ArticleBMC genomics2012
GeneFriends: an online co-expression analysis tool to identify novel gene targets for aging and complex diseases.
Article in BMC genomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.
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Who cites it
50 citing papers in PubMed, 77 citations in OpenAlex.
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- Evolution, structure and emerging roles of C1ORF112 in DNA replication, DNA damage responses, and cancer.Cellular and molecular life sciences : CMLS · 2021Review
- K-Module Algorithm: An Additional Step to Improve the Clustering Results of WGCNA Co-Expression Networks.Genes · 2021Article
- Pan-Cancer Analysis IdentifiedFrontiers in molecular biosciences · 2021Article
- High Expression of C1ORF112 Predicts a Poor Outcome: A Potential Target for the Treatment of Low-Grade Gliomas.Frontiers in genetics · 2021Article
- Comprehensive analysis of transcriptome data stemness indices identifies key genes for controlling cancer stem cell characteristics in gastric cancer.Translational cancer research · 2020Article
- CoCoCoNet: conserved and comparative co-expression across a diverse set of species.Nucleic acids research · 2020Article
- Comparative Transcriptome Analysis of DifferentInternational journal of molecular sciences · 2020Article
- Overexpression of PARPBP Correlates with Tumor Progression and Poor Prognosis in Hepatocellular Carcinoma.Digestive diseases and sciences · 2019Article
- GEF-H1 Signaling upon Microtubule Destabilization Is Required for Dendritic Cell Activation and Specific Anti-tumor Responses.Cell reports · 2019Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
backgroundAlthough many diseases have been well characterized at the molecular level, the underlying mechanisms are often unknown. Nearly half of all human genes remain poorly studied, yet these genes may contribute to a number of disease processes. Genes involved in common biological processes and diseases are often co-expressed. Using known disease-associated genes in a co-expression analysis may help identify and prioritize novel candidate genes for further study.
resultsWe have created an online tool, called GeneFriends, which identifies co-expressed genes in over 1,000 mouse microarray datasets. GeneFriends can be used to assign putative functions to poorly studied genes. Using a seed list of disease-associated genes and a guilt-by-association method, GeneFriends allows users to quickly identify novel genes and transcription factors associated with a disease or process. We tested GeneFriends using seed lists for aging, cancer, and mitochondrial complex I disease. We identified several candidate genes that have previously been predicted as relevant targets. Some of the genes identified are already being tested in clinical trials, indicating the effectiveness of this approach. Co-expressed transcription factors were investigated, identifying C/ebp genes as candidate regulators of aging. Furthermore, several novel candidate genes, that may be suitable for experimental or clinical follow-up, were identified. Two of the novel candidates of unknown function that were co-expressed with cancer-associated genes were selected for experimental validation. Knock-down of their human homologs (C1ORF112 and C12ORF48) in HeLa cells slowed growth, indicating that these genes of unknown function, identified by GeneFriends, may be involved in cancer.
conclusionsGeneFriends is a resource for biologists to identify and prioritize novel candidate genes involved in biological processes and complex diseases. It is an intuitive online resource that will help drive experimentation. GeneFriends is available online at: http://genefriends.org/.
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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.