ArticleBMC genomics2013
Interfacing cellular networks of S. cerevisiae and E. coli: connecting dynamic and genetic information.
Article in BMC genomics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- The role of replication-induced chromosomal copy numbers in spatio-temporal gene regulation and evolutionary chromosome plasticity.Frontiers in microbiology · 2023Article
- Identification of the Transcriptional Regulatory Role of RUNX2 by Network Analysis in Lung Cancer Cells.Biomedicines · 2022Article
- ModularBoost: an efficient network inference algorithm based on module decomposition.BMC bioinformatics · 2021Article
- Unraveling Root Development Through Single-Cell Omics and Reconstruction of Gene Regulatory Networks.Frontiers in plant science · 2021Review
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- Network inference in systems biology: recent developments, challenges, and applications.Current opinion in biotechnology · 2020Review
- Prostate Cancer Gene Regulatory Network Inferred from RNA-Seq Data.Current genomics · 2019Article
- Harnessing the biological complexity of Big Data from LINCS gene expression signatures.PloS one · 2018Article
- Identification of marginal causal relationships in gene networks from observational and interventional expression data.PloS one · 2017Article
- Urothelial cancer gene regulatory networks inferred from large-scale RNAseq, Bead and Oligo gene expression data.BMC systems biology · 2015Article
- Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data.Current genomics · 2015Article
- Protein complexes in bacteria.PLoS computational biology · 2015Article
- The gene regulatory network for breast cancer: integrated regulatory landscape of cancer hallmarks.Frontiers in genetics · 2014Article
- Gene regulatory networks and their applications: understanding biological and medical problems in terms of networks.Frontiers in cell and developmental biology · 2014Review
- Untangling statistical and biological models to understand network inference: the need for a genomics network ontology.Frontiers in genetics · 2014Article
- Functional and genetic analysis of the colon cancer network.BMC bioinformatics · 2014Article
- B-cell lymphoma gene regulatory networks: biological consistency among inference methods.Frontiers in genetics · 2013Article
- Enhancing systems medicine beyond genotype data by dynamic patient signatures: having information and using it too.Frontiers in genetics · 2013Article
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Authors and funding
3 authors.
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Abstract
backgroundIn recent years, various types of cellular networks have penetrated biology and are nowadays used omnipresently for studying eukaryote and prokaryote organisms. Still, the relation and the biological overlap among phenomenological and inferential gene networks, e.g., between the protein interaction network and the gene regulatory network inferred from large-scale transcriptomic data, is largely unexplored.
resultsWe provide in this study an in-depth analysis of the structural, functional and chromosomal relationship between a protein-protein network, a transcriptional regulatory network and an inferred gene regulatory network, for S. cerevisiae and E. coli. Further, we study global and local aspects of these networks and their biological information overlap by comparing, e.g., the functional co-occurrence of Gene Ontology terms by exploiting the available interaction structure among the genes.
conclusionsAlthough the individual networks represent different levels of cellular interactions with global structural and functional dissimilarities, we observe crucial functions of their network interfaces for the assembly of protein complexes, proteolysis, transcription, translation, metabolic and regulatory interactions. Overall, our results shed light on the integrability of these networks and their interfacing biological processes.
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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.