A physical and regulatory map of host-influenza interactions reveals pathways in H1N1 infection.
By S. Shapira, Irit Gat-Viks, Bennett O. V. Shum, Amélie Dricot, Marciela M de Grace, Liguo Wu, Piyush B. Gupta, Tong Hao, S. Silver, D. Root and 3 more. Cell, 2009
685 citations recorded by the source corpus.
Subfields: Epidemiology, Infectious Diseases
View Paper: https://www.semanticscholar.org/paper/7b9ae83c89ceabf0c53a198b9abb1e4a4c67b3d5
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Citations in the corpus
- Meta- and Orthogonal Integration of Influenza “OMICs” Data Defines a Role for UBR4 in Virus Budding (2015, methodology): “Three IAV interactomes were integrated: (1) Yeast-two-hybrid data from Shapira et al. (2009), (2) APMS data confirmed by RNAi from Watanabe et al. (2014), (3) APMS data generated in this study with a MIST score cutoff of ≥0.7 or a top 5% ComPASS score (see Experimental Procedures).”
- Studying and modelling dynamic biological processes using time-series gene expression data (2012, methodology): “A heuristic, ad-hoc solution that is commonly used 37,38 is to require that at least two consecutive points are above a chosen fold change in order to declare a gene as differentially expressed (FIG.”
- Interactome3D: adding structural details to protein networks (2013, methodology): “The parameter α is used to balance the contribution of the two terms (sequence identity and coverage) and is selected on the basis of empirical observations (see equation (2) later in this section for further details).”
- Global landscape of HIV–human protein complexes (2011, methodology): “Although two-hybrid methodologies have been used to systematically study host–pathogen interaction”
- A promoter-level mammalian expression atlas (2014, background): “Four of the remaining genes ( TRIM21, TRIM22, RTP4 and XAF1 ) were found to be key host determinants of influenza virus replication in a high-throughput short interfering RNA (siRNA) screen 54 , whereas another, PLSCR1 , is required for a normal interferon response to influenza A 55 .”
- Virus-Plus-Susceptibility Gene Interaction Determines Crohn’s Disease Gene Atg16L1 Phenotypes in Intestine (2010, background): “Interestingly, the Crohn’s disease associated gene NOD2 may recognize viral RNA in addition to bacterial peptidoglycan (Sabbah et al., 2009; Shapira et al., 2009), raising the possibility that a viral infection can interact with multiple susceptibility genes.”