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Extraction: Advanced Methods

Extraction: Advanced Methods

Metal ions can be separated from one another by complexation with organic ligands–the chelating agent– to form uncharged chelates. Here, the chelating agent must contain hydrophobic groups and behave as a weak acid, losing a proton to bind with the metal. Since most organic ligands used in this process are insoluble or undergo oxidation in the aqueous phase, the chelating agent is initially added to the organic phase and extracted into the aqueous phase. The metal-ligand complex is...

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Related Experiment Video

Updated: Mar 31, 2026

Using the Open-Source MALDI TOF-MS IDBac Pipeline for Analysis of Microbial Protein and Specialized Metabolite Data

Using the Open-Source MALDI TOF-MS IDBac Pipeline for Analysis of Microbial Protein and Specialized Metabolite Data

Published on: May 15, 2019

BioDB extractor: customized data extraction system for commonly used bioinformatics databases.

Rajiv Karbhal¹, Sangeeta Sawant¹, Urmila Kulkarni-Kale¹

¹Bioinformatics Centre, Savitribai Phule Pune University, Ganeshkhind, Pune, 411007 Maharashtra India.

|October 31, 2015

Summary

This summary is machine-generated.

BioDBExtractor (BDE) simplifies extracting specific biological data subsets from major databases like ENA and UniProtKB. This tool eliminates manual scripting, enabling efficient data retrieval for downstream analysis.

Keywords:

Bioinformatics Biological databases Customized data retrieval Data integration Database cross-linking

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Area of Science:

Bioinformatics
Computational Biology
Data Science

Background:

Biological data is stored in diverse formats across heterogeneous resources.
Current search engines lack granular data subset extraction capabilities, requiring manual scripting.
Accessing fine-grained data necessitates downloading and parsing complete database entries.

Purpose of the Study:

To develop a tool for efficient, fine-grained data extraction from biological databases.
To provide a common platform for accessing data from multiple sources.
To simplify data retrieval for both novice and expert users.

Main Methods:

Developed BioDBExtractor (BDE), a web-based tool with 26 data extraction utilities.
Supports common biological databases: ENA (EMBL-Bank), UniProtKB, PDB, and KEGG.
User interface allows input via accession numbers/ID codes, utility selection, and field/subfield specification.

Main Results:

BDE offers 26 customized utilities for data extraction.
Eliminates the need for downloading full entries and writing custom scripts.
Provides a user-friendly web interface for targeted data retrieval.

Conclusions:

BDE serves as a unified data extraction platform for multiple biological databases.
Facilitates downstream processing, analysis, and knowledge discovery.
Complements, but does not replace, traditional keyword-based database searches.