LDM: A web application for automated management and visualization of laboratory screening data
High-throughput screening (HTS) is essential in preclinical research to identify new drug candidates for specific diseases. This process typically generates large amounts of data that require effective storage, management, and analysis. Traditional methods for handling HTS data involve several stand...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-04-01
|
| Series: | SLAS Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2472630325000160 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | High-throughput screening (HTS) is essential in preclinical research to identify new drug candidates for specific diseases. This process typically generates large amounts of data that require effective storage, management, and analysis. Traditional methods for handling HTS data involve several standalone solutions, which can present challenges regarding data accessibility and reproducibility. We introduce Lab Data Management (LDM), an open-source web application developed to automate the management and visualization of HTS data. LDM provides a highly customizable data management system with an intuitive user interface for handling output data from various laboratory instruments, such as plate readers, microscopes, liquid handlers, and barcode readers. The app allows for results visualization and calculation of quality control metrics. An integrated Jupyter notebook can be used to retrieve the stored data and proceed with a more detailed analysis. |
|---|---|
| ISSN: | 2472-6303 |