Publication Name	World Journal of Psychiatry
Manuscript ID	61111
Country	Bulgaria

Received	2020-11-24 08:46
Peer-Review Started	2020-11-24 08:47
First Decision by Editorial Office Director	2020-12-12 20:52
Return for Revision	2020-12-12 20:52
Revised	2020-12-15 10:49
Publication Fee Transferred
Second Decision by Editor	2020-12-24 10:29
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2020-12-27 05:15
Articles in Press	2020-12-27 05:15
Edit the Manuscript by Language Editor
Typeset the Manuscript	2021-01-05 11:00
Publish the Manuscript Online	2021-01-11 11:00

ISSN	2220-3206 (online)
Open Access	This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
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Category	Neurosciences
Manuscript Type	Opinion Review
Article Title	How to construct neuroscience-informed psychiatric classification? Towards nomothetic networks psychiatry
Manuscript Source	Invited Manuscript
All Author List	Drozdstoy Stoyanov and Michael HJ Maes
Funding Agency and Grant Number
Corresponding Author	Drozdstoy Stoyanov, DSc, MD, PhD, Full Professor, Department of Psychiatry and Medical Psychology, Research Institute, Medical University of Plovdiv, Vassil Aprilov 15a, Plovdiv 4000, Bulgaria. drozdstoy.stoyanov@mu-plovdiv.bg
Key Words	Psychiatry; Major depression; Mood disorders; Schizophrenia; Antioxidants; Oxydative stress
Core Tip	The nomothetic network psychiatry approach is a new method which aims to construct causal models of schizophrenia and mood disorders by integrating all features of those mental illnesses into a data-driven model. These features comprise data on risk-resilience, adverse outcome pathways, the cognitome, brainome, symptomatome, staging, and the phenomenome. Partial Least Squares analysis may be employed to train, test, and validate those models and to build pathway-phenotypes or biosignatures. Clustering analysis performed on all illness features, reduced into latent traits scores, may expose relevant new transdiagnostic classes.
Publish Date	2021-01-11 11:00
Citation	Stoyanov D, Maes MH. How to construct neuroscience-informed psychiatric classification? Towards nomothetic networks psychiatry. World J Psychiatr 2021; 11(1): 1-12
URL	https://www.wjgnet.com/2220-3206/full/v11/i1/1.htm
DOI	https://dx.doi.org/10.5498/wjp.v11.i1.1

Full Article (PDF)	WJP-11-1.pdf
Full Article (Word)	WJP-11-1.docx
Manuscript File	61111_Auto_Edited.docx
Answering Reviewers	61111-Answering reviewers.pdf
Audio Core Tip	61111-Audio core tip.m4a
Conflict-of-Interest Disclosure Form	61111-Conflict-of-interest statement.pdf
Copyright License Agreement	61111-Copyright license agreement.pdf
Peer-review Report	61111-Peer-review(s).pdf
Scientific Misconduct Check	61111-Bing-Gao CC-1.jpg
Scientific Misconduct Check	61111-Scientific misconduct check.pdf
Scientific Editor Work List	61111-Scientific editor work list.pdf
CrossCheck Report	61111-CrossCheck report.pdf