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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-01-01
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| Series: | Journal of Personalized Medicine |
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| Online Access: | https://www.mdpi.com/2075-4426/12/1/53 |
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| author | Roman Ivanov Fedor Kazantsev Evgeny Zavarzin Alexandra Klimenko Natalya Milakhina Yury G. Matushkin Alexander Savostyanov Sergey Lashin |
| author_facet | Roman Ivanov Fedor Kazantsev Evgeny Zavarzin Alexandra Klimenko Natalya Milakhina Yury G. Matushkin Alexander Savostyanov Sergey Lashin |
| author_sort | Roman Ivanov |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T01:10:27Z |
| format | Article |
| id | doaj.art-95ef69e1d1074b7d9cc230c55f34db06 |
| institution | Directory Open Access Journal |
| issn | 2075-4426 |
| language | English |
| last_indexed | 2024-03-10T01:10:27Z |
| publishDate | 2022-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Personalized Medicine |
| spelling | doaj.art-95ef69e1d1074b7d9cc230c55f34db062023-11-23T14:19:47ZengMDPI AGJournal of Personalized Medicine2075-44262022-01-011215310.3390/jpm12010053ICBrainDB: An Integrated Database for Finding Associations between Genetic Factors and EEG Markers of Depressive DisordersRoman Ivanov0Fedor Kazantsev1Evgeny Zavarzin2Alexandra Klimenko3Natalya Milakhina4Yury G. Matushkin5Alexander Savostyanov6Sergey Lashin7Institute of Cytology and Genetics SB RAS, Novosibirsk 630090, RussiaInstitute of Cytology and Genetics SB RAS, Novosibirsk 630090, RussiaNatural Science Faculty, Novosibirsk State University, Novosibirsk 630090, RussiaInstitute of Cytology and Genetics SB RAS, Novosibirsk 630090, RussiaInstitute of Cytology and Genetics SB RAS, Novosibirsk 630090, RussiaInstitute of Cytology and Genetics SB RAS, Novosibirsk 630090, RussiaInstitute of Cytology and Genetics SB RAS, Novosibirsk 630090, RussiaInstitute of Cytology and Genetics SB RAS, Novosibirsk 630090, RussiaIn 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.https://www.mdpi.com/2075-4426/12/1/53depressiondatabaseEEGSNPquestionnaires |
| spellingShingle | Roman Ivanov Fedor Kazantsev Evgeny Zavarzin Alexandra Klimenko Natalya Milakhina Yury G. Matushkin Alexander Savostyanov Sergey Lashin ICBrainDB: An Integrated Database for Finding Associations between Genetic Factors and EEG Markers of Depressive Disorders Journal of Personalized Medicine depression database EEG SNP questionnaires |
| 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 | depression database EEG SNP questionnaires |
| url | https://www.mdpi.com/2075-4426/12/1/53 |
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