OpenMM

Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.

Map view:

Zoom: 100%

More settings

Connection length 100% Label size 100% Node size 100% Line width 100% Label width 100%

Export map as:

OpenMM topic overview

The analysis highlights Features and Overview as prominent areas in the source structure around OpenMM.

Related topics: 16
Source areas: 2
Connected nodes: 18
Extracted relationships: 22
Concept neighborhoods: 12
Bridge connections: 18

What this topic covers Research coverage

Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.

Overview · 9 topics

Features · 7 topics

Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.

Key facts & relationships

High-confidence facts extracted from structured source data. Use them as anchors for further research.

Available in: English
Developers: Stanford University Memorial Sloan Kettering Cancer Center Pompeu Fabra University National Heart, Lung, and Blood Institute
License: MIT License LGPL
Operating system: Linux, macOS, Windows
Original author: Peter Eastman
Platform: Many

Explore all related topics Closing gaps

Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.

Overview

Features

Wrapper Wrapper library
Commonly used force fields Force field (chemistry)
Integrators Numerical integration
Langevin Langevin equation
Verlet Verlet integration
Nosé–Hoover Nosé–Hoover thermostat
Brownian Brownian motion

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

How OpenMM connects Entity context

The extracted context around OpenMM shows recurring relationship patterns in the source. For example, OpenMM → API, Brownian, Developers, Hoover, Langevin, Nosé, Python, Users, Verlet Another extracted example is OpenMM → English. Use these groups to spot repeated connection types before inspecting the individual relationships.

Top relations

related to Features · 9

OpenMM → API, Brownian, Developers, Hoover, Langevin, Nosé, Python, Users, Verlet

Available in · 1

OpenMM → English

Developers · 1

OpenMM → Stanford University Memorial Sloan Kettering Cancer Center Pompeu Fabra University National Heart, Lung, and Blood Institute

License · 1

OpenMM → MIT License LGPL

Operating system · 1

OpenMM → Linux, macOS, Windows

Original author · 1

OpenMM → Peter Eastman

Platform · 1

OpenMM → Many

Release · 1

OpenMM → January 20, 2010; 16 years ago (January 20, 2010)

Repository · 1

OpenMM → github.com/openmm/openmm

Stable release · 1

OpenMM → 8.2.0 / 8 November 2024; 21 months ago (2024-11-08)

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

core22 dynamics simulations gpus molecular cuda pande lab via also written peter eastman stanford university force folding home python integrators

OpenMM relationships Subject–Predicate–Object triples

TTTA extracted 22 structured relationships around OpenMM. Examples in this analysis include OpenMM → Available in → English and OpenMM → Developers → Stanford University Memorial Sloan Kettering Cancer Center Pompeu Fabra University National Heart, Lung, and Blood Institute. The table shows each extracted connection, where it came from and its confidence.

Subject	Predicate	Object	Confidence	Src
OpenMM	Available in	English	1.00	infobox
OpenMM	Developers	Stanford University Memorial Sloan Kettering Cancer Center Pompeu Fabra University National Heart, Lung, and Blood Institute	1.00	infobox
OpenMM	License	MIT License LGPL	1.00	infobox
OpenMM	Operating system	Linux, macOS, Windows	1.00	infobox
OpenMM	Original author	Peter Eastman	1.00	infobox
OpenMM	Platform	Many	1.00	infobox
OpenMM	Release	January 20, 2010; 16 years ago (January 20, 2010)	1.00	infobox
OpenMM	Repository	github.com/openmm/openmm	1.00	infobox
OpenMM	Stable release	8.2.0 / 8 November 2024; 21 months ago (2024-11-08)	1.00	infobox
OpenMM	Type	Molecular dynamics	1.00	infobox
OpenMM	Website	openmm.org	1.00	infobox
OpenMM	Written in	C++, C, CUDA, Python	1.00	infobox
OpenMM	is a	library for performing molecular dynamics simulations on a wide variety of hardware architectures	0.90	text

Related concept clusters Concept neighborhoods

The concept neighborhoods around OpenMM bring nearby vocabulary together. In this analysis, examples include Dynamics, Also and Cuda. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

OpenMM
- Dynamics
- Also
- Cuda
- Gpus
- Via
- Core22
- Molecular
- Simulations
- Architectures
- Hardware
- Opencl
- Performing
openmm
- Dynamics
- Also
- Cuda
- Gpus
- Via
- Core22
- Molecular
- Simulations
- Architectures
- Hardware
- Opencl
- Performing
molecular dynamics
- Openmm
- Also
- Cuda
- Dynamics
- Molecular
- Simulations
- Architectures
- Hardware
- Library
- Opencl
- Performing
- Python
protein dynamics
- Openmm
- Also
- Cuda
- Molecular
- Simulations
- Architectures
- Hardware
- Library
- Opencl
- Performing
- Python
- Variety
cuda
- Dynamics
- Opencl
- Openmm
- Python
- Developers
- Eastman
- Gpus
- Lab
- Many
- Pande
- Peter
- Stanford
vijay s. pande
- Opencl
- Written
- Also
- Cuda
- Gpus
- Stanford
- University
- Via
- Core22
- Simulations
stanford university
- University
- Python
- Also
- Cuda
- Developers
- Many
- Well
- Written
gpus
- Via
- Opencl
- Openmm
- Cuda
- Lab
- Pande
- Simulations

Connections between topic areas Semantic bridges

For OpenMM, one of the stronger structural bridges in this analysis connects OpenMM with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.

Min side: 3

OpenMM — Overview · splits 9 ⟂ 10

OpenMM — Features · splits 11 ⟂ 8

Map overview Semantic statistics

OpenMM

Nodes19

Edges18

Triples22

Avg. degree1.89

Density0.105263

Components1

Source & methodology

TTTA analyzes the structure around OpenMM to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Features & Overview, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — OpenMM · EN edition · Analysis: TopicsToTalkAbout