Difference between revisions of "Features"
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BioUML utilizes a wide variety of '''methods for data analyses''': | BioUML utilizes a wide variety of '''methods for data analyses''': | ||
| − | * | + | * [[:BSA (analyses group)|biosequence analysis]], |
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| − | * | + | * [[:Category:Statistics (analyses group)|statistics]], |
| − | + | * many other [[:Category:Analyses|analyses]], | |
| − | * statistics, | + | * executing analysis from JavaScript. |
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==Other features== | ==Other features== | ||
Revision as of 12:51, 4 May 2013
The main BioUML features (shared by all editions) are listed below.
Contents |
Supported standards
The following systems biology standards are applied in BioUML:
BioUML supports SBML Level 1 version 1-2; Level 2 versions 1-4; Level 3 version 1. BioUML is the only simulator that has passed all the tests from the SBML test suite version 2.0 (test details).
BioUML supports Process Diagrams as they are defined by SBGN version 1.0.
BioUML can import data in BioPAX 2.0 format. Imported data can be stored as native BioPAX file, SQL or text database.
BioUML supoorts data in PSI-MI format.
BioUML can import ontology in OBO 1.2 format. Imported data can be presented as dependences diagram.
- CellML - Cell Markup Language. BioUML can read and simulated biochemical models presented in CellML 1.0 format.
BioUML also supports JavaScript (script console, JavaSsript editor, JavaScript debugger (BioUML workbench only), JavaScript preprocessor (allows to embed easily R expressions), R (connect to R on local or remote machine, convert BioUML data to R and save R results as BioUML data, R graphics support, R preprocessor for JavaScript) and SQL (SQL console, direct SQL access to analysis results tables).
Databases
It works with the main biological databases:
- catalogues: Ensembl, UniProt, ChEBI, GO;
- pathways: KEGG, Reactome, EHMN, BioModels, SABIO-RK, TRANSPATH, EndoNet, BMOND.
Search tools
BioUML provides powerful search possibilities with such tools as:
- full text search (Apache Lucene is used),
- graph search - finds related pathway components and presents results as an editable graph.
Graph layout engine
- includes different layout algorithms:
- force directed layout,
- hierarchical layout,
- cross grid layout (Kato,M. et al., 2005: Automatic drawing of biological networks using cross cost),
- fast grid layout (Kaname, K., Masao, N. and Satoru, M., 2008: Fast grid layout algorithm for biological networks with sweep calculation);
- supports incremental graph layout;
- supports compartments;
- layout preview;
- possibility to reuse layout for similar diagrams.
Visual modeling tools
- powerful diagram editor;
- virtual experiment - variations of diagram to simulate different experimental conditions, knock-outs, etc.;
- automated generation of optimized Java code for model simulation from corresponding pathway diagram;
- different solvers for differential equations:
- JVODE - ported to Java version of CVODE,
- RADAU IIA - (implicit Runge-Kutta method for stiff delay differential equations),
- Imex - (implicit Runge-Kutta method for stiff differential equations),
- Dormand-Prince - (explicit Runge-Kutta method),
- Euler (for debugging complex models);
- supports different model types:
- ODE - odinary differential equations,
- DAE - differential algebraic equations,
- ODE/DAE with delay,
- 1D PDE (for blood flow simulation),
- hybrid models support (with events, states and transitions),
- hierarchical models;
- plots (using JFreeChart)
- time series,
- phase portrait.
Parameters fitting
- experimental data - time courses or steady states;
- experimental data - exact or relative values of substance or concentrations;
- multiexperiment fitting;
- global and local parameters for multiexperiment fitting;
- constraint support;
- different optimization methods:
- Adaptive Simulating Annealing,
- Cellular genetic algorithm,
- Evolution strategy (SRES),
- GLBSOLVE,
- Particle swarm optimization,
- Quadratic Hill-climbing;
- optimization and parallelization of computations;
- JavaScript API for parameters fitting;
Genome browser
- uses AJAX and HTML5 <canvas> technologies (BioUML web edition);
- interactive - dragging, semantic zoom;
- DAS support (Distributed Annotation System);
- tracks support:
- Ensembl tracks
- DAS tracks
- user-loaded BED/GFF/Wiggle files
Analyses
BioUML utilizes a wide variety of methods for data analyses:
- biosequence analysis,
- model optimization,
- statistics,
- many other analyses,
- executing analysis from JavaScript.
Other features
BioUML also allows for workflows, reproducible research
- actions journal,
- Analysis,
- JavaScript,
- SQL requests,
- allows to present set of actions in research diagram,
- allows to build and execute workflow document,
and generating reports, templates
- different templates for representing data element info
- model reports
- Overview
- Reactions
- Parameters
- Variables
- ODE(model as differential equation system).
