ICBrainDB: An Integrated Database for Finding Associations between Genetic Factors and EEG Markers of Depressive Disorders.
Roman IvanovFedor KazantsevEvgeny ZavarzinAlexandra I KlimenkoNatalya MilakhinaYury G MatushkinAlexander SavostyanovSergey A LashinPublished in: Journal of personalized medicine (2022)
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.
Keyphrases
- data analysis
- big data
- machine learning
- genome wide
- electronic health record
- working memory
- functional connectivity
- resting state
- neural network
- health information
- adverse drug
- bipolar disorder
- sleep quality
- depressive symptoms
- copy number
- dna methylation
- artificial intelligence
- emergency department
- social media
- stress induced