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 Concept Videos

Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

485
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
485
Natural and Artificial Concepts01:24

Natural and Artificial Concepts

545
In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
545
Neural Circuits01:25

Neural Circuits

2.7K
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
2.7K
Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

218
Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
218
Concepts and Prototypes01:24

Concepts and Prototypes

511
The human nervous system handles vast amounts of information by translating sensory stimuli into neural impulses, which the brain processes, creating thoughts expressed through language or stored as memories. The brain also synthesizes information from emotions and memories, which significantly influence thoughts and behaviors. This intricate process creates a comprehensive mental picture.
The brain organizes this information using concepts, which are mental categories grouping linguistic data,...
511
The Nativist Approach01:21

The Nativist Approach

393
The nativist approach to infant cognitive development proposes that infants are born with inherent knowledge structures that allow them to interpret the world almost immediately. This perspective contrasts with earlier developmental theories, such as those proposed by Jean Piaget, which emphasized a more gradual acquisition of cognitive abilities through interaction with the environment. One key concept in this approach is object permanence — the understanding that objects continue to...
393

You might also read

Related Articles

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

Sort by
Same author

TabularQual: A spreadsheet-based format for annotating and curating logical models in SBML-qual.

bioRxiv : the preprint server for biology·2026
Same author

SPARK: making ethical and societal tensions explicit in AI-supported precision medicine education.

BMC medical ethics·2026
Same author

Leveraging training expertise to build capacity in computational personalised medicine.

Bioinformatics advances·2026
Same author

Mesenchymal to epithelial transition (MET) in cancer progression: insights from logical modeling.

Scientific reports·2026
Same author

'Crossing borders' in data standardisation: application of OMOP CDM in an international clinical trial network in precision cancer medicine.

Acta oncologica (Stockholm, Sweden)·2026
Same author

Clinical outcomes of genomically guided trametinib monotherapy across cancer types: results from the IMPRESS-Norway trial.

Acta oncologica (Stockholm, Sweden)·2026
Same journal

Systematic design of auxotrophic strains and media conditions to probe metabolic functions in E. coli.

PLoS computational biology·2026
Same journal

Neuronal excitability and parameter variability in the Hodgkin-Huxley model.

PLoS computational biology·2026
Same journal

Delayed reward information is underweighted in reinforcement learning with dispersed feedback.

PLoS computational biology·2026
Same journal

GHF-ACL: A novel contrastive learning framework with multi-order graph structures for herb-disease association prediction.

PLoS computational biology·2026
Same journal

GATE: Adaptive learning with working memory by information gating in multi-lamellar hippocampal formation.

PLoS computational biology·2026
Same journal

Evaluating vectors for the design of a spillover-disrupting Lassa virus transmissible vaccine.

PLoS computational biology·2026
See all related articles

Related Experiment Video

Updated: Jan 17, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.3K

NeKo: A tool for automatic network construction from prior knowledge.

Marco Ruscone1,2,3,4, Eirini Tsirvouli5, Andrea Checcoli1,2,3,6

  • 1Institut Curie, Université PSL, Paris, France.

Plos Computational Biology
|September 16, 2025
PubMed
Summary
This summary is machine-generated.

NeKo is a Python package that automates biological network construction by integrating molecular interactions from databases. This tool streamlines the process, making network analysis more efficient for researchers studying cellular functions.

More Related Videos

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

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

Published on: June 13, 2025

1.3K

Related Experiment Videos

Last Updated: Jan 17, 2026

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.3K
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

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

Published on: June 13, 2025

1.3K

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Systems Biology

Background:

  • Biological networks are crucial for understanding molecular interactions and cellular functions.
  • Manual construction of these networks is time-consuming and labor-intensive.

Purpose of the Study:

  • To introduce NeKo, a Python package designed to automate the construction of biological networks.
  • To provide researchers with a flexible and efficient tool for integrating and prioritizing molecular interactions.

Main Methods:

  • NeKo integrates molecular interaction data from various public databases.
  • It allows users to specify molecules of interest (genes, proteins, phosphosites).
  • Users can apply flexible filtering strategies (e.g., direct/indirect, signed/unsigned interactions).

Main Results:

  • NeKo automates the time-consuming process of biological network construction.
  • Demonstrated utility in constructing networks from transcriptomics data (medulloblastoma) and modeling drug synergies.
  • Provides a streamlined and efficient approach to network building.

Conclusions:

  • NeKo enhances accessibility and efficiency for researchers in constructing biological networks.
  • The package facilitates deeper insights into cellular functions and biological processes through automated network analysis.