Detangling PPI Networks to Uncover Functionally Meaningful Clusters

Hall-Swan, Sarah; Crawford, Jake; Newman, Rebecca; Cowen, Lenore

doi:10.1145/3107411.3110409

Cited by 3 publications

(2 citation statements)

References 14 publications

(10 reference statements)

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“…The clustering of protein-protein interaction networks can predict genes and protein modules that function together [25] . As previously reported, basic proteins tend to form highly connected clusters rather than function independently [26] .…”

Section: Discussionmentioning

confidence: 99%

Proteins in cord blood as a new target for prevention and treatment of bronchopulmonary dysplasia: a proteomic analysis

Wang

Mao

Chen

et al. 2021

Preprint

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This study aimed to explore the proteins in cord blood that could regulate the development of neonatal bronchi and lungs, and to find a new target for the prevention and treatment of bronchopulmonary dysplasia (BPD). In this study, proteomic analysis was used to analyze the proteins in cord blood of preterm and term infants. A total of 100 differentially expressed (57 up-regulated and 43 down-regulated) proteins were identified from preterm with BPD and term infants cord blood (fold change ≥ 1.5, P value < 0.05). GO analysis revealed that the major enrichment functions of these differential proteins were multi-organism process, stimulus, immune system process growth, reproductive process, development process and antioxidant activity. The signaling pathways involved included insulin resistance, insulin signaling pathway, IL−17 signaling pathway, PI3K−Akt signaling pathway, NF−kappa B signaling pathway, glucagon signaling pathway, apoptosis, MAPK signaling pathway, as well as glycolysis/gluconeogenesis. Further protein and protein interact (PPI) analysis revealed that the interacting proteins involved were PGAM1, CNN2, HSP90AA and DAG1, which were all crucial in the development of BPD. We found that these differential proteins in cord blood might regulate bronchopulmonary development through the abovementioned signaling pathways or their interaction proteins, which may provide a new research direction for the intervention of BPD.

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Section: Discussionmentioning

confidence: 99%

Proteins in cord blood as a new target for prevention and treatment of bronchopulmonary dysplasia: a proteomic analysis

Wang

Mao

Chen

et al. 2021

Preprint

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show abstract

“…Module prediction and identifying non-overlapping clusters with the PPI remains challenging since the PPI network has a short diameter, i.e., most nodes are close to all other nodes in terms of network distance. Novel distance metrics and community detection algorithms have been proposed to overcome this problem (Hall-Swan et al, 2018). The recently proposed DIseAse MOdule Detection (DIAMOnD) algorithm (Ghiassian et al, 2015) associates the functional modules of known disease-associated proteins (seed proteins) and identifies the close neighbors of these genes (candidate disease-associated proteins) using topological properties of the interactome.…”

Section: Paradigm I: Network-based Approach To Human Disease Using Th...mentioning

confidence: 99%

Network Medicine in the Age of Biomedical Big Data

et al. 2019

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Network medicine is an emerging area of research dealing with molecular and genetic interactions, network biomarkers of disease, and therapeutic target discovery. Large-scale biomedical data generation offers a unique opportunity to assess the effect and impact of cellular heterogeneity and environmental perturbations on the observed phenotype. Marrying the two, network medicine with biomedical data provides a framework to build meaningful models and extract impactful results at a network level. In this review, we survey existing network types and biomedical data sources. More importantly, we delve into ways in which the network medicine approach, aided by phenotype-specific biomedical data, can be gainfully applied. We provide three paradigms, mainly dealing with three major biological network archetypes: protein-protein interaction, expression-based, and gene regulatory networks. For each of these paradigms, we discuss a broad overview of philosophies under which various network methods work. We also provide a few examples in each paradigm as a test case of its successful application. Finally, we delineate several opportunities and challenges in the field of network medicine. We hope this review provides a lexicon for researchers from biological sciences and network theory to come on the same page to work on research areas that require interdisciplinary expertise. Taken together, the understanding gained from combining biomedical data with networks can be useful for characterizing disease etiologies and identifying therapeutic targets, which, in turn, will lead to better preventive medicine with translational impact on personalized healthcare.

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ELSNC: A semi-supervised community detection method with integration of embedding-enhanced links and node content in attributed networks

Cao,

Zou,

et al. 2024

Applied Soft Computing

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Detangling PPI Networks to Uncover Functionally Meaningful Clusters

Cited by 3 publications

References 14 publications

Proteins in cord blood as a new target for prevention and treatment of bronchopulmonary dysplasia: a proteomic analysis

Proteins in cord blood as a new target for prevention and treatment of bronchopulmonary dysplasia: a proteomic analysis

Network Medicine in the Age of Biomedical Big Data

ELSNC: A semi-supervised community detection method with integration of embedding-enhanced links and node content in attributed networks

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