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_14
Snippet: We built a schizophrenia bioenergetic gene profile of 6 glycolytic genes based on data from our cell-level postmortem findings (HK1, PFKM, PFKL, GPI) and the literature (LDHA, PFKFB2). These "seed genes" were used in subsequent "lookup" replication studies, iLINCS clustering analyses (followed by Enrichr analysis), and iLINCS connectivity analyses (drug discovery analysis using "inverse/discordant" signatures). Figure 1 summarizes the bioinformat.....
Document: We built a schizophrenia bioenergetic gene profile of 6 glycolytic genes based on data from our cell-level postmortem findings (HK1, PFKM, PFKL, GPI) and the literature (LDHA, PFKFB2). These "seed genes" were used in subsequent "lookup" replication studies, iLINCS clustering analyses (followed by Enrichr analysis), and iLINCS connectivity analyses (drug discovery analysis using "inverse/discordant" signatures). Figure 1 summarizes the bioinformatic work flow for both clustering and connectivity analyses.
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