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iOmicsPASS: a novel method for integration of multi-omics data over biological networks and discovery of predictive subnetworks

https://doi.org/10.1101/374520
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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The CPTAC Data Portal: A Resource for Cancer Proteomics Research
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Gene Ontology: tool for the unification of biology
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MCM2: An alternative to Ki-67 for measuring breast cancer cell proliferation
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The consensus molecular subtypes of colorectal cancer
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TRRUST: a reference database of human transcriptional regulatory interactions
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Comparison of DNA Quantification Methods for Next Generation Sequencing
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Molecular subclasses of breast cancer: how do we define them? The IMPAKT 2012 Working Group Statement
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Inference of patient-specific pathway activities from multi-dimensional cancer genomics data using PARADIGM
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TRED: a Transcriptional Regulatory Element Database and a platform for in silico gene regulation studies
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From micrograms to picograms: quantitative PCR reduces the material demands of high-throughput sequencing
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ConsensusPathDB: toward a more complete picture of cell biology
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iRefIndex: A consolidated protein interaction database with provenance
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ATHENA: Identifying interactions between different levels of genomic data associated with cancer clinical outcomes using grammatical evolution neural network
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Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes
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Patient-Specific Data Fusion Defines Prognostic Cancer Subtypes
inferredcites →https://doi.org/10.1371/journal.pcbi.1003983openalex-snapshot
Integrative Multi-omics Module Network Inference with Lemon-Tree
inferredcites →https://doi.org/10.2174/138920207780076938openalex-snapshot
Ribosomal Proteins and Colorectal Cancer
inferredcites →https://doi.org/10.3389/fgene.2017.00084openalex-snapshot
More Is Better: Recent Progress in Multi-Omics Data Integration Methods
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What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/9781119865728.ch7openalex-snapshot
Clinical Applications of “Omics” Technology as a Bioinformatic Tool
inferred← citeshttps://doi.org/10.1007/s12032-025-02945-5openalex-snapshot
Metabolic reprogramming and functional crosstalk within the tumor microenvironment (TME) and A Multi-omics anticancer approach
inferred← citeshttps://doi.org/10.1016/j.biotechadv.2025.108691openalex-snapshot
The stressing point: how plants respond to environmental stimuli
inferred← citeshttps://doi.org/10.1016/j.gene.2023.147246openalex-snapshot
LaCOme: Learning the latent convolutional patterns among transcriptomic features to improve classifications
inferred← citeshttps://doi.org/10.1109/tcbb.2020.3008196openalex-snapshot
Personalized Metabolic Analysis of Diseases
inferred← citeshttps://doi.org/10.3389/fbioe.2021.613307openalex-snapshot
Omics-Driven Biotechnology for Industrial Applications
inferred← citeshttps://doi.org/10.3389/fphys.2019.00379openalex-snapshot
Plasma Protein and MicroRNA Biomarkers of Insulin Resistance: A Network-Based Integrative -Omics Analysis
inferred← citeshttps://doi.org/10.3390/metabo9040076openalex-snapshot
Systems Biology and Multi-Omics Integration: Viewpoints from the Metabolomics Research Community
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