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Conservation of Protein Domains Over Different Proteins

Conservation of Protein Domains Over Different Proteins

Protein domains are small structurally independent units that are part of a single amino acid chain. Although these domains are often structurally independent, they may rely on synergistic effects to perform their functions as part of a larger protein. Protein domains may be conserved within the same organism, as well as across different organisms.
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Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale studies have provided new insights into the evolutionary relationship between organisms.
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Conservation of Protein Domains

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Related Experiment Video

Updated: Jun 8, 2025

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Published on: May 31, 2011

MAFin: Motif Detection in Multiple Alignment Files.

Michail Patsakis^1,2, Kimonas Provatas^1,2, Fotis A Baltoumas³

¹Institute for Personalized Medicine, Department of Biochemistry and Molecular Biology, The Pennsylvania State University College of Medicine, Hershey, PA, USA.

|November 1, 2024

Summary

This summary is machine-generated.

MAFin is a new tool for motif detection in Multiple Alignment Format (MAF) files, enabling efficient conservation analysis in comparative genomics and proteomics research.

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An Integrated Approach for Microprotein Identification and Sequence Analysis

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Published on: July 12, 2022

Area of Science:

Comparative genomics
Proteomics
Bioinformatics

Background:

Multiple Alignment File (MAF) format is standard for comparative genomics and proteomics.
Existing methods lack direct motif detection within MAF files.

Purpose of the Study:

Introduce MAFin, a novel tool for motif detection and conservation analysis in MAF files.
Streamline genomic and proteomic research by enabling efficient motif discovery.

Main Methods:

MAFin is the first tool for motif detection in MAF files.
Supports multithreaded search using k-mers, regular expressions, or Position Weight Matrices.
Calculates motif conservation percentage and provides statistical interpretation.

Main Results:

MAFin successfully detects conserved motifs within MAF files.
Quantifies motif conservation across aligned sequences.
Exports detected motifs and conservation data in JSON and CSV formats.

Conclusions:

MAFin enhances motif detection and conservation analysis in comparative genomics and proteomics.
Provides a streamlined approach for researchers working with MAF data.
Facilitates downstream analyses through accessible data export.