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Updated: Mar 19, 2026

Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

Novel function discovery through sequence and structural data mining.

Briallen Lobb¹, Andrew C Doxey¹

¹Department of Biology, University of Waterloo, 200 University Ave. West, Waterloo, ON N2L 3G1, Canada.

Current Opinion in Structural Biology

|June 13, 2016

Summary

This summary is machine-generated.

Mining large protein datasets reveals novel functions using diverse bioinformatics approaches. These methods, including sequence and structural analysis, help discover new protein activities and specificities, even in uncharacterized proteins.

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A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Area of Science:

Proteomics
Bioinformatics
Structural Biology

Background:

Large-scale sequence and structural data offer vast potential for discovering novel proteins.
Effective mining strategies are crucial to unlock the functional insights hidden within this data.

Purpose of the Study:

To review protein function prediction methods.
To highlight recent studies applying these methods for novel functionality discovery.

Main Methods:

Sequence-based homology detection
Phylogenetic analysis
Structural bioinformatics
Genomic context-based functional association inference

Main Results:

Diverse approaches enable new functionality prediction irrespective of sequence similarity to known proteins.
Functional shifts in sequences can reveal novel activities and specificities.
New functions can be predicted for uncharacterized sequences and structures.

Conclusions:

Integrated methods and expanded protein domain knowledge amplify the discovery of novel protein functions.
Bioinformatics tools are essential for navigating and interpreting large-scale protein data.