With the advancements of high-throughput sequencing technology, several recent studies addressed the clinical/phenotypic stratification of samples by utilizing transcriptome data. However, existing stratification meth...
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Recent algorithmic advances in electrocardiogram (ECG) classification are largely contributed to deep learning. However, these methods are still based on a relatively straightforward application of deep neural network...
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ISBN:
(数字)9781728173825
ISBN:
(纸本)9781728111056
Recent algorithmic advances in electrocardiogram (ECG) classification are largely contributed to deep learning. However, these methods are still based on a relatively straightforward application of deep neural networks (DNNs), which leaves incredible room for improvement. In this paper, as part of the PhysioNet / Computing in Cardiology Challenge 2020, we developed an 18-layer residual convolutional neural network to classify clinical cardiac abnormalities from 12-lead ECG recordings. We focused on examining a collection of data pre-processing, model architecture, training, and post-training procedure refinements for DNN-based ECG classification. We showed that by combining these refinements, we can improve the classification performance significantly. Our team, DSAIL_SNU, obtained a 0.695 challenge score using 10-fold cross-validation, and a 0.420 challenge score on the full test data, placing us 6th in the official ranking.
Summary: In this article, we propose a new method named fused mixed graphical model (FMGM), which can infer network structures for dichotomous phenotypes. We assumed that the interplay of different omics markers is as...
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Breast cancer is classified into five intrinsic subtypes, with differing treatment methods and prognoses. Therefore, accurate identification of subtypes from patient transcriptome data is essential. Many gene signatur...
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ISBN:
(纸本)9781665429825
Breast cancer is classified into five intrinsic subtypes, with differing treatment methods and prognoses. Therefore, accurate identification of subtypes from patient transcriptome data is essential. Many gene signatures, including PAM50, have been developed to classify breast cancer subtypes. However, existing gene selection methods do not utilize biological pathways. Gene signature selection using biological pathways can explain signature genes in terms of biological functions. Thus, we propose a probabilistic model for pathway-guided gene set selection using gene expression data. First, we defined gene and pathway factors based on gene expression and pathway activation levels, and calculated the posterior probability. Second, we adopted the prediction strength to guide gene set selection. Third, the gene set was selected using the posterior probability and prediction strength values. Finally, on evaluating the selected gene set, it was experimentally confirmed that our gene set performed better on classification tasks than the PAM50 gene set, a gene set produced by the XGBoost classifier, and a random gene set. Among the genes selected by our method, it was confirmed that the genes included in the cell cycle and circadian rhythm pathways showed different expression patterns for each breast cancer subtype. Our selected gene set exhibited biological significance in terms of pathway activation.
Recently, graph neural networks (GNNs) have been widely used for document classification. However, most existing methods are based on static word co-occurrence graphs without sentence-level information, which poses th...
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Emerging evidence suggests expression from human endogenous retrovirus (HERV) loci likely contributes to, or is a biomarker of, glioblastoma multiforme (GBM) disease progression. However, the relationship between HERV...
In genome era,average nucleotide identity(ANI)is the "gold standard" of prokaryotic taxonomy to delineation of *** is a mean of nucleotide identity between conserved regions shared by two *** introdu...
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In genome era,average nucleotide identity(ANI)is the "gold standard" of prokaryotic taxonomy to delineation of *** is a mean of nucleotide identity between conserved regions shared by two *** introduction of a DNA-DNA hybridization(DDH)value of 70%as the threshold for the microbial species boundary,95-96%of ANI values which correlate well with the thresholdis a robust measure of evolutionary *** is an issue,however,which difference between identities of query genome to reference genomeeould be a serious problem in the calculation of the mean *** average nucleotide identities of 63,690 genome pairs with 14,745 strains in 10 big *** study found over 55%of total samples got more than 0.1%difference,and up to 1,101 genome pairs got difference not less than 1%.We develop a new method that similar with ANI algorithm to calculate identity between sets of truly orthologous sequences shared by two microbial *** our study,we introduce modified ANI algorithm as name of *** identity of nucleotide calculated via new algorithm hadone ANI value through tested version that had a 0.00042%average discrepancy between bidirectional calculations.
Backgrounds & Aims: Since the Omicron variant emerged as a major severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant, COVID-19-associated mortality has decreased remarkably. Nevertheless, patients...
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Psoriasis is well known as a chronic inflammatory dermatosis. The disease affects persons of all ages and is a burden worldwide. Psoriasis is associated with various diseases such as arthritis. The disease is characte...
Recent advances in next-generation sequencing technologies have facilitated the use of deoxyribonucleic acid (DNA) as a novel covert channels in steganography. There are vari-ous methods that exist in other domains to...
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