Search Results for "qt-based" - Page 3
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Showing 176 open source projects for "qt-based"
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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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openModeller is a complete C++ framework for species potential distribution modelling. The project also includes a graphical user interface, a web service interface and an API for Python.
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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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ChIP-RNA-seqPRO
ChIP-RNA-sequencing-processing (ChIP-RNA-seqPRO)
...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, sequence variation, and expression datasets is now available. Please visit the Cloudomics, project for cloud-based resources: https://sourceforge.net/projects/cloudomics-for-aws/ -
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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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TinkerCell is a software for synthetic biology. The visual interface allows users to design networks using various biological "parts". Models can include modules and multiple cells. Users can program new functions using C or Python. www.tinkercell.
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StochPy - Stochastistic modeling in Python - is an easy-to-use package, which provides several stochastic simulation algorithms and unique analysis techniques, which can be used for stochastic simulations of biochemical systems.
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Stochastic Rule Builder (SRB)
Modeling framework for capturing positional and temporal dynamics
...Our framework describes individual regulatory components using generic action oriented descriptions of their biochemical interactions with a DNA sequence. All the possible actions are based on the current state of factors bound to the DNA. We developed a rule builder to automatically generate the complete set of biochemical interaction rules for any given DNA sequence. Off-the-shelf stochastic simulation engines can model the behavior of a system of rules and the resulting changes in the configuration of bound factors can be visualized. -
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Maximum Common Genome Alignment (MCGA)
Pipeline for creating core genome alignments for phylogenetic analysis
Maximum Common Genome Alignment (MCGA) Tool MCGA is a bioinformatics analysis tool written in Python for generating core genome alignment for bacterial whole genome sequences which can be used to construct phylogenetic trees. -
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scipion-xmipp
Image processing framework to integrate EM software packages.
Scipion is an image processing framework to obtain 3D models of macromolecular complexes using Electron Microscopy (3DEM). It integrates several software packages and presents an unified interface for both biologists and developers. Scipion allows to execute workflows combining different software tools, while taking care of formats and conversions. Additionally, all steps are tracked and can be reproduced later on. Xmipp is a well-known package in the EM image processing. It is integrated... -
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GASiC
Genome Abundance Similarity Correction
One goal of sequencing based metagenomic analysis is the quantitative taxonomic assessment of microbial community compositions. However, the majority of approaches either quantify at low resolution (e.g. at phylum level) or have severe problems discerning highly similar species. Yet, accurate quantification on species level is desirable in applications such as metagenomic diagnostics or community comparison. -
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pipasic
pipasic: Protein Abundance Correction in Metaproteomic Data
...These challenges are similar but not identical to the challenges arising in the analysis of metagenomic samples and require specific solutions. pipasic (peptide intensity-weighted proteome abundance similarity correction) is a tool which corrects identification and spectral counting based quantification results using peptide similarity estimation and expression level weighting within a non-negative lasso framework. pipasic has distinct advantages over approaches only regarding unique peptides or aggregating results to the lowest common ancestor. -
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fitGCP
Fitting genome coverage distributions with mixture models
...fitGCP is a framework for fitting mixtures of probability distributions to genome coverage profiles. Besides commonly used distributions, fitGCP uses distributions tailored to account for common artifacts. The mixture models are iteratively fitted based on the Expectation-Maximization algorithm. Please find the accompanying paper here: http://dx.doi.org/10.1093/bioinformatics/btt147 -
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xmipp
Image processing suite for Electron Microscopy
XMIPP is an image processing suite for 3D-reconstruction of biological specimens from transmission electron microscopy data. NOTE that stable releases (including binaries) are longer stored at Sourceforge, but are available at http://xmipp.cnb.csic.es -
