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

Conservative Site-specific Recombination and Phase Variation

Conservative Site-specific Recombination and Phase Variation

Because the DNA segments are cut and reorganized in a direction-specific manner, site-specific recombination has emerged as an efficient genetic engineering technique. Flippase and Cyclization recombinases or Flp and Cre, respectively, are two members of the tyrosine recombinase family derived from bacteriophages, that are used to mediate site-specific DNA insertions, deletions, and targeted expression of proteins in mammalian cell lines.
The recognition sites for Cre recombinase called LoxP...

You might also read

Related Articles

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

Sort by

Same author

Panaln: indexing pangenome for read alignment.

Bioinformatics (Oxford, England)·2025

Same author

An efficient Burrows-Wheeler transform-based aligner for short read mapping.

Computational biology and chemistry·2024

Same author

Neural Network-Based Autonomous Search Model with Undulatory Locomotion Inspired by <i>Caenorhabditis Elegans</i>.

Sensors (Basel, Switzerland)·2022

Same author

Temporal Output Discrepancy for Loss Estimation-Based Active Learning.

IEEE transactions on neural networks and learning systems·2022

Same author

Attention-Based Temporal-Frequency Aggregation for Speaker Verification.

Sensors (Basel, Switzerland)·2022

Same author

Neural model generating klinotaxis behavior accompanied by a random walk based on C. elegans connectome.

Scientific reports·2022

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: Mar 17, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

RefSelect: a reference sequence selection algorithm for planted (l, d) motif search.

Qiang Yu¹, Hongwei Huo², Ruixing Zhao¹

¹School of Computer Science and Technology, Xidian University, Xi'an, 710071, China.

BMC Bioinformatics

|July 26, 2016

Summary

This summary is machine-generated.

RefSelect improves planted (l, d) motif search (PMS) by intelligently selecting reference sequences. This stabilizes and accelerates PMS algorithms, offering significant speedups, especially for large biological datasets.

Keywords:

Pattern-driven Planted (l, d) motif search Reference sequences

More Related Videos

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Published on: August 16, 2017

Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

Related Experiment Videos

Last Updated: Mar 17, 2026

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Optimization of Synthetic Proteins: Identification of Interpositional Dependencies Indicating Structurally and/or Functionally Linked Residues

Published on: July 14, 2015

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Creating and Applying a Reference to Facilitate the Discussion and Classification of Proteins in a Diverse Group

Published on: August 16, 2017

Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

Area of Science:

Computational Biology
Bioinformatics

Background:

The planted (l, d) motif search (PMS) is a critical problem in computational biology.
Existing pattern-driven PMS algorithms often select reference sequences arbitrarily, leading to unstable performance, particularly with large alphabets.

Purpose of the Study:

To address the instability and inefficiency of current PMS algorithms.
To introduce a novel method for optimizing reference sequence selection in PMS.

Main Methods:

Developed RefSelect, a method to solve the reference sequence selection problem by evaluating candidate motif counts.
Integrated RefSelect with existing pattern-driven PMS algorithms.

Main Results:

RefSelect ensures stable and efficient PMS problem solving.
Achieved speedups of up to 100x on protein data.
Demonstrated suitability for large datasets with hundreds of sequences.

Conclusions:

RefSelect effectively resolves execution time instability in pattern-driven PMS algorithms.
The algorithm offers efficient and effective reference sequence selection with minimal storage requirements.
A parallel version of RefSelect is available for handling very large datasets.