition of protein-protein interaction sites (PPIs) is beneficial for the interpretation of protein functions and the development of new drugs. Traditional biological experiments to identify PPI sites are expensive and inefficient, leading to...
IEEE/ACM transactions on computational biology and bioinformatics
Jun 5, 2023
Exploring drug-protein interactions (DPIs) through computational methods can effectively reduce the workload and the cost of DPI identification. Previous works try to predict DPIs by integrating and analyzing the unique features of drugs and proteins...
IEEE/ACM transactions on computational biology and bioinformatics
Jun 5, 2023
Recent advancements of artificial intelligence based on deep learning algorithms have made it possible to computationally predict compound-protein interaction (CPI) without conducting laboratory experiments. In this manuscript, we integrated a graph ...
IEEE/ACM transactions on computational biology and bioinformatics
Jun 5, 2023
In silico machine learning based prediction of drug functions considering the drug properties would substantially enhance the speed and reduce the cost of identifying promising drug leads. The drug function prediction capability of different drug pro...
Detecting DeepFake videos has become a central task in modern multimedia forensics applications. This article presents a method to detect face swapped videos when the portrayed person in the video is known. We propose using a threshold classifier bas...
Neural networks : the official journal of the International Neural Network Society
Jun 3, 2023
Image steganography is a long-standing image security problem that aims at hiding information in cover images. In recent years, the application of deep learning to steganography has the tendency to outperform traditional methods. However, the vigorou...
OBJECTIVE: To determine whether graph neural network based models of electronic health records can predict specialty consultation care needs for endocrinology and hematology more accurately than the standard of care checklists and other conventional ...
Environmental science and pollution research international
Jun 3, 2023
Economic development has brought about global greenhouse gas emissions and, thus, global climate change, a common challenge worldwide and urgently needs to be addressed. Accurate carbon price forecasting plays a pivotal role in providing a reasonable...
In manufacturing, convolutional neural networks (CNNs) are widely used on image sensor data for data-driven process monitoring and quality prediction. However, as purely data-driven models, CNNs do not integrate physical measures or practical conside...
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