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Towards a complete map of the human long non-coding RNA transcriptome
Gene maps, or annotations, enable us to navigate the functional landscape of our genome.
They are a resource upon which virtually all studies depend, from single-gene to genome …
They are a resource upon which virtually all studies depend, from single-gene to genome …
A literature review of gene function prediction by modeling gene ontology
Annotating the functional properties of gene products, ie, RNAs and proteins, is a
fundamental task in biology. The Gene Ontology database (GO) was developed to …
fundamental task in biology. The Gene Ontology database (GO) was developed to …
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 …
GANLDA: Graph attention network for lncRNA-disease associations prediction
Increasing studies have indicated that long non-coding RNAs (lncRNAs) play important
roles in many physiological and pathological pathways. Identifying lncRNA-disease …
roles in many physiological and pathological pathways. Identifying lncRNA-disease …
Computational models for lncRNA function prediction and functional similarity calculation
From transcriptional noise to dark matter of biology, the rapidly changing view of long non-
coding RNA (lncRNA) leads to deep understanding of human complex diseases induced by …
coding RNA (lncRNA) leads to deep understanding of human complex diseases induced by …
[HTML][HTML] Graph convolutional network and convolutional neural network based method for predicting lncRNA-disease associations
Aberrant expressions of long non-coding RNAs (lncRNAs) are often associated with
diseases and identification of disease-related lncRNAs is helpful for elucidating complex …
diseases and identification of disease-related lncRNAs is helpful for elucidating complex …
[HTML][HTML] Data resources and computational methods for lncRNA-disease association prediction
N Sheng, L Huang, Y Lu, H Wang, L Yang… - Computers in Biology …, 2023 - Elsevier
Increasing interest has been attracted in deciphering the potential disease pathogenesis
through lncRNA-disease association (LDA) prediction, regarding to the diverse functional …
through lncRNA-disease association (LDA) prediction, regarding to the diverse functional …
GAERF: predicting lncRNA-disease associations by graph auto-encoder and random forest
QW Wu, JF **a, JC Ni, CH Zheng - Briefings in bioinformatics, 2021 - academic.oup.com
Predicting disease-related long non-coding RNAs (lncRNAs) is beneficial to finding of new
biomarkers for prevention, diagnosis and treatment of complex human diseases. In this …
biomarkers for prevention, diagnosis and treatment of complex human diseases. In this …
A random forest based computational model for predicting novel lncRNA-disease associations
D Yao, X Zhan, X Zhan, CK Kwoh, P Li, J Wang - BMC bioinformatics, 2020 - Springer
Background Accumulated evidence shows that the abnormal regulation of long non-coding
RNA (lncRNA) is associated with various human diseases. Accurately identifying disease …
RNA (lncRNA) is associated with various human diseases. Accurately identifying disease …
LncRNA expression profile-based matrix factorization for identifying lncRNA-disease associations
J Ha - IEEE Access, 2024 - ieeexplore.ieee.org
Long non-coding RNAs (lncRNAs) play significant roles in multiple biological processes and
contribute to the progression and development of various human diseases. Therefore, it is …
contribute to the progression and development of various human diseases. Therefore, it is …