Search Results for "front-end" - Page 2
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Showing 143 open source projects for "front-end"
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xMariner
xMariner automates the analysis of MALDI spectra and report generation
xMariner automates the analysis of MALDI spectra and report generation -
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TagCalc
Calculates groups of aminoacids that adjust to a mass difference
Calculates groups of amino-acids that adjust to a mass difference (Python 3 version). -
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Xtraq
Xtraq extracts iTRAQ data from .ANZ Peaks results files
Xtraq extracts iTRAQ data from .ANZ Peaks results files. -
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An open source framework for LC-MS based proteomics and metabolomics. OpenMS offers data structures and algorithms for the processing of mass spectrometry data. The library is written in C++. Our source code and wiki lives on GitHub (https://github.com/OpenMS/OpenMS).
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RELEASE NOTE: Get raxmlGUI 2.0 at the NEW PROJECT LOCATION: https://antonellilab.github.io/raxmlGUI/ raxmlGUI is a graphical user interface to RAxML, one of the most popular and widely used software for phylogenetic inference using maximum likelihood. A userfriendly graphical front-end for phylogenetic analyses using RAxML (Stamatakis, 2006). Please cite: Silvestro, Michalak (2012) - raxmlGUI: a graphical front-end for RAxML. Organisms Diversity and Evolution 12, 335-337. DOI: 10.1007/s13127-011-0056-0
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Application to optimize DNA sequences coding protein to put in in the different organizm (f.e. human protein in E.Coli). It proposes the optimal cutting places to connect many shorter fragments into bigger one using ligaze.
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!!! PTEROS DEVELOPMENT MOVED TO GITHUB !!! New project page: https://github.com/yesint/pteros New documentation page: https://yesint.github.io/pteros/ Pteros is the C++ library for custom molecular modeling and simulations codes designed for researchers, not for C++ gurus. Provides facilities for PDB, XTC and TRR files IO, powerful selections, geometry transformations, RMSD fitting and alignment, etc.
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SnowyOwl
RNA-Seq based gene prediction pipeline for fungal genomes
SnowyOwl is a gene prediction pipeline that uses RNA-Seq data to train and provide hints for the generation of Hidden Markov Model (HMM)-based gene predictions, and to evaluate the resulting models. The pipeline has been validated and streamlined by comparing its predictions to manually curated gene models in three fungal genomes, and its results show substantial increases in sensitivity and selectivity over previous gene predictions. Sensitivity is gained by repeatedly running the HMM gene... -
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P3BSseq
Parallel processing pipeline for analysis of bisulfite sequencing data
...P3BSseq outperforms the known BSseq mappers regarding running time, computer hardware requirements. We optimized the P3BSseq parameters for both directional and non-directional libraries, and for both single-end and paired-end reads of Whole Genome and Reduced Representation BSseq. P3BSseq is a user-friendly streamlined solution for BSseq upstream analysis, requiring only basic computer and NGS knowledge. -
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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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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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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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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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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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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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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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Virus QSP Modeling
C++ and Python code for simulating RNA virus replication
Stochastic simulation model of poliovirus Sabin-to-Mahoney genetic state transition (C++ code). Models genotypes, virus populations, and quasispecies cloud. Simulates replication error and copy-choice recombination. Various parameters guiding the model are user-specified. Python code post-processes simulation output to produce report files. -
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MicrobeGPS
The Explorative Taxonomic Profiling Tool for Metagenomic Data
MicrobeGPS is a bioinformatics tool for the analysis of metagenomic sequencing data. The goal is to profile the composition of metagenomic communities as accurately as possible and present the results to the user in a convenient manner. One main focus is reliability: the tool calculates quality metrics for the estimated candidates and allows the user to identify false candidates easily. -
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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. The... -
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math lib for .NET. n-dim arrays, complex numbers, linear algebra, FFT, sorting, cells- and logical arrays as well as 3D plotting classes help developing algorithms on every platform supporting .NET. Sources from SVN, binaries: http://ilnumerics.net
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ADTEx
Aberration detection in tumour exome
Aberration Detection in Tumour Exome (ADTEx) is a tool for copy number variation (CNV) detection for whole-exome data from paired tumour/matched normal samples. -
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Magnolya
De novo CNV detection by co-assembly
Magnolya enables copy number variation (CNV) detections without using a reference genome. Magnolya directly compares two next-generation sequencing datasets. -
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mitoMaker
mitoMaker - a mitochondria assembly and annotation script
...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). -
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mullpy
Multilabel-learning library built on python
Mullpy is a machine-learning library that mainly aim to solve multi-label problems. It is classifier independent, has many ensemble capabilities (diversity methods like bagging, random subspaces, etc.) and automated results presentation (Excel, images as ROC or class-separated info, etc.). It is fully configurable. At the moment supports Neural Networks and classifiers defined in files. It is working on python3.3.
