[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 …

CODENET: A deep learning model for COVID-19 detection

H Ju, Y Cui, Q Su, L Juan, B Manavalan - Computers in Biology and …, 2024 - Elsevier
Conventional COVID-19 testing methods have some flaws: they are expensive and time-
consuming. Chest X-ray (CXR) diagnostic approaches can alleviate these flaws to some …

Cm-siRPred: Predicting chemically modified siRNA efficiency based on multi-view learning strategy

T Liu, J Huang, D Luo, L Ren, L Ning, J Huang… - International Journal of …, 2024 - Elsevier
The rational modification of siRNA molecules is crucial for ensuring their drug-like
properties. Machine learning-based prediction of chemically modified siRNA (cm-siRNA) …

[HTML][HTML] SAGESDA: Multi-GraphSAGE networks for predicting SnoRNA-disease associations

BM Momanyi, YW Zhou, BK Grace-Mercure… - Current Research in …, 2024 - Elsevier
Over the years, extensive research has highlighted the functional roles of small nucleolar
RNAs in various biological processes associated with the development of complex human …

Advanced forecasting of COVID-19 epidemic: Leveraging ensemble models, advanced optimization, and decomposition techniques

Y Yin, I Ahmadianfar, FK Karim, H Elmannai - Computers in Biology and …, 2024 - Elsevier
In the global effort to address the outbreak of the new coronavirus pneumonia (COVID-19)
pandemic, accurate forecasting of epidemic patterns has become crucial for implementing …

E-mula: an ensemble multi-localized attention feature extraction network for viral protein subcellular localization

GM Bakanina Kissanga, H Zulfiqar, S Gao, SB Yussif… - Information, 2024 - mdpi.com
Accurate prediction of subcellular localization of viral proteins is crucial for understanding
their functions and developing effective antiviral drugs. However, this task poses a …

The prediction of Recombination Hotspot Based on Automated Machine Learning

DX Ye, JW Yu, R Li, YD Hao, TY Wang, H Yang… - Journal of Molecular …, 2024 - Elsevier
Meiotic recombination plays a pivotal role in genetic evolution. Genetic variation induced by
recombination is a crucial factor in generating biodiversity and a driving force for evolution …

ACVPred: Enhanced prediction of anti-coronavirus peptides by transfer learning combined with data augmentation

Y Xu, T Liu, Y Yang, J Kang, L Ren, H Ding… - Future Generation …, 2024 - Elsevier
Anti-coronavirus peptides (ACVPs) have garnered significant attention in COVID-19
therapeutic research due to their precise targeting, low risk of drug resistance, flexible …

ncRS: A resource of non-coding RNAs in sepsis

B Zhong, Y Dai, L Chen, X Xu, Y Lan, L Deng… - Computers in Biology …, 2024 - Elsevier
Sepsis, a life-threatening condition triggered by the body's response to infection, presents a
significant global healthcare challenge characterized by disarrayed host responses …

RDscan: Extracting RNA-disease relationship from the literature based on pre-training model

Y Zhang, Y Yang, L Ren, L Ning, Q Zou, N Luo… - Methods, 2024 - Elsevier
With the rapid advancements in molecular biology and genomics, a multitude of connections
between RNA and diseases has been unveiled, making the efficient and accurate extraction …