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Automated Microbial Diagnostics01:24

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Automated diagnostic analyzers have transformed clinical microbiology by providing rapid and reliable methods for pathogen identification and antibiotic susceptibility testing. Among these systems, the Vitek 2 is widely used because it automates the traditionally labor-intensive processes of microbial identification (ID) and antibiotic susceptibility testing (AST), delivering standardized and timely results that are essential for effective patient care.Microbial Identification with ID CardsThe...

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Related Experiment Video

Updated: May 25, 2026

Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot
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Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot

Published on: October 28, 2021

The EnzymeTracker: an open-source laboratory information management system for sample tracking.

Thomas Triplet1, Gregory Butler

  • 1Department of Computer Science and Software Engineering, Concordia University, 1455 De Maisonneuve Blvd. West, Montreal, Quebec, H3G 1M8, Canada.

BMC Bioinformatics
|January 28, 2012
PubMed
Summary

EnzymeTracker is a free, open-source laboratory information management system that overcomes spreadsheet limitations for biological data entry, mining, and sharing. This web-based system offers enhanced data validation, collaboration tools, and sample tracking capabilities for researchers.

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Area of Science:

  • Bioinformatics
  • Laboratory Management
  • Data Science

Background:

  • Spreadsheets are commonly used for experimental data storage but present challenges in data sharing, mining, and validation.
  • Proprietary laboratory information management systems are often expensive, limiting access for many research laboratories.
  • There is a need for cost-effective and flexible solutions for managing biological experimental data.

Purpose of the Study:

  • To introduce EnzymeTracker, an open-source, web-based laboratory information management system (LIMS).
  • To provide a flexible alternative to spreadsheets and costly proprietary systems for managing experimental biological data.
  • To facilitate data entry, mining, sharing, and sample tracking in research settings.

Main Methods:

  • Developed a web-based LIMS utilizing a database management system and an AJAX interface.
  • Implemented online spreadsheets for data entry and monitoring of experiments.
  • Integrated features for data access control (OpenID), user management, protocol libraries, and QR matrix barcoding.

Main Results:

  • EnzymeTracker offers dynamic data entry suggestions and smart data-mining tools for efficient information retrieval.
  • The system provides tools for visualizing, annotating, and exporting experimental data with customizable reports.
  • Supports collaborative research through shared data libraries and user/team management.

Conclusions:

  • EnzymeTracker is a user-friendly, open-source LIMS that offers significant advantages over traditional spreadsheets.
  • The system has been successfully used daily by over 50 scientists for 20 months, demonstrating its practical utility.
  • EnzymeTracker is freely available under the GNU GPLv3 license, promoting wider adoption in the scientific community.