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Related Concept Videos

Depressive Disorders: Etiology01:27

Depressive Disorders: Etiology

Depressive disorders result from a complex interplay of biological, psychological, and sociocultural factors, each contributing uniquely to the development and persistence of the condition. Understanding these factors provides critical insight into the multifaceted nature of depression.
Biological Factors in Depression
Biological predispositions significantly influence the risk of developing depressive disorders. Genetic studies highlight the role of variations in the serotonin transporter...
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Depression is a prevalent mental illness marked by persistent sadness and lack of interest in previously enjoyable activities. It can take several forms, including major depression, persistent depressive disorder, and bipolar I and II disorders. Symptoms range from emotional changes like chronic worry to physical changes like sleep disturbances and suicidal thoughts. From a neurobiological perspective, depression is believed to be triggered by abnormalities in the brain's prefrontal cortex,...

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Related Experiment Video

Updated: Jul 2, 2026

Mining Spatial Transcriptomics Datasets using DeepSpaceDB
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Published on: September 5, 2025

TranDep: a transcriptomics atlas of depression.

Xiaogang Zhong1,2,3, Siwen Gui1,2,3, Dongfang Wang1,2,3

  • 1Department of Neurology, NHC Key Laboratory of Diagnosis and Treatment on Brain Functional Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.

Molecular Psychiatry
|July 1, 2026
PubMed
Summary

This study compiles extensive depression transcriptomic data across species, creating the TranDep database to identify key genes and biological functions for improved diagnosis and targeted therapies for this severe mental illness.

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Animal Models of Depression - Chronic Despair Model (CDM)
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Mining Spatial Transcriptomics Datasets using DeepSpaceDB
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Animal Models of Depression - Chronic Despair Model (CDM)
05:47

Animal Models of Depression - Chronic Despair Model (CDM)

Published on: September 23, 2021

Area of Science:

  • Neuroscience and Genetics
  • Bioinformatics and Computational Biology

Background:

  • Depression is a major public health concern with complex pathogenesis.
  • Understanding depression-associated genetic regulatory networks is crucial for diagnosis and therapy.
  • A comprehensive view of transcriptional alterations in depression is currently lacking.

Purpose of the Study:

  • To compile and analyze extensive depression-related transcriptomic datasets.
  • To develop a centralized, user-friendly database (TranDep) for depression research.
  • To identify differentially expressed genes (DEGs) and explore their functions in depression.

Main Methods:

  • Leveraged transcriptomic studies from public repositories (NCBI, CNCB, EBI) and internal data.
  • Compiled a large, cross-species dataset including various tissues, interventions, and sample types.
  • Employed a unified pipeline for data preprocessing and differential expression analysis.

Main Results:

  • Generated a comprehensive dataset of over 631,882 molecular entries across 4 species.
  • Included single-cell and single-nucleus transcriptomic data for detailed cellular analysis.
  • Developed the TranDep database (http://www.depression-atlas.cn/) for accessible data exploration.

Conclusions:

  • TranDep provides a valuable cross-species transcriptional atlas for depression research.
  • The database facilitates the identification of robust DEGs and exploration of their biological functions.
  • TranDep may aid in discovering and validating diagnostic and therapeutic markers for depression.