ReviewEURASIP journal on bioinformatics & systems biology2017
From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.
Review in EURASIP journal on bioinformatics & systems biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
51 citing papers in PubMed, 102 citations in OpenAlex.
- Proteome analyses reveal endoplasmic reticulum stress-induced changes in protein abundance associated with Ube2j2 deficiency in human cell culture.G3 (Bethesda, Md.) · 2026Article
- When normalization induces correlation: shared and unstable references can create hidden dependencies.NPJ systems biology and applications · 2026Article
- Identifying ICAM-1 as a Therapeutic Target for Cytokine Storm in Human Macrophages Through Integrative Bioinformatics Approaches.Molecules (Basel, Switzerland) · 2026Article
- A network-guided penalized regression with application to proteomics data.Bioinformatics advances · 2026Article
- A Holistic Investigation of Arabidopsis Proteomes Altered in Chloroplast Biogenesis and Retrograde Signalling Identifies PsbO as a Key Regulator of Chloroplast Quality Control.Plant, cell & environment · 2025Article
- Proteomic insights into the environmental adaptation of the subtropical brain coral hostiScience · 2025Article
- CoPPIs algorithm: a tool to unravel protein cooperative strategies in pathophysiological conditions.Briefings in bioinformatics · 2025Article
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- Computational Tools and Methods for the Study of Systemic Amyloidosis at the Clinical and Molecular Level.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Unveiling Biomarkers in Head and Neck Squamous Cell Carcinoma through Bioinformatics: The Role ofInternational journal of molecular sciences · 2024Article
- Network analysis of the proteome and peptidome sheds light on human milk as a biological system.Scientific reports · 2024Article
- A machine learning based approach to identify carotid subclinical atherosclerosis endotypes.Cardiovascular research · 2023Article
- Article
- Review
- Uncovering Protein Networks in Cardiovascular Proteomics.Molecular & cellular proteomics : MCP · 2023Review
- Bioinformatic Analysis of Key Regulatory Genes in Adult Asthma and Prediction of Potential Drug Candidates.Molecules (Basel, Switzerland) · 2023Article
- The Protein Network in Subcutaneous Fat Biopsies from Patients with AL Amyloidosis: More Than Diagnosis?Cells · 2023Article
- Evidence and Metabolic Implications for a New Non-Canonical Role of Cu-Zn Superoxide Dismutase.International journal of molecular sciences · 2023Article
- The proteome and phosphoproteome of circulating extracellular vesicle-enriched preparations are associated with characteristic clinical features in type 1 diabetes.Frontiers in endocrinology · 2023Article
- Protocol to analyze dysregulation of the eIF4F complex in human cancers using R software and large public datasets.STAR protocols · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.