Author: Courtney R. Sullivan; Catharine A. Mielnik; Sinead M. O’Donovan; Adam J. Funk; Eduard Bentea; Erica A.K. DePasquale; Zhexing Wen; Vahram Haroutunian; Pavel Katsel; Amy J. Ramsey; Jarek Meller; Robert E. McCullumsmith
Title: Connectivity analyses of bioenergetic changes in schizophrenia: Identification of novel treatments Document date: 2018_6_5
ID: ltb6l5xz_81
Snippet: In summary, we have utilized the LINCS library of genetic and chemical perturbations, coupled with a novel bioinformatics approach to gain insight into the connectivity of bioenergetic pathology in schizophrenia, generated candidate drugs with the potential to reverse the . CC-BY-NC-ND 4.0 International license is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It . https://doi.org.....
Document: In summary, we have utilized the LINCS library of genetic and chemical perturbations, coupled with a novel bioinformatics approach to gain insight into the connectivity of bioenergetic pathology in schizophrenia, generated candidate drugs with the potential to reverse the . CC-BY-NC-ND 4.0 International license is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It . https://doi.org/10.1101/338392 doi: bioRxiv preprint connected pathological signature as opposed to a single target, and restored long-term memory with the PPAR agonist pioglitazone in a preclinical model of schizophrenia. Our work highlights the potential for bioinformatic analyses to identify novel treatment strategies for disorders of cognition and other difficult to treat clinical domains.
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