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Related Experiment Video

Updated: Jul 9, 2026

Mutagenesis and Functional Analysis of Ion Channels Heterologously Expressed in Mammalian Cells

Mutagenesis and Functional Analysis of Ion Channels Heterologously Expressed in Mammalian Cells

Published on: October 1, 2010

Signal processing for functional analysis of protein mutants.

K Najarian¹, K Gopalakrishnan, R H Zadeh

¹College of Information Technology, University of North Carolina at Charlotte, NC 28223, USA. knajaria@uncc.edu

International Journal of Bioinformatics Research and Applications

|December 1, 2007

Summary

We developed a novel method to predict protein mutant function from amino acid sequences. This technique uses signal processing to analyze biochemical signals, enabling classification of mutant protein behaviors.

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A Protocol for Functional Assessment of Whole-Protein Saturation Mutagenesis Libraries Utilizing High-Throughput Sequencing

A Protocol for Functional Assessment of Whole-Protein Saturation Mutagenesis Libraries Utilizing High-Throughput Sequencing

Published on: July 3, 2016

Area of Science:

Biochemistry
Computational Biology
Bioinformatics

Background:

Understanding protein mutant function is crucial for various biological and medical applications.
Predicting protein behavior from primary sequence remains a significant challenge.

Purpose of the Study:

To introduce a new computational technique for predicting the functional behavior of protein mutants.
To leverage primary amino acid sequences for functional prediction.

Main Methods:

Representing amino acid sequences as biochemical signals.
Applying signal processing techniques to extract meaningful measures.
Utilizing computational measures to classify mutant protein functions.

Main Results:

The developed technique successfully extracts functionally relevant information from protein sequences.
Computational measures derived from signal processing effectively distinguish between different functional classes of mutant proteins.

Conclusions:

The proposed method offers a novel approach to predict protein mutant functionality directly from primary sequence data.
This technique has potential applications in protein engineering and disease research.