Free java graph visualization software for linux

Genomorama: Genome Visualization is a multi-scale, multi-genome, multi-platform visualization and analysis program. It provides a powerful yet easy to use interface that leverages the visualization power of modern computers (via OpenGL) and the substantial bioinformatic infrastructure provided by the NCBI (via the NCBI C toolkit).
Genomorama is written in portable, highly optimized C++ and comes in three "flavors" that allow it to run natively on (most) modern operating systems: OS X (using Carbon), Microsoft Windows (using MFC), and Linux (using Motif). Executables and source code are freely provided for all flavors.
Main features:
- High performance has not been sacrificed on the altar of portability
- OpenGL graphics take advantage of the video-game optimized graphics cards available in most desktop and laptop computers.
- C++ allows transparent and complete utilization of system resources (like memory).
- Native windowing toolkits (Carbon, MFC and Motif) for every operating system facilitate responsiveness and ease of use.
- A stand-alone, self-contained executable frees Genomorama from dependence on third party applications.
- Source code for all platforms is freely available.
- An attractive, full featured user interface
- Genomorama presents a clean, uncluttered user interface.
- Multi-scale rendering displays relevant details while maintaining readability.
- Use a keyboard or a mouse to efficiently zoom, pan and explore genomes of arbitrary size.
- Attractive WYSIWYG Postscript and GIF output formats yield publication quality images.
- Novel features to aid genome analysis
- In addition to the standard searching options (like query by sequence and gene name), Genomorama offers "forward and reverse" DNA hybridization based searches.
- Provide a pair of PCR primers, and Genomorama will output the amplicons.
- Provide a hybridization probe and Genomorama will find binding sites.
- Provide a pair of Padlock probes and Genomorama will identify binding locations
- Provide a set of PCR primer criteria (length, melting temperature, base composition, etc.) and Genomorama will find PCR primers.
- Genomorama can display and search an arbitrary number of genomes (limited only by computer memory).
- Harness the power of the NCBI toolkit to directly access and search the NCBI Entrez database.
- Compute melting profile, in addition to traditional base composition plots (i.e. %G+C, %A+T, etc).
Enhancements:
- This release fixes the following bugs: parsing gbk files that contain single base annotations on the complement strand;
- missed exact matches at 3 end of target sequence;
- fragile parsing of annotation range;
- downloading of very large Genbank records (i.e. human chromosomes);
- and omitted intergenic space following single base annotations (i.e. SNPs).
- Custom color records are now saved to and read from GBK files.
- An OS X Intel-specific executable has been added.
- The information dialog box has been made resizable.

The Visualization ToolKit (VTK) is an open source, freely available software system for 3D computer graphics, image processing, and visualization used by thousands of researchers and developers around the world. Visualization Toolkit consists of a C++ class library, and several interpreted interface layers including Tcl/Tk, Java, and Python.
Professional support and products for VTK are provided by Kitware, Inc. VTK supports a wide variety of visualization algorithms including scalar, vector, tensor, texture, and volumetric methods; and advanced modeling techniques such as implicit modelling, polygon reduction, mesh smoothing, cutting, contouring, and Delaunay triangulation. In addition, dozens of imaging algorithms have been directly integrated to allow the user to mix 2D imaging / 3D graphics algorithms and data.
The design and implementation of the library has been strongly influenced by object-oriented principles. VTK has been installed and tested on nearly every Unix-based platform, PCs (Windows 98/ME/NT/2000/XP), and Mac OSX Jaguar or later.
Many resources exist to help you utilize the full potential of VTK in your application area. These resources include:
Mailing List: Over 1900 users are subscribed to this list. A great place to post questions, and search for answers.
VTK Textbook: The Visualization Toolkit, An Object-Oriented Approach To 3D Graphics, 3rd edition, ISBN 1-930934-12-2, now published by Kitware. This is a great book to read if you want to learn the details of the visualization algorithms and data structures. The book is often used as a college text in visualization and graphics courses.
VTK Users Guide: The Visualization Toolkit Users Guide, ISBN 1-930934-13-0, published by Kitware. This is the book to get if you want to learn how to install and use VTK.
ParaView Guide: The ParaView Guide, ISBN 1-930934-14-9, published by Kitware. ParaView is a turn-key visualization system build on top of VTK, and makes VTK easier to use with an interactive, point and click interface. ParaView also supports supercomputing applications, including tiled display and distributed parallel processing.
CMake: Mastering CMake, ISBN 1-930934-11-4, published by Kitware. CMake is the premier, cross-platform build system used to compile and link VTK. A useful book if you want to use VTK in your projects.
Support: A variety of support options are available ranging from the single point-of-contact Professional Subscription to get you up and running, to custom Site Support to help you develop your next product with VTK.
Enhancements:
- Many bugs were fixed, including fixes for memory leaks, array bounds errors, and stack overflows.

Graphviz - Graph visualization is a way of representing structural information as diagrams of abstract graphs and networks. Automatic graph drawing has many important applications in software engineering, database and web design, networking, and in visual interfaces for many other domains.

Graphviz is open source graph visualization software. It has several main graph layout programs. See the gallery for some sample layouts. It also has web and interactive graphical interfaces, and auxiliary tools, libraries, and language bindings.

The Graphviz layout programs take descriptions of graphs in a simple text language, and make diagrams in several useful formats such as images and SVG for web pages, Postscript for inclusion in PDF or other documents; or display in an interactive graph browser. (Graphviz also supports GXL, an XML dialect.)

Graphviz has many useful features for concrete diagrams, such as options for colors, fonts, tabular node layouts, line styles, hyperlinks, and custom shapes.

In practice, graphs are usually generated from an external data sources, but they can also be created and edited manually, either as raw text files or within a graphical editor. (Graphviz was not intended to be a Visio replacement, so it is probably frustrating to try to use it that way.)

Java Tetris project is a simple Tetris game.
Java Tetris is a game written with Eclipse and the VE Plugin. It is a nice starting point if you want to learn Java and Eclipse.
The game can be started as Java applet or Java application.
Enhancements:
- The dependency on jdom was removed.
- The jar is now only 30kb.
- A bug was fixed in the score list.

Sun Java Platform Enterprise Edition (Java EE) is the industry standard for developing portable, robust, scalable, and secure server-side Java applications.

Building on the solid foundation of Java SE, Java EE provides Web services, component model, management, and communications APIs that make it the industry standard for implementing enterprise class service-oriented architecture (SOA) and Web 2.0 applications.

FreeCell Java Applet project is a Java applet of the popular FreeCell card game.

This is a Java applet of the popular FreeCell card game.

FreeCell is the enormously popular solitaire game. Because all cards are visible at the start of the game, it is almost entirely a game of skill.

Almost all FreeCell positions can be won. The most notable exception is the game #11982.

graph-tool project is a program to help with statistical analysis of graphs.
Main features:
- support for directed and undirected graphs
- support for arbitrary vertex or edge properties
- generic filtering of edges and vertices
- several statistical measurements:
- degree (or scalar property) histogram
- vertex-vertex degree (or scalar property) correlation
- average nearest neighbours degree (or scalar property)
- vertex-edge-vertex correlation
- clustering coefficients
- assortativity coefficient
- average distance
- component statistics
- generation of random graphs with arbitrary degree distribution and degree correlation
- graph history measurement based on filtering
- support for graphml and dot file formats
The core algorithms are written in C++, making use of the Boost Graph Library, and template metaprogramming techniques, with performace in mind. The command line interface and other outlying code are written in python.