Recent advances and applications of deep learning, electroencephalography, and modern analysis techniques in screening, evaluation, and mechanistic analysis of …

L Su, H Ji, J Kong, W Yan, Q Zhang, J Li… - Trends in Food Science & …, 2024 - Elsevier
Background Taste peptides are oligopeptides that improve the flavor and palatability of food.
Due to their unique taste characteristics and nutritional values, the development of taste …

[HTML][HTML] Bioactive peptides derived from whey proteins for health and functional beverages

M Saubenova, Y Oleinikova, A Rapoport… - Fermentation, 2024 - mdpi.com
Milk serves as a crucial source of natural bioactive compounds essential for human nutrition
and health. The increased production of high-protein dairy products is a source of whey—a …

AnnoPRO: a strategy for protein function annotation based on multi-scale protein representation and a hybrid deep learning of dual-path encoding

L Zheng, S Shi, M Lu, P Fang, Z Pan, H Zhang, Z Zhou… - Genome biology, 2024 - Springer
Protein function annotation has been one of the longstanding issues in biological sciences,
and various computational methods have been developed. However, the existing methods …

Enhanced efficacy of combined VEGFR peptide–drug conjugate and anti-PD-1 antibody in treating hepatocellular carcinoma

J Liu, Y Bai, X Liu, B Zhou, P Sun, Y Wang, S Ju… - Scientific Reports, 2024 - nature.com
This study aimed to design a VEGFR-targeting peptide–drug conjugate with the ability to
decrease tumor burden and suppress tumor angiogenesis, and to further evaluate the …

AI-Assisted Rational Design and Activity Prediction of Biological Elements for Optimizing Transcription-Factor-Based Biosensors

N Ding, Z Yuan, Z Ma, Y Wu, L Yin - Molecules, 2024 - pmc.ncbi.nlm.nih.gov
The rational design, activity prediction, and adaptive application of biological elements (bio-
elements) are crucial research fields in synthetic biology. Currently, a major challenge in the …

Cardiovascular health management in diabetic patients with machine-learning-driven predictions and interventions

R Jose, F Syed, A Thomas, M Toma - Applied Sciences, 2024 - mdpi.com
The advancement of machine learning in healthcare offers significant potential for
enhancing disease prediction and management. This study harnesses the PyCaret library …

Enhanced transformer encoder and hybrid cascaded upsampler for medical image segmentation

C Li, L Wang, S Cheng - Expert Systems with Applications, 2024 - Elsevier
UNet has been highly successful in various medical image segmentation tasks, but the
restricted field of perception of convolutional operations has led to the lack of UNet's ability …

Fire detection in ship engine rooms based on deep learning

J Zhu, J Zhang, Y Wang, Y Ge, Z Zhang, S Zhang - Sensors, 2023 - mdpi.com
Ship fires are one of the main factors that endanger the safety of ships; because the ship is
far away from land, the fire can be difficult to extinguish and could often cause huge losses …

Effective multi-modal clustering method via skip aggregation network for parallel scRNA-seq and scATAC-seq data

D Hu, K Liang, Z Dong, J Wang, Y Zhao… - Briefings in …, 2024 - academic.oup.com
In recent years, there has been a growing trend in the realm of parallel clustering analysis
for single-cell RNA-seq (scRNA) and single-cell Assay of Transposase Accessible …

Deep sample clustering domain adaptation for breast histopathology image classification

P Wang, G Yang, Y Li, P Li, Y Guo, R Chen - Biomedical Signal Processing …, 2024 - Elsevier
Deep learning has been widely applied to the diagnosis of breast cancer. Most deep
learning models require a large number of labeled samples for training, but a large number …