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Frontiers in Pharmacology|October 20, 2022
Network science approach elucidates integrative genomic-metabolomic signature of antidepressant response and lifetime history of attempted suicide in adults with major depressive disorderCaroline W Grant, Angelina R Wilton, Rima Kaddurah-Daouk, et al.
Journal of Personalized Medicine|March 25, 2022
Multi-Omics Characterization of Early- and Adult-Onset Major Depressive DisorderCaroline W Grant, Erin F Barreto, Rakesh Kumar, et al.
Psychiatry Research|July 5, 2005
Brief psychiatric rating scale expanded version: How do new items affect factor structure?Dawn Velligan, Thomas Prihoda, Ellen Dennehy, et al.
Molecular Psychiatry|February 17, 2026
A brain-enriched circRNA blood biomarker can predict response to SSRI antidepressantsGrigorios Papageorgiou, El Chérif Ibrahim, Victor Gorgievski, et al.
Contemporary Clinical Trials Communications|July 4, 2017
Statistical Analysis Plan for Stage 1 EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care) StudyEva Petkova, R Todd Ogden, Thaddeus Tarpey, et al.
Biological Psychiatry|June 9, 2022
Dynamic Resting-State Network Biomarkers of Antidepressant Treatment ResponseRoselinde H Kaiser, Henry W Chase, Mary L Phillips, et al.
Schizophrenia Bulletin|January 6, 2005
The Texas medication algorithm project: clinical results for schizophreniaAlexander L Miller, M Lynn Crismon, A John Rush, et al.
Translational Psychiatry|October 8, 2021
Multi-omics driven predictions of response to acute phase combination antidepressant therapy: a machine learning approach with cross-trial replicationJeremiah B Joyce, Caroline W Grant, Duan Liu, et al.
Human Brain Mapping|June 3, 2015
Test-retest reliability of freesurfer measurements within and between sites: Effects of visual approval processZafer Iscan, Tony B Jin, Alexandria Kendrick, et al.
Journal of Psychiatric Research|January 10, 2020
Comprehensive phenotyping of depression disease trajectory and risk: Rationale and design of Texas Resilience Against Depression study (T-RAD)Madhukar H Trivedi, Cherise R Chin Fatt, Manish K Jha, et al.
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