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Related Concept Videos

Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
Enzyme-Linked Immunosorbent Assay01:33

Enzyme-Linked Immunosorbent Assay

In 1971, Peter Perlman and Eva Engvall developed an Enzyme-linked immunosorbent assay (ELISA or EIA). ELISA differs from western blot in that the assays are conducted in microtiter plates or in vivo rather than on an absorbent membrane.
There are many different types of ELISAs, but they all involve an antibody molecule whose constant region binds an enzyme, leaving the variable region free to bind its specific antigen.  Enzyme-substrate reaction allows the antigen to be visualized or quantified.

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Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens
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Published on: June 28, 2018

ELISA-BASE: an integrated bioinformatics tool for analyzing and tracking ELISA microarray data.

Amanda M White1, James R Collett, Shannon L Seurynck-Servoss

  • 1Pacific Northwest National Laboratory, Richland, WA 99352, USA. amanda.white@pnl.gov

Bioinformatics (Oxford, England)
|April 7, 2009
PubMed
Summary
This summary is machine-generated.

ELISA-BASE is a new open-source database designed for managing enzyme-linked immunosorbent assay (ELISA) microarray data. It aids in capturing, organizing, and analyzing complex biological assay results.

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Area of Science:

  • Bioinformatics
  • Biotechnology
  • Data Management

Background:

  • Enzyme-linked immunosorbent assay (ELISA) microarrays generate complex datasets.
  • Existing systems may lack specialized features for ELISA microarray data analysis.
  • Efficient data management is crucial for biological research.

Purpose of the Study:

  • To introduce ELISA-BASE, an open-source database system.
  • To provide a platform for capturing, organizing, and analyzing ELISA microarray data.
  • To enhance the utility of the BioArray Software Environment (BASE) for ELISA applications.

Main Methods:

  • Development of an open-source database.
  • Extension of the BioArray Software Environment (BASE).
  • Implementation of features for ELISA microarray data handling.

Main Results:

  • ELISA-BASE facilitates structured data capture.
  • The system enables organized storage of ELISA microarray results.
  • Analysis capabilities are integrated within the database.

Conclusions:

  • ELISA-BASE offers a comprehensive solution for ELISA microarray data.
  • The database system supports efficient data management and analysis.
  • It serves as a valuable extension to existing biological database environments.