• A disease-related gene mining method based on weakly supervised learning model

    9 days ago - By BMC Bioinformatics

    Predicting disease-related genes is helpful for understanding the disease pathology and the molecular mechanisms during the disease progression. However, traditional methods are not suitable for screening gene...
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  • MS/MS in silico subtraction-based proteomic profiling as an approach to facilitate disease gene discovery: application to lens development and cataract

    9 days ago - By Springer

    Abstract
    While the bioinformatics resource-tool iSyTE (integrated Systems Tool for Eye gene discovery) effectively identifies human cataract-associated genes, it is currently based on just transcriptome data, and thus, it is necessary to include protein-level information to gain greater confidence in gene prioritization. Here, we expand iSyTE through development of a novel proteome-based resource on the lens and demonstrate its utility in cataract gene discovery. We applied high-throughput tandem mass spectrometry to generate a global protein expression profile of mouse lens at embryonic...
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  • A novel target convergence set based random walk with restart for prediction of potential LncRNA-disease associations

    9 days ago - By Springer

    Abstract
    Background
    In recent years, lncRNAs have been proved to be closely related to the occurrence and development of many serious diseases that are seriously harmful to human health. However, most of the lncRNA-disease associations have not been found yet due to high costs and time complexity of traditional bio-experiments. Hence, it is quite urgent and necessary to establish efficient and reasonable computational models to predict potential associations between lncRNAs and diseases.
    Results
    In this manuscript, a novel prediction model called TCSRWRLD is proposed to predict potential...
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