Protein interaction networks: centrality, modularity, dynamics, and applications
In the post-genomic era, proteomics has achieved significant theoretical and practical
advances with the development of high-throughput technologies. Especially the rapid …
advances with the development of high-throughput technologies. Especially the rapid …
RNMFLP: predicting circRNA–disease associations based on robust nonnegative matrix factorization and label propagation
Circular RNAs (circRNAs) are a class of structurally stable endogenous noncoding RNA
molecules. Increasing studies indicate that circRNAs play vital roles in human diseases …
molecules. Increasing studies indicate that circRNAs play vital roles in human diseases …
Biomedical data, computational methods and tools for evaluating disease–disease associations
In recent decades, exploring potential relationships between diseases has been an active
research field. With the rapid accumulation of disease-related biomedical data, a lot of …
research field. With the rapid accumulation of disease-related biomedical data, a lot of …
DeepLncLoc: a deep learning framework for long non-coding RNA subcellular localization prediction based on subsequence embedding
Long non-coding RNAs (lncRNAs) are a class of RNA molecules with more than 200
nucleotides. A growing amount of evidence reveals that subcellular localization of lncRNAs …
nucleotides. A growing amount of evidence reveals that subcellular localization of lncRNAs …
End-to-end interpretable disease–gene association prediction
Identifying disease–gene associations is a fundamental and critical biomedical task towards
understanding molecular mechanisms, the diagnosis and treatment of diseases. It is time …
understanding molecular mechanisms, the diagnosis and treatment of diseases. It is time …
DGHNE: network enhancement-based method in identifying disease-causing genes through a heterogeneous biomedical network
The identification of disease-causing genes is critical for mechanistic understanding of
disease etiology and clinical manipulation in disease prevention and treatment. Yet the …
disease etiology and clinical manipulation in disease prevention and treatment. Yet the …
NIDM: network impulsive dynamics on multiplex biological network for disease-gene prediction
The prediction of genes related to diseases is important to the study of the diseases due to
high cost and time consumption of biological experiments. Network propagation is a popular …
high cost and time consumption of biological experiments. Network propagation is a popular …
[HTML][HTML] A knowledge graph-based disease-gene prediction system using multi-relational graph convolution networks
Identifying disease-gene associations is important for understanding molecule mechanisms
of diseases, finding diagnostic markers and therapeutic targets. Many computational …
of diseases, finding diagnostic markers and therapeutic targets. Many computational …
Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation
Non-coding RNAs (ncRNAs), generated from nonprotein coding DNA sequences, constitute
98–99% of the human genome. Non-coding RNAs encompass diverse functional classes …
98–99% of the human genome. Non-coding RNAs encompass diverse functional classes …
The biological processes of ferroptosis involved in pathogenesis of COVID-19 and core ferroptoic genes related with the occurrence and severity of this disease
Z Zhang, T Pang, M Qi, G Sun - Evolutionary Bioinformatics, 2023 - journals.sagepub.com
Background: A worldwide outbreak of coronavirus disease 2019 (COVID-19) has resulted in
millions of deaths. Ferroptosis is a form of iron-dependent cell death which is characterized …
millions of deaths. Ferroptosis is a form of iron-dependent cell death which is characterized …