Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

DIALIGN-T: an improved algorithm for segment-based multiple sequence alignment.

Amarendran R Subramanian1, Jan Weyer-Menkhoff, Michael Kaufmann

  • 1University of Tübingen, Wilhelm-Schickard-Institut für Informatik, Sand 13, 72076 Tübingen, Germany. subraman@informatik.uni-tuebingen.de

BMC Bioinformatics
|March 24, 2005
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Modeling hemorrhage control in the context of agent-based active shooter simulations.

Journal of emergency management (Weston, Mass.)·2026
Same author

Emergency preparedness planning for active shooter situations through higher-fidelity agent-based active shooter simulations: Framework for computational modeling of injury and blood loss.

Journal of emergency management (Weston, Mass.)·2026
Same author

Architecture and dynamics of the abscisic acid gene regulatory network.

The Plant journal : for cell and molecular biology·2024
Same author

Correction: Luedemann et al. Prostate Cancer-Associated miRNAs in Saliva: First Steps to an Easily Accessible and Reliable Screening Tool. <i>Biomolecules</i> 2022, <i>12</i>, 1366.

Biomolecules·2023
Same author

Splitting Vertices in 2-Layer Graph Drawings.

IEEE computer graphics and applications·2023
Same author

App-SpaM: phylogenetic placement of short reads without sequence alignment.

Bioinformatics advances·2023
Same journal

SNPio: a Python interface for population genomic data processing.

BMC bioinformatics·2026
Same journal

SpaHNR: a spatial domain identification method via sparse attention-based hierarchical node representation and multi-view contrastive learning.

BMC bioinformatics·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
See all related articles

DIALIGN v2.3 improves protein sequence alignment by enhancing its segment-based approach. This new version excels in aligning locally related sequences and performs comparably to standard methods for globally related ones.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Presents a re-implementation of the DIALIGN segment-based multiple protein alignment approach.
  • Addresses limitations of previous DIALIGN versions, particularly on globally related sequences.

Purpose of the Study:

  • To improve the segment-based approach for protein sequence alignment.
  • To enhance performance on both locally and globally related sequence sets.

Main Methods:

  • Introduced a fragment-chaining algorithm for pairwise alignment favoring low-scoring local alignment chains.
  • Implemented an improved greedy procedure for multiple alignment, reducing sensitivity to spurious similarities.
  • Utilized BAliBASE for global alignment evaluation and created IRMBASE for local alignment benchmarking.

Related Experiment Videos

Main Results:

  • New DIALIGN version shows significant improvement on BAliBASE compared to previous versions.
  • Achieves performance comparable to CLUSTAL W on global alignment tasks.
  • Outperforms all evaluated methods on locally related sequences in the IRMBASE benchmark.

Conclusions:

  • The enhanced DIALIGN program offers superior performance for locally related protein sequences.
  • It provides competitive results for globally related sequences, comparable to established tools.