Meccus pallidipennis
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1304992 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Trimerotropis pallidipennis overview
| PRJNA737551 | ENA
Project description:Trimerotropis pallidipennis Transcriptome Assembly
| PRJNA598231 | ENA
Project description:Trimerotropis pallidipennis Raw sequence reads
| PRJNA733099 | ENA
Project description:Meccus pallidipennis Transcriptome or Gene expression
| PRJNA323400 | ENA
Project description:Integration of multiple signals shapes cell adaptation to their microenvironment through synergistic and antagonistic interactions. The combinatorial complexity governing signal integration for multiple cellular output responses has not been resolved. For outputs measured in the conditions 0 (control), signals X, Y, X+Y, combinatorial analysis revealed 82 possible interaction profiles, which we biologically assimilated to 5 positive, and 5 negative interaction modes. To experimentally validate their use in living cells, we designed an original computational workflow, and applied it to transcriptomics data of innate immune cells integrating physiopathological signal combinations. Up to 9 of the 10 defined modes coexisted in context-dependent proportions. Each integration mode was enriched in specific molecular pathways, suggesting a coupling between genes involved in particular functions, and the corresponding mode of integration. We propose that multimodality and functional coupling are general principles underlying the systems level integration of physiopathological and pharmacological stimuli by mammalian cells. The general experiment design : No stimulus (Medium), stimulus X, stimulus Y and combination treatment X+Y was applied for 6 or 24 hours, with different stimuli combinations. Every experimental condition was carried out in 3 independent biological replicates.
2015-03-06 | E-GEOD-57915 | biostudies-arrayexpress
Project description:Integration of multiple signals shapes cell adaptation to their microenvironment through synergistic and antagonistic interactions. The combinatorial complexity governing signal integration for multiple cellular output responses has not been resolved. For outputs measured in the conditions 0 (control), signals X, Y, X+Y, combinatorial analysis revealed 82 possible interaction profiles, which we biologically assimilated to 5 positive, and 5 negative interaction modes. To experimentally validate their use in living cells, we designed an original computational workflow, and applied it to transcriptomics data of innate immune cells integrating physiopathological signal combinations. Up to 9 of the 10 defined modes coexisted in context-dependent proportions. Each integration mode was enriched in specific molecular pathways, suggesting a coupling between genes involved in particular functions, and the corresponding mode of integration. We propose that multimodality and functional coupling are general principles underlying the systems level integration of physiopathological and pharmacological stimuli by mammalian cells.
2015-03-06 | GSE57915 | GEO
Project description:We generated a genome-scale, genetic interaction network from the analysis of more than 5 million double mutants in the haploid human cell line, HAP1. The network comprises ~90,000 negative and positive genetic interactions, including thousands of extreme synthetic lethal and genetic suppression interactions. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Systematic comparative analyses showed that the general principles and topology of genetic networks are conserved from yeast to humans. A genetic interaction network mapped in a single genetic background complements the DepMap cancer cell co-essentiality network, recapitulating many of the same functional connections and also capturing unique functional information to reveal roles of previously uncharacterized genes and molecular determinants of specific cancer cell line genetic dependencies.
2026-05-07 | GSE296341 | GEO