Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Evolutionary Relationships through Genome Comparisons

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

Single-Strand DNA Binding Proteins

Single-Strand DNA Binding Proteins

For successful DNA replication, the unwinding of double-stranded DNA must be accompanied by stabilization and protection of the separated single strands of the DNA. This crucial task is performed by single-strand DNA-binding (SSB) proteins. They bind to the DNA in a sequence-independent manner, which means that the nitrogenous bases of the DNA need not be present in a specific order for binding of SSB proteins to it. The binding of SSB proteins straightens single-stranded DNA (ssDNA) and makes...

Conserved Binding Sites

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Associations of C-reactive protein-triglyceride-glucose index cumulative burden with incident cardiovascular disease in middle-aged and older Chinese adults with abnormal glucose metabolism.

Nutricion hospitalaria·2026

Same author

The role of non-coding RNA-mediated autophagy in Alzheimer's disease.

Brain research bulletin·2026

Same author

Density-dependent functional thresholds and early-warning indicators of alpine meadow degradation under plateau pika (Ochotona curzoniae) and zokor (Myospalax baileyi) disturbance: A meta-analysis.

Journal of environmental management·2026

Same author

Natural variation in the ORL4 promoter regulates rice leaf rolling to modulate leaf architecture and yield.

The Plant cell·2026

Same author

Pressure-Induced Discovery of a Topological Phase of Bi<sub>4</sub>Br<sub>4</sub> with AA''-Stacking.

The journal of physical chemistry letters·2026

Same author

Inhibiting RhoA Activation Via GDP-State Stabilization to Relieve Heart Failure.

Circulation research·2026

Same journal

OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.

BMC bioinformatics·2026

Same journal

NAP: an open source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data.

BMC bioinformatics·2026

Same journal

SurvGME: an R package for survival analysis with graphical and measurement error models.

BMC bioinformatics·2026

Same journal

SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external hint.

BMC bioinformatics·2026

Same journal

Dual channel drug-drug interactions extraction based on cross attention.

BMC bioinformatics·2026

Same journal

FeSseqdb: a curated sequence-level database and interpretable machine learning framework for identifying iron-sulfur proteins.

BMC bioinformatics·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 13, 2026

An Integrated Approach for Microprotein Identification and Sequence Analysis

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

An improved sequence based prediction protocol for DNA-binding proteins using SVM and comprehensive feature analysis.

Chuanxin Zou¹, Jiayu Gong, Honglin Li

¹Shanghai Key Laboratory of New Drug Design, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.

BMC Bioinformatics

|March 19, 2013

Summary

This summary is machine-generated.

This study introduces a novel computational method to accurately predict DNA-binding proteins (DNA-BPs) directly from their amino acid sequences. The approach transforms protein features into a uniform numeric representation, improving prediction accuracy for DNA-BP identification.

More Related Videos

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

DNA Sequence Recognition by DNA Primase Using High-Throughput Primase Profiling

DNA Sequence Recognition by DNA Primase Using High-Throughput Primase Profiling

Published on: October 8, 2019

Related Experiment Videos

Last Updated: May 13, 2026

An Integrated Approach for Microprotein Identification and Sequence Analysis

An Integrated Approach for Microprotein Identification and Sequence Analysis

Published on: July 12, 2022

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

DNA Sequence Recognition by DNA Primase Using High-Throughput Primase Profiling

DNA Sequence Recognition by DNA Primase Using High-Throughput Primase Profiling

Published on: October 8, 2019

Area of Science:

Bioinformatics
Computational Biology
Proteomics

Background:

DNA-binding proteins (DNA-BPs) are crucial in both eukaryotic and prokaryotic systems.
Existing computational methods for DNA-BP prediction utilize various features but predicting directly from primary sequence remains a challenge.

Purpose of the Study:

To develop an accurate, sequence-based computational protocol for predicting DNA-binding proteins.
To systematically investigate feature transformation methods for improved DNA-BP prediction accuracy.

Main Methods:

Employed Support Vector Machine (SVM) classifier.
Utilized four types of protein properties and three feature transformation methods (OCTD, AC, SAA) at global, nonlocal, and local levels.
Applied mRMR-IFS feature selection and ensemble learning for optimal model development.

Main Results:

Achieved high prediction accuracy: 0.940 (0.881 MCC) on DNAdset and 0.811 (0.614 MCC) on DNAaset via five-fold cross-validation.
Identified optimal features that may offer insights into protein-DNA interaction mechanisms.

Conclusions:

Demonstrated an efficient, sequence-based protocol for accurate DNA-BP prediction using transformed and integrated features.
Proposed a novel framework for sequence descriptor-based protein function prediction.