Search Results - "multi-omics integration algorithms"

Benchmarking multi-omics integration algorithms across single-cell RNA and ATAC data by Xiao, Chuxi, Chen, Yixin, Meng, Qiuchen, Wei, Lei, Zhang, Xuegong

“…Abstract Recent advancements in single-cell sequencing technologies have generated extensive omics data in various modalities and revolutionized cell research,…”
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Guide to Metabolomics Analysis: A Bioinformatics Workflow by Chen, Yang, Li, En-Min, Xu, Li-Yan

“…Metabolomics is an emerging field that quantifies numerous metabolites systematically. The key purpose of metabolomics is to identify the metabolites…”
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Benchmarking multi-omics integration algorithms across single-cell RNA and ATAC data by Xiao, Chuxi, Chen, Yixin, Wei, Lei, Zhang, Xuegong

“…Recent advancements in single-cell sequencing technologies have generated extensive omics data in various modalities and revolutionized cell research,…”
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Benchmarking algorithms for single-cell multi-omics prediction and integration by Hu, Yinlei, Wan, Siyuan, Luo, Yuanhanyu, Li, Yuanzhe, Wu, Tong, Deng, Wentao, Jiang, Chen, Jiang, Shan, Zhang, Yueping, Liu, Nianping, Yang, Zongcheng, Chen, Falai, Li, Bin, Qu, Kun

“… Here, we present a benchmark study of 14 protein abundance/chromatin accessibility prediction algorithms and 18 single-cell multi-omics integration algorithms using 47 single-cell multi-omics datasets…”
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A denoised multi-omics integration framework for cancer subtype classification and survival prediction by Pang, Jiali, Liang, Bilin, Ding, Ruifeng, Yan, Qiujuan, Chen, Ruiyao, Xu, Jie

“…Abstract The availability of high-throughput sequencing data creates opportunities to comprehensively understand human diseases as well as challenges to train…”
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Integrative multi‐omic and machine learning approach for prognostic stratification and therapeutic targeting in lung squamous cell carcinoma by Zhang, Xiao, Zhang, Pengpeng, Ren, Qianhe, Li, Jun, Lin, Haoran, Huang, Yuming, Wang, Wei

“…‐omics integration algorithms. Subsequently, we employed 10 commonly used machine learning algorithms, combining them into 101…”
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Integrating transcriptomics and proteomics to analyze the immune microenvironment of cytomegalovirus associated ulcerative colitis and identify relevant biomarkers by Chen, Yang, Zheng, Qingqing, Wang, Hui, Tang, Peiren, Deng, Li, Li, Pu, Li, Huan, Hou, Jianhong, Li, Jie, Wang, Li, Peng, Jun

“…Background In recent years, significant morbidity and mortality in patients with severe inflammatory bowel disease (IBD) and cytomegalovirus (CMV) have drawn…”
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Cancer molecular subtyping using limited multi-omics data with missingness by Bu, Yongqi, Liang, Jiaxuan, Li, Zhen, Wang, Jianbo, Wang, Jun, Yu, Guoxian

“…Diagnosing cancer subtypes is a prerequisite for precise treatment. Existing multi-omics data fusion-based diagnostic solutions build on the requisite of…”
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scME: A Dual-Modality Factor Model for Single-Cell Multi-Omics Embedding by Zhou, Bin, Yang, Fan, Zeng, Feng

“… Our results demonstrate that scME can generate a better joint representation of multiple modalities than those generated by other single-cell multi-omics integration algorithms, which gives a clear…”
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Multi-Omics Modelling to Identify Actionable Targets in Epithelial Ovarian Cancer by Meeson, Kate E

“…Constraint-based modelling is a powerful technology, which can reconstitute the metabolism of an organism through the integration of omics data with a…”
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