Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Motivation: Deciphering the response of a complex biological system to an insulting event, at the gene expression level, requires adopting theoretical models that are more sophisticated than a one-to-one comparison (i.e. t-test). Here,  investigate the ability of a novel reverse engineering approach (System Response Inference) to unveil non-obvious transcriptional signatures of the system response induced by prion infection.#R##N##R##N#Results: To this end,  analyze previously published gene expression data, from which  extrapolate a putative full-scale model of transcriptional gene–gene dependencies in the mouse central nervous system. Then,  use this nominal model to interpret the gene expression changes caused by prion replication, aiming at selecting the genes primarily influenced by this perturbation. Our method sheds light on the mode of action of prions by identifying key transcripts that are the most likely to be responsible for the overall transcriptional rearrangement from a nominal regulatory network. As a first result of our inference,  have been able to predict known targets of prions (i.e. PrPC) and to unveil the potential role of previously unsuspected genes.#R##N##R##N#Contact: altafini@sissa.it#R##N##R##N#Supplementary Information: Supplementary data are available at Bioinformatics online.
['Mattia Zampieri', 'Giuseppe Legname', 'Daniel Segrè', 'Claudio Altafini']
I am writing a research paper on a idea A system-level approach for deciphering the transcriptional response to prion infection
[{"from": "human", "value": "I am writing a research paper on a idea A system-level approach for deciphering the transcriptional response to prion infection"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Motivation: Deciphering the response of a complex biological system to an insulting event, at the gene expression level, requires adopting theoretical models that are more sophisticated than a one-to-one comparison (i.e. t-test). Here,  investigate the ability of a novel reverse engineering approach (System Response Inference) to unveil non-obvious transcriptional signatures of the system response induced by prion infection.#R##N##R##N#Results: To this end,  analyze previously published gene expression data, from which  extrapolate a putative full-scale model of transcriptional gene\u2013gene dependencies in the mouse central nervous system. Then,  use this nominal model to interpret the gene expression changes caused by prion replication, aiming at selecting the genes primarily influenced by this perturbation. Our method sheds light on the mode of action of prions by identifying key transcripts that are the most likely to be responsible for the overall transcriptional rearrangement from a nominal regulatory network. As a first result of our inference,  have been able to predict known targets of prions (i.e. PrPC) and to unveil the potential role of previously unsuspected genes.#R##N##R##N#Contact: altafini@sissa.it#R##N##R##N#Supplementary Information: Supplementary data are available at Bioinformatics online."}]