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ICBrainDB: An Integrated Database for Finding Associations between Genetic Factors and EEG Markers of Depressive Disorders
In this study, we collected and systemized diverse information related to depressive and anxiety disorders as the first step on the way to investigate the associations between molecular genetics, electrophysiological, behavioral, and psychological characteristics of people. Keeping that in mind, we...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8780210/ https://www.ncbi.nlm.nih.gov/pubmed/35055368 http://dx.doi.org/10.3390/jpm12010053 |
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author | Ivanov, Roman Kazantsev, Fedor Zavarzin, Evgeny Klimenko, Alexandra Milakhina, Natalya Matushkin, Yury G. Savostyanov, Alexander Lashin, Sergey |
author_facet | Ivanov, Roman Kazantsev, Fedor Zavarzin, Evgeny Klimenko, Alexandra Milakhina, Natalya Matushkin, Yury G. Savostyanov, Alexander Lashin, Sergey |
author_sort | Ivanov, Roman |
collection | PubMed |
description | In this study, we collected and systemized diverse information related to depressive and anxiety disorders as the first step on the way to investigate the associations between molecular genetics, electrophysiological, behavioral, and psychological characteristics of people. Keeping that in mind, we developed an internet resource including a database and tools for primary presentation of the collected data of genetic factors, the results of electroencephalography (EEG) tests, and psychological questionnaires. The sample of our study was 1010 people from different regions of Russia. We created the integrated ICBrainDB database that enables users to easily access, download, and further process information about individual behavioral characteristics and psychophysiological responses along with inherited trait data. The data obtained can be useful in training neural networks and in machine learning construction processes in Big Data analysis. We believe that the existence of such a resource will play an important role in the further search for associations of genetic factors and EEG markers of depression. |
format | Online Article Text |
id | pubmed-8780210 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87802102022-01-22 ICBrainDB: An Integrated Database for Finding Associations between Genetic Factors and EEG Markers of Depressive Disorders Ivanov, Roman Kazantsev, Fedor Zavarzin, Evgeny Klimenko, Alexandra Milakhina, Natalya Matushkin, Yury G. Savostyanov, Alexander Lashin, Sergey J Pers Med Article In this study, we collected and systemized diverse information related to depressive and anxiety disorders as the first step on the way to investigate the associations between molecular genetics, electrophysiological, behavioral, and psychological characteristics of people. Keeping that in mind, we developed an internet resource including a database and tools for primary presentation of the collected data of genetic factors, the results of electroencephalography (EEG) tests, and psychological questionnaires. The sample of our study was 1010 people from different regions of Russia. We created the integrated ICBrainDB database that enables users to easily access, download, and further process information about individual behavioral characteristics and psychophysiological responses along with inherited trait data. The data obtained can be useful in training neural networks and in machine learning construction processes in Big Data analysis. We believe that the existence of such a resource will play an important role in the further search for associations of genetic factors and EEG markers of depression. MDPI 2022-01-05 /pmc/articles/PMC8780210/ /pubmed/35055368 http://dx.doi.org/10.3390/jpm12010053 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ivanov, Roman Kazantsev, Fedor Zavarzin, Evgeny Klimenko, Alexandra Milakhina, Natalya Matushkin, Yury G. Savostyanov, Alexander Lashin, Sergey ICBrainDB: An Integrated Database for Finding Associations between Genetic Factors and EEG Markers of Depressive Disorders |
title | ICBrainDB: An Integrated Database for Finding Associations between Genetic Factors and EEG Markers of Depressive Disorders |
title_full | ICBrainDB: An Integrated Database for Finding Associations between Genetic Factors and EEG Markers of Depressive Disorders |
title_fullStr | ICBrainDB: An Integrated Database for Finding Associations between Genetic Factors and EEG Markers of Depressive Disorders |
title_full_unstemmed | ICBrainDB: An Integrated Database for Finding Associations between Genetic Factors and EEG Markers of Depressive Disorders |
title_short | ICBrainDB: An Integrated Database for Finding Associations between Genetic Factors and EEG Markers of Depressive Disorders |
title_sort | icbraindb: an integrated database for finding associations between genetic factors and eeg markers of depressive disorders |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8780210/ https://www.ncbi.nlm.nih.gov/pubmed/35055368 http://dx.doi.org/10.3390/jpm12010053 |
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