Animal model integration to AutDB, a genetic database for autism

Area of Science:

• Neuroscience
• Genetics
• Bioinformatics

Background:

• Autism Spectrum Disorder (ASD) research generates vast molecular data, posing challenges for systematic analysis.
• Existing Autism Database (AutDB) manually curates ASD-related human genes.
• A new module is developed to address the need for cataloging ASD-related animal models.

Purpose of the Study:

• To design, develop, and integrate a comprehensive module for collecting and cataloging ASD-related animal models within AutDB.
• To facilitate systematic analysis of diverse molecular and phenotypic data associated with ASD.
• To enable cross-modal navigation between animal models and human gene studies.

Main Methods:

• Data extracted from peer-reviewed literature.
• Animal models annotated using a standardized vocabulary of ASD-related phenotypic terms.
• New module integrated into AutDB, linking animal models to human genes.

Main Results:

• A new, integrated Animal Model module is now part of AutDB.
• The module currently focuses on mouse models but is designed for future expansion to other species.
• Entries link animal models to corresponding candidate genes, enabling cross-modal navigation.

Conclusions:

• The modular ASD database serves as a platform for data mining and computational strategies to develop predictive disease models.
• This resource offers insights into the molecular underpinnings of ASD.
• It provides a model for disease-driven databases curating phenotypic characteristics of animal models.