Search Results for "code analysis"
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Showing 14 open source projects for "code analysis"
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BioXTAS RAW
Processing and analysis of Small Angle X-ray Scattering (SAXS) data.
BioXTAS RAW is a program for analysis of Small-Angle X-ray Scattering (SAXS) data. The software enables: creation of 1D scattering profiles from 2D detector images, standard data operations such as averaging and subtraction, analysis of radius of gyration (Rg) and molecular weight, and advanced analysis using GNOM and DAMMIF as well as electron density reconstructions using DENSS. -
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MAGeCK
Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout
Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout (MAGeCK) is a computational tool to identify important genes from the recent genome-scale CRISPR-Cas9 knockout screens technology. For instructions and documentations, please refer to the wiki page. MAGeCK is developed by Wei Li and Han Xu from Dr. Xiaole Shirley Liu's lab at Dana-Farber Cancer Institute/Harvard School of Public Health, and is maintained by Wei Li lab at Children's National Medical Center. We thank the support... -
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LP CSIC/UAB Apps and Code
Software and Code from Laboratori de Proteòmica CSIC/UAB
Software, Code and Documents from Laboratori de Proteòmica CSIC/UAB ( LP-CSIC/UAB: http://proteomica.uab.cat ) -
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MToolBox
A bioinformatics pipeline to analyze mtDNA from NGS data
...MToolBox includes an updated computational strategy to assemble mitochondrial genomes from Whole Exome and/or Genome Sequencing (PMID: 22669646) and an improved fragment-classify tool (PMID:22139932) for haplogroup assignment, functional and prioritization analysis of mitochondrial variants. MToolBox provides pathogenicity scores, profiles of genome variability and disease-associations for mitochondrial variants. MToolBox provides also a Variant Call Format file (version 4.0) featuring, for the first time, allele-specific heteroplasmy. Please, check out the most recent updates of the source code with the Github repository of MToolBox: https://github.com/mitoNGS/MToolBox or visit the Web version of MToolBox @ MSeqDR: https://mseqdr.org/mtoolbox.php -
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Python4Proteomics Course
Python course for Proteomics analysis
Python course (in Spanish) for Proteomics analysis using basically Jupyter NoteBooks. For more information, you can have a look at the readme.md file in the source code tree: https://sourceforge.net/p/lp-csic-uab/p4p/code/ci/default/tree/readme.md -
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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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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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BioC
We describe a simple XML format to share text documents and annotation
A minimalist approach to share text documents and data annotations. Allows a large number of different annotations to be represented. Project files contain: - simple code to hold/read/write data and perform sample processing. - BioC-formatted corpora - BioC tools that work with BioC corpora BioC goals - simplicity - interoperability - broad use - reuse There should be little investment required to learn to use a format or a software module to process that format. We are... -
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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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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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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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SPADE
A toolkit for developing and deploying protein structure algorithms.
The Structural Proteomics Application Development Environment is a Python tool kit for developing and deploying bioinformatics applications. Handles graphics, analysis, and modeling of protein sequence and structure. Source and Win installers available. SPADE source code can be cloned from http://www.github.com/deaconjs/SPADE. -
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Atlas2Cloud
Atlas2 Genome Analysis Pipeline on Amazon Web Services
This is the backend source code of the Atlas2-Cloud pipeline on Amazon which starts and terminates worker nodes, runs analysis and monitors worker instances. It is PRIMARILY meant to be used through Amazon Web Services (AWS) management console by looking for the public Atlas2-Cloud machine image. Alternatively, the code can also be used for running the pipeline from your computer. -
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""" E-Cell's source code repository has moved to GitHub! https://github.com/ecell The development of E-Cell now continues on GitHub. The Subversion repository was abandoned. """ E-Cell System is an object-oriented software suite for modeling, simulation, and analysis of large scale complex systems such as biological cells. It allows many components driven by multiple algorithms with different timescales to coexist in a model.
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