Search Results for "data modeling"

NeuroML is an XML-based description language for defining and exchanging neuronal cell, network and modeling data including reconstructions of cell anatomy, membrane physiology, electrophysiological data, network connectivity, and model specification

This project moved to GitHub in 2021 and is available at: https://cbrinkrolf.github.io/VANESA/ This tool is a platform-independent software to create individual pathways and to examine biological networks of distributed, heterogeneous data sources, e.g. KEGG, BRENDA. VANESA also offers Petri net modeling of extended hybrid Petri nets which can be also simulated using the OpenModelica framework.

Use statistical methods to analyze time-course data (gene expression microarray and RNA-seq data in particular, but not limited to). Apply significance tests to filter out only significant genes or time series. Cluster time series into similar groups. Generate network models, including linear or non-linear models. Variable selection and optimization routines included. Written in Scala and R. The application is a cross-platform desktop app with a simple GUI and is fully functional...

The Protein Geometry Database hosts the development code for a flexible database for searching protein geometry, as well as a library for accessing this data for protein modeling & refinement programs.

The VRML97-Import-Script is a Python-Script, that extends the capabilities of Blender to import VRML97-Files. It supports Blender since version 2.42.

JPhysChem - a mathematical modeling toolbox designed to provide an abstract layer and a comprehensive graphical front-end for general model building and specific modeling and data processing in the field of mass spectrometry and physical chemistry.

Experimental Lindenmayer System generator, in 3D using OpenGL. Used for modeling the fractal growth processes of plants.

Our goal is to create an open source framework and toolset for modeling dynamic cellular network functions, and to develop a user community committed to using, extending and exploiting these tools to further our knowledge of biologic processes.