Spectrum of orocutaneous disease associations: Genodermatoses and inflammatory conditions.
Sign Up to like & getrecommendations! Published in 2017 at "Journal of the American Academy of Dermatology"
DOI: 10.1016/j.jaad.2017.02.017
Abstract: The oral cavity and cutaneous organ systems share a close embryologic origin. Therefore, there are numerous dermatologic conditions presenting with concomitant oral findings of which the dermatologist must be aware. The second article in this… read more here.
Keywords: genodermatoses inflammatory; disease associations; associations genodermatoses; inflammatory conditions ... See more keywords
A novel approach for predicting microRNA-disease associations by unbalanced bi-random walk on heterogeneous network
Sign Up to like & getrecommendations! Published in 2017 at "Journal of biomedical informatics"
DOI: 10.1016/j.jbi.2017.01.008
Abstract: MicroRNAs (miRNAs) play a critical role by regulating their targets in post-transcriptional level. Identification of potential miRNA-disease associations will aid in deciphering the pathogenesis of human polygenic diseases. Several computational models have been developed to… read more here.
Keywords: heterogeneous network; network; unbalanced random; disease associations ... See more keywords
Predicting CircRNA Disease Associations using Novel Node Classification and Link Prediction Models on Graph Convolutional Networks.
Sign Up to like & getrecommendations! Published in 2021 at "Methods"
DOI: 10.1016/j.ymeth.2021.10.008
Abstract: Accumulated studies have discovered that circular RNAs (CircRNAs) are closely related to many complex human diseases. Due to this close relationship, CircRNAs can be used as good biomarkers for disease diagnosis and therapeutic targets for… read more here.
Keywords: circrna disease; disease associations; prediction models; prediction ... See more keywords
Novel human microbe-disease associations inference based on network consistency projection
Sign Up to like & getrecommendations! Published in 2018 at "Scientific Reports"
DOI: 10.1038/s41598-018-26448-8
Abstract: Increasing evidence shows that microbes are closely related to various human diseases. Obtaining a comprehensive and detailed understanding of the relationships between microbes and diseases would not only be beneficial to disease prevention, diagnosis and… read more here.
Keywords: network; disease associations; disease; projection ... See more keywords
Discovering disease-disease associations using electronic health records in The Guideline Advantage (TGA) dataset.
Sign Up to like & getrecommendations! Published in 2021 at "Scientific reports"
DOI: 10.1038/s41598-021-00345-z
Abstract: Certain diseases have strong comorbidity and co-occurrence with others. Understanding disease-disease associations can potentially increase awareness among healthcare providers of co-occurring conditions and facilitate earlier diagnosis, prevention and treatment of patients. In this study, we… read more here.
Keywords: advantage tga; disease associations; electronic health; disease ... See more keywords
Predicting drug-disease associations with heterogeneous network embedding.
Sign Up to like & getrecommendations! Published in 2019 at "Chaos"
DOI: 10.1063/1.5121900
Abstract: The prediction of drug-disease associations holds great potential for precision medicine in the era of big data and is important for the identification of new indications for existing drugs. The associations between drugs and diseases… read more here.
Keywords: drug; heterogeneous network; disease associations; drug disease ... See more keywords
Predicting microRNA-disease associations using bipartite local models and hubness-aware regression
Sign Up to like & getrecommendations! Published in 2018 at "RNA Biology"
DOI: 10.1080/15476286.2018.1517010
Abstract: ABSTRACT The development and progression of numerous complex human diseases have been confirmed to be associated with microRNAs (miRNAs) by various experimental and clinical studies. Predicting potential miRNA-disease associations can help us understand the underlying… read more here.
Keywords: disease associations; disease; model; bipartite local ... See more keywords
A graph auto-encoder model for miRNA-disease associations prediction
Sign Up to like & getrecommendations! Published in 2021 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbaa240
Abstract: Emerging evidence indicates that the abnormal expression of miRNAs involves in the evolution and progression of various human complex diseases. Identifying disease-related miRNAs as new biomarkers can promote the development of disease pathology and clinical… read more here.
Keywords: encoder; disease associations; disease; model ... See more keywords
GAERF: predicting lncRNA-disease associations by graph auto-encoder and random forest
Sign Up to like & getrecommendations! Published in 2021 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbaa391
Abstract: 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 paper, we proposed a machine learning techniques-based classification approach to identify… read more here.
Keywords: auto encoder; lncrna disease; disease associations; disease ... See more keywords
A weighted bilinear neural collaborative filtering approach for drug repositioning
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbab581
Abstract: Drug repositioning is an efficient and promising strategy for traditional drug discovery and development. Many research efforts are focused on utilizing deep-learning approaches based on a heterogeneous network for modeling complex drug-disease associations. Similar to… read more here.
Keywords: drug repositioning; disease; drug disease; disease associations ... See more keywords
Biomedical data, computational methods and tools for evaluating disease-disease associations
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbac006
Abstract: 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 computational methods and tools/platforms have been developed to reveal intrinsic… read more here.
Keywords: computational methods; disease disease; disease associations; biomedical data ... See more keywords