Search Results for "gnu science" - Page 3
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Showing 223 open source projects for "gnu science"
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CircularLogo is a light-weighted, easy to use web application that visualizes the intra-motif dependencies of a DNA or RNA motif.
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KAPPA (Key Aminoacid Pattern-based Protein Analyzer) is a sequence search program dedicated to the discovery and clustering of proteins defined by a key aminoacid pattern.
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Stochastic simulator for signaling pathways occuring in biological cells. Handles reaction-diffusion processes in 3D tetrahedral meshes. Please check our new repository: https://github.com/CNS-OIST/STEPS
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pybrn is a Python package for the analysis of biochemical reaction networks. It provides basic model handling capabilities, import from SBML, analysis of conservation relations, steady state computation and model simulation.
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This project houses software to analyze data acquired from electrophysiology experiments. Currently, we have an Octave/MATLAB program to analyze electroneurogram traces of coupled oscillators, and a Perl library for the analysis of voltage trace data
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converts a SAM file to fasta file. SAM file is a file output from bwa alignment software. It outputs aligned fasta file.
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The complexity of cellular networks is an outstanding challenge for documentation, visualisation and mathematical modelling. In this project, we develop a new way to describe these networks that minimises the combinatorial complexity and allows an automatic visualisation and export of mathematical (ODE/rulebased) models.
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Biskit is a python library for structural bioinformatics research. It simplifies the analysis of macromolecular structures, protein complexes, and molecular dynamics trajectories and offers a platform for the rapid integration of external programs. PLEASE NOTE: The Biskit source code as well as any later releases are now hosted on https://github.com/graik/biskit The sourceforge repo is only kept here for reference.
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LGTmate
Lateral Gene Transfer utility
LGTmate is a simple and powerful bioinformatic software tool to identify lateral gene transfer events and contaminants in Eukaryotic proteomes. It is available as a GUI or command-line application, with no dependencies and no installation required. -
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LipidXplorer is an uniqe software to identify lipids from high to low resolution mass spectra.
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Copy Number Analysis for Targeted Resequencing (CONTRA) is a tool for copy number variation (CNV) detection for targeted resequencing data such as those from whole-exome capture data.
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Moose
Multiscale Neuroscience and Systems Biology Simulator
Moose is the core of a modern software platform for the simulation of neural systems ranging from subcellular components and biochemical reactions to complex models of single neurons, large networks, and systems-level processes. We have moved Github.com. This should be your source for the latest version of the code. -
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HTSeq
Analysing high-throughput sequencing data with Python
This SourceForge page is outdated! HTSeq has been moved to github: https://github.com/simon-anders/htseq General information and documentation on HTSeq; http://www-huber.embl.de/users/anders/HTSeq -
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ENLY
Bioinformatic tool to improve draft genome assemblies by closing gaps
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ChIP-RNA-seqPRO
ChIP-RNA-sequencing-processing (ChIP-RNA-seqPRO)
ChIP-RNA-seqPRO: A strategy for identifying regions of epigenetic deregulation associated with aberrant transcript splicing and RNA-editing sites. Runnable python scripts packaged together with customized annotation libraries, demo data input and README guide. 9/26 : v1.1 Updated MAIN_IV to debug error thrown by python pandas no longer supporting 'subset'. This code will no longer be actively maintained/updated here. A cloud-based resource for comparative analysis of epigenetic,... -
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pyQPCR is a GUI application written in python that deals with quantitative PCR (QPCR) raw data. Using quantification cycle values extracted from QPCR instruments, it uses a proven and universally applicable model to give finalized quantification resu
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ExSTraCS
Extended Supervised Tracking and Classifying System
This advanced machine learning algorithm is a Michigan-style learning classifier system (LCS) developed to specialize in classification, prediction, data mining, and knowledge discovery tasks. Michigan-style LCS algorithms constitute a unique class of algorithms that distribute learned patterns over a collaborative population of of individually interpretable IF:THEN rules, allowing them to flexibly and effectively describe complex and diverse problem spaces. ExSTraCS was primarily developed... -
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The MeVisLab Community project provides add-on modules that extend the functionality of the MeVisLab software. The modules are provided and maintained by the MeVisLab developer community and can be compiled with the public MeVisLab SDK.
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ExAM-Exome_Analysis_And_Mining
A whole exome sequencing analysis package and its graphical interface
During the past few years, whole exome sequencing has imposed itself for genetic research, largely due to its use for detection of causative mutations responsible for Mendelian disorders. As a consequence of their power and of the rapidly decreasing cost of these technologies, massive amount of exome sequencing data are generated and becoming available to a broadening community of scientists. However, these data remain difficult to analyze and interpret by the general scientific community,... -
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The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.
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memesa-tools
A collection of tools used in the enumeration of solution spaces
This collection of tools forms the basis of a pipeline for the complete enumeration of the number of solutions present in a model that maximizes a single objective function. -
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NetView P
Population Genomics Network Analysis Pipeline
NetView P has been re-structured as a package for R and moved to GitHub: https://github.com/esteinig/netview -
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BioImageXD - free open source software for analysis, processing and 3D rendering of multi dimensional, multi data channel, time series image data from microscopy and other sources.
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DEAPathways
Differential Expression Analysis for Pathways
This project contains the source code associated with the PLoS Computational Biology publication: "Differential Expression Analysis for Pathways". The paper text can be found here: http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002967
