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

Ecological Disturbance

Ecological Disturbance

An ecological disturbance is a temporary disruption in the environment resulting from abiotic, biotic, or anthropogenic factors, causing a pronounced change in an ecosystem. The impact of an ecological disturbance, which can depend on its intensity, frequency, and spatial distribution, plays a significant role in shaping the species diversity within the ecosystem.Ecological disturbances can be caused by an event as small as the trampling of underbrush to an incident as wide-ranging as a forest...

Methods of Classification and Identification

Methods of Classification and Identification

Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...

You might also read

Related Articles

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

Sort by

Same author

Corrigendum to "The lived experience of social anxiety disorder: A conceptual model focused on adolescents and young adults based on published literature and social media listening"[Journal of Anxiety Disorders 118 (2026) 1-11/103129].

Journal of anxiety disorders·2026

Same author

Best practices for the collection and analysis of patient experience data from social media for patient-focused drug development.

Frontiers in medicine·2026

Same author

Empowering biological knowledgebases: advances in human-in-the-loop AI-driven literature curation.

Bioinformatics advances·2026

Same author

The lived experience of social anxiety disorder: A conceptual model focused on adolescents and young adults based on published literature and social media listening.

Journal of anxiety disorders·2026

Same author

Large language models forecast patient health trajectories enabling digital twins.

NPJ digital medicine·2025

Same author

Generative AI and digital twins: shaping a paradigm shift from precision to truly personalized medicine.

Expert opinion on drug discovery·2025

Same journal

Correction to 'New origin firing is inhibited by APC/CCdh1 activation in S-phase after severe replication stress'.

Nucleic acids research·2026

Same journal

VeloRM: disentangling pre- and post-splicing RNA modification dynamics at single-cell resolution.

Nucleic acids research·2026

Same journal

Accessibility of telomeric overhangs to stabilizing small-molecule ligands.

Nucleic acids research·2026

Same journal

Multivalent interactions mediate SNAIL transcription factor stimulation of the nucleosome deacetylase activity of the CoREST complex.

Nucleic acids research·2026

Same journal

Genome-wide mapping of DNA G-quadruplexes in Trypanosoma brucei chromatin reveals enrichment in coding regions and transcription start sites.

Nucleic acids research·2026

Same journal

Correction to 'The Gene Ontology knowledgebase in 2026'.

Nucleic acids research·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 27, 2026

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

Identifying and classifying biomedical perturbations in text.

Raul Rodriguez-Esteban¹, Phoebe M Roberts, Matthew E Crawford

¹Pfizer Research Technology Center, 620 Memorial Dr., Cambridge, MA 02139, USA. Raul.Rodriguez-Esteban@pfizer.com

Nucleic Acids Research

|December 17, 2008

Summary

This summary is machine-generated.

Researchers developed a formal framework to classify molecular perturbations, enabling a novel algorithm for automatic detection and characterization in biomedical texts. This approach enhances understanding of gene-phenotype and protein-protein interactions in diseases like diabetes and cancer.

More Related Videos

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Related Experiment Videos

Last Updated: Jun 27, 2026

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

Area of Science:

Biomedical research
Systems biology
Bioinformatics

Background:

Molecular perturbations are crucial for understanding biological systems.
Existing methods for classifying perturbations are diverse and lack formalization.
Formalizing perturbation properties can improve experimental design and target analysis.

Purpose of the Study:

To propose a formal framework for describing and classifying molecular perturbations.
To develop a novel algorithm for automatic detection and characterization of perturbations in text.
To demonstrate the framework's relevance in studying gene-phenotype and protein-protein interactions.

Main Methods:

Development of a formal framework for perturbation classification.
Creation of an algorithm for automated perturbation detection and characterization from text.
Application of the framework and algorithm to analyze gene-phenotype and protein-protein interactions in diabetes and cancer datasets.

Main Results:

A formal framework for perturbation analysis was established.
A novel algorithm for automatic perturbation detection and characterization was developed.
The framework and algorithm proved relevant for studying gene-phenotype and protein-protein interactions in complex diseases.

Conclusions:

The proposed formal framework provides a systematic way to describe and classify molecular perturbations.
Automated detection and characterization of perturbations enhance biomedical knowledge accumulation.
This approach offers a new perspective on the multivariate landscape of biological systems and disease mechanisms.