The process of splicing messenger RNA to remove introns plays a central role in creating genes and gene variants. We describe Splam, a novel method for predicting splice junctions in DNA using deep residual convolutional neural networks. Unlike previous models, Splam looks at a 400-base-pair window flanking each splice site, reflecting the biological splicing process that relies primarily on signals within this window.
View Article and Find Full Text PDFAs the number and variety of assembled genomes continues to grow, the number of annotated genomes is falling behind, particularly for eukaryotes. DNA-based mapping tools help to address this challenge, but they are only able to transfer annotation between closely-related species. Here we introduce LiftOn, a homology-based software tool that integrates DNA and protein alignments to enhance the accuracy of genome-scale annotation and to allow mapping between relatively distant species.
View Article and Find Full Text PDFThe process of splicing messenger RNA to remove introns plays a central role in creating genes and gene variants. Here we describe Splam, a novel method for predicting splice junctions in DNA based on deep residual convolutional neural networks. Unlike some previous models, Splam looks at a relatively limited window of 400 base pairs flanking each splice site, motivated by the observation that the biological process of splicing relies primarily on signals within this window.
View Article and Find Full Text PDFMany protein biomarkers are present in biofluids at a very low level but may play critical roles in important biological processes. The fact that these low-abundance proteins remain largely unexplored underscores the importance of developing new tools for highly sensitive protein detection. Although digital enzyme-linked immunosorbent assay (ELISA) has demonstrated ultrahigh sensitivity compared with conventional ELISA, the requirement of specialized instruments limits the accessibility and prevents the widespread implementation.
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