ArticleJournal of computational biology : a journal of computational molecular cell biology2010
Cross species expression analysis of innate immune response.
Article in Journal of computational biology : a journal of computational molecular cell biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
The trial behind it
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
6 citing papers in PubMed, 18 citations in OpenAlex.
- Improved integration of single-cell transcriptome data demonstrates common and unique signatures of heart failure in mice and humans.GigaScience · 2024Article
- CoSIA: an R Bioconductor package for CrOss Species Investigation and Analysis.Bioinformatics (Oxford, England) · 2023Article
- CoSIA: an R Bioconductor package for CrOss Species Investigation and Analysis.bioRxiv : the preprint server for biology · 2023Article
- A statistical normalization method and differential expression analysis for RNA-seq data between different species.BMC bioinformatics · 2019Article
- A novel method for cross-species gene expression analysis.BMC bioinformatics · 2013Article
- Cross-species transcriptional network analysis defines shared inflammatory responses in murine and human lupus nephritis.Journal of immunology (Baltimore, Md. : 1950) · 2012Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
The innate immune response is the first line of host defense against infections. This system employs a number of different types of cells, which in turn activate different sets of genes. Microarray studies of human and mouse cells infected with various pathogens identified hundreds of differentially expressed genes. However, combining these datasets to identify common and unique response patterns remained a challenge. We developed methods based on probabilistic graphical models to combine expression experiments across species, cells, and pathogens. Our method analyzes homologous genes in different species concurrently overcoming problems related to noise and orthology assignments. Using our method, we identified both core immune response genes and genes that are activated in macrophages in both human and mouse but not in dendritic cells, and vice versa. Our results shed light on immune response mechanisms and on the differences between various types of cells that are used to fight infecting bacteria. For supporting website, see www.cs.cmu.edu/-lyongu/pub/immune/.
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What OpenQuestion holds
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.