3Dmol.js: molecular visualization with WebGL

By Nicholas B Rego, David Ryan Koes. 2014

334 citations recorded by the source corpus.

Summary: 3Dmol.js is a modern, object-oriented JavaScript library that uses the latest web technologies to provide interactive, hardware-accelerated three-dimensional representations of molecular data without the need to install browser plugins or Java. 3Dmol.js provides a full featured API for developers as well as a straightforward declarative interface that lets users easily share and embed molecular data in websites. Availability and implementation: 3Dmol.js is distributed under the permissive BSD open source license. Source code and documentation can be found at http://3Dmol.csb.pitt.edu Contact: dkoes@pitt.edu

Subfields: Materials Chemistry, Physical and Theoretical Chemistry

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Materials Chemistry

In Physical and Theoretical Chemistry

Citations in the corpus

CATH: an expanded resource to predict protein function through structure and sequence (2016, positive): “js, a 3D molecular structure viewer (24).”
mTM-align: a server for fast protein structure database search and multiple protein structure alignment (2018, background): “(iii) The visualization of the alignment by the 3Dmol library (23).”
PDBsum: Structural summaries of PDB entries (2017, methodology): “Previously the images were static ones, generated using the PyMOL molecular graphics program, 17 but have recently been replaced by a JavaScript molecular viewer called 3Dmol.js, 18 developed at the University of Pittsburgh School of Medicine.”
NGL viewer: web‐based molecular graphics for large complexes (2018, neutral): “js (Rego and Koes, 2015), ChemDoodle (Burger, 2015), iCn3D github.”
Improvements to the APBS biomolecular solvation software suite (2017, methodology): “js [76, 77] to provide web-based setup and visualization of APBS-PDB2PQR calculations and related workflows.”
NGLview–interactive molecular graphics for Jupyter notebooks (2018, methodology): “Related tools that integrate molecular graphics in Jupyter notebooks include 3dmol.js (Rego and Koes, 2015), chemview (https://github.com/gabrielelanaro/chem view) and pv (https://github.com/biasmv/pv).”
Integration of the Rosetta suite with the python software stack via reproducible packaging and core programming interfaces for distributed simulation (2019, methodology): “Existing tools for web-based bio-molecular visualization, such as py3dmol 19 and NGLview, 20 extend this interface to a fully-featured biomolecular simulation, analysis, and visualization environment.”
COACH-D: improved protein–ligand binding sites prediction with refined ligand-binding poses through molecular docking (2018, positive): “The visualization of the complex structure is obtained by the 3Dmol library (20).”