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zadetkov: 141
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  • INDEED: Integrated differen... INDEED: Integrated differential expression and differential network analysis of omic data for biomarker discovery
    Zuo, Yiming; Cui, Yi; Di Poto, Cristina ... Methods (San Diego, Calif.), 12/2016, Letnik: 111
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    •INDEED integrates differential expression & network analyses for biomarker discovery.•INDEED builds sparse network based on partial correlation for better visualization.•INDEED’s performance in ...
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42.
  • A pseudo-value regression a... A pseudo-value regression approach for differential network analysis of co-expression data
    Ahn, Seungjun; Grimes, Tyler; Datta, Somnath BMC bioinformatics, 01/2023, Letnik: 24, Številka: 1
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    The differential network (DN) analysis identifies changes in measures of association among genes under two or more experimental conditions. In this article, we introduce a pseudo-value regression ...
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43.
  • Comparative assessment of d... Comparative assessment of differential network analysis methods
    Lichtblau, Yvonne; Zimmermann, Karin; Haldemann, Berit ... Briefings in bioinformatics, 09/2017, Letnik: 18, Številka: 5
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    Abstract Differential network analysis (DiNA) denotes a recent class of network-based Bioinformatics algorithms which focus on the differences in network topologies between two states of a cell, such ...
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44.
  • Discovery of pan-cancer rel... Discovery of pan-cancer related genes via integrative network analysis
    Zhu, Yuan; Zhang, Houwang; Yang, Yuanhang ... Briefings in functional genomics, 07/2022, Letnik: 21, Številka: 4
    Journal Article

    Abstract Identification of cancer-related genes is helpful for understanding the pathogenesis of cancer, developing targeted drugs and creating new diagnostic and therapeutic methods. Considering the ...
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45.
  • Plasma and Serum Metabolite... Plasma and Serum Metabolite Association Networks: Comparability within and between Studies Using NMR and MS Profiling
    Suarez-Diez, Maria; Adam, Jonathan; Adamski, Jerzy ... Journal of proteome research, 07/2017, Letnik: 16, Številka: 7
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    Blood is one of the most used biofluids in metabolomics studies, and the serum and plasma fractions are routinely used as a proxy for blood itself. Here we investigated the association networks of an ...
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46.
  • Identifying network biomark... Identifying network biomarkers of cancer by sample-specific differential network
    Zhang, Yu; Chang, Xiao; Xia, Jie ... BMC bioinformatics, 06/2022, Letnik: 23, Številka: 1
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    Abundant datasets generated from various big science projects on diseases have presented great challenges and opportunities, which contributed to unfolding the complexity of diseases. The discovery ...
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47.
  • Efficient computation for d... Efficient computation for differential network analysis with applications to quadratic discriminant analysis
    Pan, Yuqing; Mai, Qing Computational statistics & data analysis, April 2020, 2020-04-00, Letnik: 144
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    Differential network analysis is an important statistical problem with wide applications. Many statisticians focus on binary problems and propose to perform such analysis by obtaining sparse ...
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48.
  • PRANA: an R package for dif... PRANA: an R package for differential co-expression network analysis with the presence of additional covariates
    Ahn, Seungjun; Datta, Somnath BMC genomics, 11/2023, Letnik: 24, Številka: 1
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    Advances in sequencing technology and cost reduction have enabled an emergence of various statistical methods used in RNA-sequencing data, including the differential co-expression network analysis ...
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50.
  • Estimating differential lat... Estimating differential latent variable graphical models with applications to brain connectivity
    Na, S; Kolar, M; Koyejo, O Biometrika, 06/2021, Letnik: 108, Številka: 2
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    Summary Differential graphical models are designed to represent the difference between the conditional dependence structures of two groups, and thus are of particular interest for scientific ...
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