Recent advances in machine learning methods for predicting LncRNA and disease associations
J Tan, X Li, L Zhang, Z Du - Frontiers in Cellular and Infection …, 2022 - frontiersin.org
Long non-coding RNAs (lncRNAs) are involved in almost the entire cell life cycle through
different mechanisms and play an important role in many key biological processes …
different mechanisms and play an important role in many key biological processes …
Multi-task prediction-based graph contrastive learning for inferring the relationship among lncRNAs, miRNAs and diseases
Motivation Identifying the relationships among long non-coding RNAs (lncRNAs),
microRNAs (miRNAs) and diseases is highly valuable for diagnosing, preventing, treating …
microRNAs (miRNAs) and diseases is highly valuable for diagnosing, preventing, treating …
GCNFORMER: graph convolutional network and transformer for predicting lncRNA-disease associations
D Yao, B Li, X Zhan, X Zhan, L Yu - BMC bioinformatics, 2024 - Springer
Background A growing body of researches indicate that the disrupted expression of long
non-coding RNA (lncRNA) is linked to a range of human disorders. Therefore, the effective …
non-coding RNA (lncRNA) is linked to a range of human disorders. Therefore, the effective …
Transformer-based enhanced model for accurate prediction and comprehensive analysis of hazardous waste generation in Shanghai: Implications for sustainable …
W Shi, Y Zhao, Z Li, W Zhang, T Zhou, K Lin - Chemosphere, 2023 - Elsevier
The escalating generation of hazardous waste (HW) has become a pressing concern
worldwide, straining waste management systems and posing significant health hazards …
worldwide, straining waste management systems and posing significant health hazards …
Predicting lncRNA-disease associations based on heterogeneous graph convolutional generative adversarial network
Z Lu, H Zhong, L Tang, J Luo, W Zhou… - PLOS Computational …, 2023 - journals.plos.org
There is a growing body of evidence indicating the crucial roles that long non-coding RNAs
(lncRNAs) play in the development and progression of various diseases, including cancers …
(lncRNAs) play in the development and progression of various diseases, including cancers …
RNA Sequence Analysis Landscape: A Comprehensive Review of Task Types, Databases, Datasets, Word Embedding Methods, and Language Models
Deciphering information of RNA sequences reveals their diverse roles in living organisms,
including gene regulation and protein synthesis. Aberrations in RNA sequence such as …
including gene regulation and protein synthesis. Aberrations in RNA sequence such as …
A combined deep learning framework for mammalian m6A site prediction
Summary N 6-methyladenosine (m6A) is the most prevalent chemical modification in
eukaryotic mRNAs and plays key roles in diverse cellular processes. Precise localization of …
eukaryotic mRNAs and plays key roles in diverse cellular processes. Precise localization of …
Self-Supervised Contrastive Learning on Attribute and Topology Graphs for Predicting Relationships Among lncRNAs, miRNAs and Diseases
Exploring potential association between long non-coding RNAs (lncRNAs), microRNAs
(miRNAs) and diseases is an essential part of prevention, diagnosis and treatment of …
(miRNAs) and diseases is an essential part of prevention, diagnosis and treatment of …
X-lda: an interpretable and knowledge-informed heterogeneous graph learning framework for lncrna-disease association prediction
The identification of disease-related long noncoding RNAs (lncRNAs) is beneficial to
unravel the intricacies of gene expression regulation and epigenetic signatures …
unravel the intricacies of gene expression regulation and epigenetic signatures …
HGECDA: a heterogeneous graph embedding model for CircRNA-disease association prediction
Y Fu, R Yang, L Zhang, X Fu - IEEE Journal of Biomedical and …, 2023 - ieeexplore.ieee.org
Circular RNAs (circRNAs) are specifically and abnormally expressed in disease tissues, and
thus can be used as biomarkers to diagnose relevant diseases. Predicting circRNA-disease …
thus can be used as biomarkers to diagnose relevant diseases. Predicting circRNA-disease …