Search Results for "python library"
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Showing 49 open source projects for "python library"
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CBFLIB is a library of ANSI-C functions providing a simple mechanism for accessing Crystallographic Binary Files (CBF files) and Image-supporting CIF (imgCIF) files. The CBFLIB API is loosely based on the CIFPARSE API for mmCIF files.
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The Sashimi project hosts the Trans-Proteomic Pipeline (TPP), a mature suite of tools for mass-spec (MS, MS/MS) based proteomics: statistical validation, quantitation, visualization, and converters from raw MS data to the open mzML/mzXML formats.
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STRIKER-GUI
Refine the spectral library to enhance its completeness and coverage.
STRIKER is a tool for correcting spectra with missing or incorrect adduct annotations. It also enables efficient construction of an HMDB-based spectral library and extraction of sublibraries from large spectral libraries. -
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Conscious Artificial Intelligence
It's possible for machines to become self-aware.
This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses. This project has 2 subprojects: Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api A video from the first prototype has been made: http://www.youtube.com/watch?v=qH-IQgYy9zg Above video shows a popperian agent collecting mining ore from 3... -
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SASA Tool
SWATH-Auto System Analyzer Tool, SASA Tool
SWATH-Auto System Analyzer Tool, SASA Tool, is a novel SWATH platform for non-targeted metabolomics data analysis with an accurate mass spectral library for metabolite identification using SWATH acquisition mode. -
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bioweb
polyglot language framework to analyze genetic data
polyglot framework using Python/C++/JavaScript to fast develop applications to analyze biological sequences -
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CBMPy
PySCeS Constraint Based Modelling
PySCeS CBMPy is a new platform for constraint based modelling and analysis. It has been designed using principles developed in the PySCeS simulation software project: usability, flexibility and accessibility. CBMPy supports the latest standards for encoding CBM models encoding, SBML L3 FBC, COBRA as well as MIRIAM compliant RDF and custom annotations. Its architecture is both extensible and flexible using data structures that are intuitive to the biologist while transparently... -
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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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e-Species
A taxonomically intelligent biodiversity search engine
This is a pure Python CGI-based implementation of a taxonomically intelligent species search engine. It searches biological databases for a taxonomic name. The search is done "on the fly" using web services (SOAP/XML) or URL API's. -
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Open-source Python software library and GUI desktop environment for direct bioinformatic analysis of mass-spectrometry data through powerful scripting tools and interfaces to many machine data formats, database search engines, and peptide data formats. For a copy of the source code, check out our Github repositories: mzDesktop: https://github.com/MaxAlex/mzDesktop multiplierz: https://github.com/MaxAlex/multiplierz
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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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Collaborative Computing Project for NMR
Collaborative Computing Project for NMR (CCPN)
The Collaborative Computational Project for NMR (CCPN) provides tools and knowledge to maximise the impact of the biological NMR studies. The CCPN software facilitates data analysis and software integration. The project actively promotes the exchange of knowledge and provides training and best practices for the NMR community. CCPN also has a leading role in the development of a NMR data-sharing standard and coordination of NMR instrumentation proposals for RCUK and BIS. The 28 partners of... -
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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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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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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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BayesRate
Bayesian estimation of diversification rates
BayesRate is a program to estimate speciation and extinction rates from dated phylogenies in a Bayesian framework. The methods are described in: Silvestro, D., Schnitzler, J. and Zizka, G. (2011) A Bayesian framework to estimate diversification rates and their variation through time and space. BMC Evolutionary Biology, 11, 311 Silvestro D., Zizka G. & Schulte K. (2014) Disentangling the effects of key innovations on the diversification of Bromelioideae (Bromeliaceae). Evolution, 68, 163-175. -
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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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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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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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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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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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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 -
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PyMod
(OBSOLETE) PyMOL Plugin for Homology Modeling of Protein Structures
This is the UNOFFICIAL mirror to PyMod. Since the release of PyMod2.0, this repository will no longer be maintained. -
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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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caplib
Correct, translate and analyze combinatorial library sequencing data
Originally developped to handle PacBio CCS data for an AAV capsid library. This program will extract, correct, translate and analyze the sequencng data, starting from the CCS fastq file.
