AIPs-DeepEnC-GA: Predicting anti-inflammatory peptides using embedded evolutionary and sequential feature integration with genetic algorithm based deep …
Inflammation is a biological response to harmful stimuli including infections, damaged cells,
tissue injuries, and toxic chemicals. It plays an essential role in facilitating tissue repair by …
tissue injuries, and toxic chemicals. It plays an essential role in facilitating tissue repair by …
[HTML][HTML] Applications of single‑cell omics and spatial transcriptomics technologies in gastric cancer
L Ren, D Huang, H Liu, L Ning… - Oncology …, 2024 - … .spandidos-publications.com
Gastric cancer (GC) is a prominent contributor to global cancer‑related mortalities, and a
deeper understanding of its molecular characteristics and tumor heterogeneity is required …
deeper understanding of its molecular characteristics and tumor heterogeneity is required …
mACPpred 2.0: Stacked deep learning for anticancer peptide prediction with integrated spatial and probabilistic feature representations
Anticancer peptides (ACPs), naturally occurring molecules with remarkable potential to
target and kill cancer cells. However, identifying ACPs based solely from their primary amino …
target and kill cancer cells. However, identifying ACPs based solely from their primary amino …
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 …
PLMACPred prediction of anticancer peptides based on protein language model and wavelet denoising transformation
Anticancer peptides (ACPs) perform a promising role in discovering anti-cancer drugs. The
growing research on ACPs as therapeutic agent is increasing due to its minimal side effects …
growing research on ACPs as therapeutic agent is increasing due to its minimal side effects …
Moss-m7G: A Motif-Based Interpretable Deep Learning Method for RNA N7-Methlguanosine Site Prediction
N-7methylguanosine (m7G) modification plays a crucial role in various biological processes
and is closely associated with the development and progression of many cancers. Accurate …
and is closely associated with the development and progression of many cancers. Accurate …
Identification of microbe–disease signed associations via multi-scale variational graph autoencoder based on signed message propagation
H Zhu, H Hao, L Yu - BMC biology, 2024 - Springer
Background Plenty of clinical and biomedical research has unequivocally highlighted the
tremendous significance of the human microbiome in relation to human health. Identifying …
tremendous significance of the human microbiome in relation to human health. Identifying …
mHPpred: Accurate identification of peptide hormones using multi-view feature learning
Peptide hormones were first used in medicine in the early 20th century, with the pivotal
event being the isolation and purification of insulin in 1921. These hormones are integral to …
event being the isolation and purification of insulin in 1921. These hormones are integral to …
Prediction of cancer drug combinations based on multidrug learning and cancer expression information injection
S Ren, L Chen, H Hao, L Yu - Future Generation Computer Systems, 2024 - Elsevier
Compared with patients with common diseases, cancer patients usually have a more fragile
cellular microenvironment and more complex or varied complications. Therefore, to meet …
cellular microenvironment and more complex or varied complications. Therefore, to meet …
Voting-ac4C: Pre-trained large RNA language model enhances RNA N4-acetylcytidine site prediction
Abstract RNA N4-acetylcytidine (ac4C) modification plays a crucial role in gene expression
regulation. However, existing prediction methods face limitations in capturing RNA …
regulation. However, existing prediction methods face limitations in capturing RNA …