Biomolecular visualization using AVS (original) (raw)

Integrating Computation and Visualization for Biomolecular Analysis: An Example Using Python and AVS

Pacific Symposium on Biocomputing, 1999

One of the challenges in biocomputing is to enable the efficient use of a wide variety of fast-evolving computational methods to simulate, analyze, and understand the complex properties and interactions of molecular systems. Our laboratory investigates several areas including molecular visualization, protein-ligand docking, protein-protein docking, molecular surfaces, and the derivation of phenomenological potentials. In this paper we present an approach based on the Python programming language to achieve a high level of integration between these different computational methods and our primary visualization system, AVS. This approach removes many limitations of AVS while increasing dramatically the inter-operability of our computational tools. Several examples are shown to illustrate how this approach enables a high level of integration and inter-operability between different tools, while retaining modularity and avoiding the creation of a large monolithic package that is difficult to extend and maintain.

Integrating Biomolecular Analysis and Visual Programming

2007

One of the challenges in bio-computing is to enable the efficient use of a wide variety of rapidly evolving computational methods to simulate, analyze and understand complex interactions of molecular systems. Our laboratory is interested in the development of novel computational technologies and in the application of these technologies to the analysis and understanding of complex biological systems. We have been using the Python programming language as a platform to develop reusable and interoperable components dealing with different aspects of structural bioinformatics. These components are the basic building blocks from which several domain specific applications have been developed. In this paper we describe the integration of two applications developed in our laboratory: PMV and a visual-programming environment. PMV is a general purpose, command-driven molecular visualization and manipulation program built from reusable software components. The visual-programming environment enab...

The Molecular Biology Toolkit (MBT): a modular platform for developing molecular visualization applications

BMC bioinformatics, 2005

The large amount of data that are currently produced in the biological sciences can no longer be explored and visualized efficiently with traditional, specialized software. Instead, new capabilities are needed that offer flexibility, rapid application development and deployment as standalone applications or available through the Web. We describe a new software toolkit--the Molecular Biology Toolkit (MBT; http://mbt.sdsc.edu)--that enables fast development of applications for protein analysis and visualization. The toolkit is written in Java, thus offering platform-independence and Internet delivery capabilities. Several applications of the toolkit are introduced to illustrate the functionality that can be achieved. The MBT provides a well-organized assortment of core classes that provide a uniform data model for the description of biological structures and automate most common tasks associated with the development of applications in the molecular sciences (data loading, derivation o...

MDScope — a visual computing environment for structural biology

Computer Physics Communications, 1995

MDScope is an integrated set of computational tools which function as an interactive visual computing environment for the simulation and study of biopolymers. This environment consists of three parts: (1) vmd, a molecular visualization program for interactive display of molecular systems; (2) namd, a molecular dynamics program designed for performance, scalability, modularity, and portability, which runs in parallel on a variety of computer platforms; (3) MDCOMM, a protocol and library which functions as the unifying communication agent between the visualization and simulation components of MDScope. ~ is expressly dedgned for distributed memory parallel architectures and uses a spatial decomposition parallelization ~ategy COUlfled with a multi-threaded, message-driven computation model which reduces inefficiencies due to communi¢~tlion latency. Through the MDCOMM software, vmd acts as a graphical interface and interactive control for namd, allowing a user running flamd to utilize a parallel platform for computational power while Visualizing the trajectory as it is computed. Modularity in both vmd and namd is accomplished through an object-oriented design, which facilitates the addition of features and new algorithms. the study of biopolymer aggregates like membranes, and to protein structure prediction. Widely used MD applications include CHARMm [5], X,PLOR [8], GROMOS [29], AMBER [30], and CEDAR [10].

Avogadro: An advanced semantic chemical editor, visualization, and analysis platform

Journal of Cheminformatics, 2012

The Avogadro project has developed an advanced molecule editor and visualizer designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas. It offers flexible, high quality rendering, and a powerful plugin architecture. Typical uses include building molecular structures, formatting input files, and analyzing output of a wide variety of computational chemistry packages. By using the CML file format as its native document type, Avogadro seeks to enhance the semantic accessibility of chemical data types.

Molecular Graphics: Bridging Structural Biologists and Computer Scientists

Structure

Visualization of molecular structures is one of the most common tasks carried out by structural biologists, yet the technical details and advances required to e ciently display molecular structures are often hidden from the end user. During decades molecular viewer software such as Chimera, COOT, PyMOL, or VMD provided the most common solutions to quickly visualize structures. Nowadays, new and e cient ways to depict molecular objects are changing how structural biologists interact with their data. Such novelties are often driven by advances made by computer scientists, but an important gap remains between this community and the final users such as structural and computational biologists. In this perspective article, we clarify how developments from computer graphics and data visualization have led to novel ways of understanding protein structure. We present future developments from computer science that will be beneficial for structural biology. By pointing to canonical papers and explaining technical progress underlying new graphical developments in simple terms, we hope to promote communication between the di↵erent communities to shape future developments in molecular graphics.