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

What's in a character?

Rob DeSalle1

  • 1Division of Invertebrates and the Molecular Systematics Laboratories, American Museum of Natural History, 79th Street at Central Park West, New York, NY 10024, USA. desalle@amnh.org

Journal of Biomedical Informatics
|December 31, 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

Natural selection and language genes in humans.

Scientific reports·2026
Same author

Mitochondrial Gene Phylogenetic Incongruencies Are Linked to Chromosomal Position and Function.

Genome biology and evolution·2025
Same author

Morphological data, phylogenomics and recalcitrant nodes.

Cladistics : the international journal of the Willi Hennig Society·2025
Same author

Linguistic capacity was present in the <i>Homo sapiens</i> population 135 thousand years ago.

Frontiers in psychology·2025
Same author

Race realism goes both ways.

History and philosophy of the life sciences·2025
Same author

What Do We Gain When Tolerating Loss? The Information Bottleneck Wrings Out Recombination.

Molecular biology and evolution·2025
Same journal

Evaluation of temporal preservation in synthetic longitudinal patient data.

Journal of biomedical informatics·2026
Same journal

ARKE: An ontology-driven framework for automated mapping of local radiology procedure terms to the LOINC-RadLex playbook using large language model.

Journal of biomedical informatics·2026
Same journal

A validation-driven training controller for cross-lingual biomedical NER via reinforcement learning-based adaptive loss weighting.

Journal of biomedical informatics·2026
Same journal

ASP-HR: An Adaptive Spatial Perception and Hierarchical Reasoning mechanism for document-level biomedical relation extraction.

Journal of biomedical informatics·2026
Same journal

Beyond Accuracy: Safety-Centered guidelines for the evaluation of LLM-based therapy recommendation systems for chronic multimorbidity patients.

Journal of biomedical informatics·2026
Same journal

DeepEN: A deep reinforcement learning framework for personalized enteral nutrition in critical care.

Journal of biomedical informatics·2026
See all related articles

This study clarifies how characters form the basis of systematic analysis in bioinformatics. It details diverse biological data types for phylogenetic tree construction and comparative biology.

Area of Science:

  • Bioinformatics
  • Comparative Biology
  • Systematics

Background:

  • Systematic analyses are crucial in bioinformatics, especially for constructing phenetic and phylogenetic trees.
  • Understanding systematic analysis nuances is vital for bioinformaticians in modern biology.
  • Defining appropriate primary data for phylogenetic analyses remains a challenge.

Purpose of the Study:

  • To define characters as the foundation of all comparative analyses.
  • To describe the variety of primary data available in biology, genomics, and bioinformatics.
  • To contextualize these data types within established tree-building methodologies.

Main Methods:

  • Character definition and classification.
  • Review of diverse primary data sources in biological sciences.

Related Experiment Videos

  • Integration of data types into phylogenetic tree-building frameworks.

    • Main Results:

    • Characters are fundamental to comparative analysis and hierarchical organization.
    • Diverse data, including genomic information, can be utilized in systematic studies.
    • A framework is presented for applying various data types to tree building.

    Conclusions:

    • Accurate character definition and data selection are essential for robust phylogenetic analysis.
    • Bioinformaticians must understand data nuances for effective systematic studies.
    • This work provides a guide for integrating diverse biological data into tree-building approaches.