Search Results for "data capture framework"

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.

polyglot framework using Python/C++/JavaScript to fast develop applications to analyze biological sequences

Ericscript is a computational framework to detect gene fusions from paired end RNA-seq data with high sensitity and specificity.

JFASTA is a lightweight framework for handling FASTA files. It supports reading, writing and parsing of single- or multi-FASTA files. Files may be read/ written at once, or stream-based (memory efficient). It's stable, very intuitive and good integrated with Java 1.5 SDK and later.

The BioUtils - Proteomics package is a lightweight Java framework for handling commonly used data produced and needed in the field of Mass spectrometry in general and especially in the field of Proteomics. It's stable, intuitive to use and good integrated with Java 6 SDK and later.

MZmine 2 is a framework written in Java for differential analysis of mass spectrometry data.

Framework for text mining, data integration and data analysis. Keywords: ontology and graph alignment, relation mining, warehouse, semantic database integration, bioinformatics, systems biology, microarray, Java.

...It performs approximate Bayesian computation for stochastic models having latent dynamics defined by stochastic differential equations (SDEs) and not limited to the "state-space" modelling framework. Both one- and multi-dimensional SDE systems are supported and partially observed systems are easily accommodated. Variance components for the "measurement error" affecting the data/observations can be estimated. A 50-pages Reference Manual is provided with two case-studies implemented and discussed. The methodology is based on the research article available at http://arxiv.org/abs/1204.5459 Author's research page is http://www.maths.lth.se/matstat/staff/umberto/

GenOO-HTS [jee-noo] is an open-source; object-oriented Perl framework specifically developed for the design of High Throughput Sequencing (HTS) analysis tools. The primary aim of GenOO-HTS is to make simple HTS analyses easy and complicated analyses possible. GenOO-HTS models biological entities into Perl objects and provides relevant attributes and methods that allow for the manipulation of high throughput sequencing data.

Darwin 2: Java Framework for Evolutionary Computation (genetic algorithm, GA). A true framework with out-of-the-box functionality and extensibility of all classes. Interface-based pattern with dependency-injection to configure components.

Python module for manipulation of Crystallographic Information Framework (CIF) files

A comparative map and trait visualization framework enabling visual integration of genomic data from disparate data sources and allowing rich client-side interactivity and manipulation. Extensible through plugins for new datasources and algorithms.

Anna is lightweight Java framework to build pipeline systems of any kind. It will take care of recurrent needs such as dependency management, data serialisation and synchronization as well as parallelization of execution.

A collection of tools for working with the comparative data analysis ontology including import/export facilities for common phylogenetic file formats, and also a triple-store framework.

A lightweight, browsing-based, 100% Python, federated data integration framework. Users may create custom schemas for disparate sources, query and expand results across sources to find related data; for use in fields such as bioinformatics and datamining

Structure is a framework for two-dimensional molecular visualization written in Java and based on Octet.

Dogwood is an ontology-aware Distributed Annotation System (DAS) server framework for the integration of biological, biomedical and clinical data.

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.

The ORIEL workbench is a data browsing interface for REST-based information retrieval services. Originally developed for Bioinformatics applications.

CSBI is a component based framework that allows for inter-component data sharing and access. GINY is an Open Source Graph Library.

BioCSharp is an open-source project designed to provide a bioinformatics .NET framework for processing biological data. It will include objects for manipulating sequences, file parsers, DAS, database access and analysis and statistical routines.

TAS (Transcription Analysis System) is a multi-tier framework for running parameterized SQL queries. Users can analyze new data or new combinations of data with a few clicks in a GUI. Potentially complex/repetitive database interaction is all automated

A framework for image analysis and data analysis, aimed towards microscopy and the needs of current research.