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PhyloTrack
PhyloTrack, D3.js and JBrowse for phylogeny and positioning of samples
PhyloTrack is a JavaScript--based software tool that integrates the D3.js library for data visualization with the JBrowse tool for genome browser representation. It requires a phylogenetic tree of the common Newick data format as input, as well as three meta data files for samples, clade-defining nodes and clade color definitions - all in tab delimited format. Functionality within PhyloTrack shows the informative markers at each node in the phylogenetic tree, therefore highlighting clade-defining polymorphism. ... -
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openSEQ
NGS compute distro proloaded with pipeline analysis software
Forked Ubuntu 14.04 minimal install with XOrg and FluxBox desktop environment for web-based pipeline construction and job submission. HOWTO: 1) Set VM network settings to a bridged adapter type. 2) Load VM to client 3) From host: $ ssh -X ubuntu@<foobar> 'firefox && butterfly.server.py --unsecure' --- passwd = 616287xx 5) or ssh into host with X forwarding, and type runme This will launch an X-session of Firefox on the client, which will then be forwarded to the host. ... -
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InMethyl
Design of target-specific primers for bis. sequencing of CpG-islands
...This balance is based on the calculation of scoring factor including primer pair specificity, nucleotide composition (sequence complexity), thermodynamic features (melting temperature, dimers dG etc.), presence of CpG-sites and other parameters. Users are intended to customize the desired or limit ranges of these values, as well as penalties for out-of-bounds values. -
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Ymap - Yeast Mapping Analysis Pipeline
Pipeline for large-scale genome changes analysis of genome datasets.
The active use repository has migrated over to: https://github.com/darrenabbey/ymap The repository here was errantly created with some large binary files included. Attempts to extract the files from the history here have failed. A copy of the history was successfully scrubbed and then hosted at github. -------- Eukaryotic pathogens have complicated and dynamic genomes. To facilitate analysis of copy number variations (CNV), single nucleotide polymorphisms (SNPs), and loss of... -
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MDcons(Molecular Dynamics consensus)
Interpretation of Biomolecular MD simulations
MDcons is a tool to analyze conserved contacts during Molecular Dynamics (MD) simulations of Protein, Rna, Dna & Ligand based complexes. The input is either a Molecular Dynamics trajectory or a set of snapshots. The input can also be a single snapshot. The outputs are (1) map of most/less frequently conserved contacts during MD (2) a list of most/less frequently conserved contacts during MD. -
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miRStat
identification of common sets of microRNAs for groups of genes
miRStat enables identification of regulatory microRNA targeting several genes in a custom gene group. This Python application is based on the TargetScan 6.2 microRNA target prediction data. Conserved and Nonconserved site context+ scores files are required (unzip and place to directory with program). Available at http://targetscan.org/cgi-bin/targetscan/data_download.cgi?db=vert_61 -
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Spatio-temporal simulation environment (STSE) is set of tools used to perform spatio-temporal simulations, dedicated mainly to biological systems. Main development language is Python. Tools are currently based on: EPD, VTK, qhull, openalea, PlantGL.
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Pathomx
Workflow-based data analysis built on IPython
Pathomx is a workflow-based tool for the analysis and visualisation of experimental data. Initially created as a tool for metabolomic data analysis is has been extended and can now be used for any scientific and non-scientific data analysis. -
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mitoMaker
mitoMaker - a mitochondria assembly and annotation script
mitoMaker is a pipeline script developed to simplify the assembly and automatic annotation of mitochondrial genomes, based on raw NGS reads and an optional target reference. mitoMaker calls well known assemblers and algorithms, such as SOAPdenovo, MIRA and blast+ and parses their results providing easily readable outputs, such as FASTA, GENBANK, SEQUIN, PNG and others. General pipeline: 1-iterative De Novo assembly, with different k-mer values, trying to assemble a build that matches a target mitochondrial genome given. 2-searches for all mitochondrial gene features and circularization. 3-stores the best result found. 4-uses the best assembly as backbone for a reference based assembly, using MIRA and MITObim, trying to extend the mitogenome and close gaps. 5-annotates the best assembly, identifying the start and end position of each and every feature. 6-creates a folder with all the results (PNG, GENBANK, FASTA, SEQUIN, CAF, MAF and a stats logfile).
