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Progress and trends in neurological disorders research based on deep learning
In recent years, deep learning (DL) has emerged as a powerful tool in clinical imaging,
offering unprecedented opportunities for the diagnosis and treatment of neurological …
offering unprecedented opportunities for the diagnosis and treatment of neurological …
Prediction of compressive strength of rice husk ash concrete based on stacking ensemble learning model
Q Li, Z Song - Journal of Cleaner Production, 2023 - Elsevier
By replacing cement in concrete production with rice husk ash (RHA), the amount of cement
used and its environmental impact can be reduced. The objective of this study is to …
used and its environmental impact can be reduced. The objective of this study is to …
[HTML][HTML] A first computational frame for recognizing heparin-binding protein
Heparin-binding protein (HBP) is a cationic antibacterial protein derived from multinuclear
neutrophils and an important biomarker of infectious diseases. The correct identification of …
neutrophils and an important biomarker of infectious diseases. The correct identification of …
Deep-STP: a deep learning-based approach to predict snake toxin proteins by using word embeddings
Snake venom contains many toxic proteins that can destroy the circulatory system or
nervous system of prey. Studies have found that these snake venom proteins have the …
nervous system of prey. Studies have found that these snake venom proteins have the …
[HTML][HTML] Wearable flexible electronics based cardiac electrode for researcher mental stress detection system using machine learning models on single lead …
In the modern world, wearable smart devices are continuously used to monitor people's
health. This study aims to develop an automatic mental stress detection system for …
health. This study aims to develop an automatic mental stress detection system for …
[HTML][HTML] A statistical analysis of the sequence and structure of thermophilic and non-thermophilic proteins
Thermophilic proteins have various practical applications in theoretical research and in
industry. In recent years, the demand for thermophilic proteins on an industrial scale has …
industry. In recent years, the demand for thermophilic proteins on an industrial scale has …
iRNA-ac4C: a novel computational method for effectively detecting N4-acetylcytidine sites in human mRNA
Abstract RNA N4-acetylcytidine (ac4C) is the acetylation of cytidine at the nitrogen-4
position, which is a highly conserved RNA modification and involves a variety of biological …
position, which is a highly conserved RNA modification and involves a variety of biological …
[HTML][HTML] Empirical comparison and recent advances of computational prediction of hormone binding proteins using machine learning methods
Hormone binding proteins (HBPs) belong to the group of soluble carrier proteins. These
proteins selectively and non-covalently interact with hormones and promote growth …
proteins selectively and non-covalently interact with hormones and promote growth …
Phage_UniR_LGBM: phage virion proteins classification with UniRep features and LightGBM model
W Bao, Q Cui, B Chen, B Yang - … and mathematical methods in …, 2022 - Wiley Online Library
Phage, the most prevalent creature on the planet, serves a variety of critical roles. Phage's
primary role is to facilitate gene‐to‐gene communication. The phage proteins can be …
primary role is to facilitate gene‐to‐gene communication. The phage proteins can be …
Machine learning-based modeling and analysis of PFOS removal from contaminated water by nanofiltration process
Per-and polyfluoroalkyl substances (PFAS) are hazardous chemicals that have been widely
used in different industries and released into the environment through contaminated …
used in different industries and released into the environment through contaminated …