Open Source Python Bio-Informatics Software - Page 9
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Python Bio-Informatics Software
View 66 business solutionsBrowse free open source Python Bio-Informatics Software and projects below. Use the toggles on the left to filter open source Python Bio-Informatics Software by OS, license, language, programming language, and project status.
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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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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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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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Code repository for the Laboratory for Genome Bioinformatics at Texas A&M. The LGB project was initiated primarily to support biologists at Texas A&M needing help with bioinformatics in order to use new genomic technologies.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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LaiaMotifs
Search for MHC-like motifs in peptide collections
Search for MHC-like motifs in peptide collections (Python 3 version). 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/laiamotifs3/code/ci/default/tree/README.md -
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This is a c-library that provides tools for advanced analysis of electrophysiological data. It features denoising, unsupervised classification, time-frequency analysis, phase-space analysis, neural networks, time-warping and more.
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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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LipidWrapper
Create lipid-bilayer models of arbitrary geometry.
LATEST VERSION NOW LOCATED AT http://git.durrantlab.com/jdurrant/lipidwrapper As ever larger and more complex biological systems are modeled in silico, approximating physiological lipid bilayers with simple planar models becomes increasingly unrealistic. When building large-scale models of whole subcellular environments, models of lipid membranes with carefully considered, biologically relevant curvature are essential. LipidWrapper, written by Jacob Durrant in the lab of Rommie E. Amaro, is capable of creating curved membrane models with geometries derived from various possible sources, both experimental and theoretical. We are hopeful that this utility will be a useful tool for the computational-biology community. -
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LipidXplorer is an uniqe software to identify lipids from high to low resolution mass spectra.
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LoFreq
Fast and sensitive variant-calling from sequencing data
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LymPHOS2
LymPHOS2 Web-App
LymPHOS2 is a web-based Application at www.LymPHOS.org containing peptidic and protein sequences and spectrometric information on the PhosphoProteome of human T-Lymphocytes. - Nguyen, TD., Vidal-Cortes, O., Gallardo, Ó., Abian, J., Carrascal, M., LymPHOS 2.0: an update of a phosphosite database of primary human T cells. Database 2015, 2015. DOI: 10.1093/database/bav115 - Carrascal, M., Ovelleiro, D., Casas, V., Gay, M., Abian, J., Phosphorylation analysis of primary human T lymphocytes using sequential IMAC and titanium oxide enrichment. J. Proteome Res. 2008, 7, 5167-5176. DOI: 10.1021/pr800500r - Ovelleiro, D., Carrascal, M., Casas, V., Abian, J., LymPHOS: design of a phosphosite database of primary human T cells. Proteomics 2009, 9, 3741–3751. DOI: 10.1002/pmic.200800701 - Gallardo, Ó., Ovelleiro, D., Gay, M., Carrascal, M., Abian, J., A collection of open source applications for mass spectrometry data mining. Proteomics 2014, 20, 2275-2279. DOI: 10.1002/pmic.20140012 -
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MAXIMUS is a genome assembly pipeline which takes the best out of multiple reference assemblies and de novo assembly. The benefits of this approach include better assembled repetitive regions, less gaps and higher accuracy for the resultant assembly.
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This program has been written having in mind to create an useful tool to evaluate the Motor Evoked Potentials (MEPs) generated by Transcranial Magnetic Stimulation (TMS) and recorded with the program "Signal" (version 2.xx).
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MGFVisor
Visor for mass spectrometry MGF files
Visor for mass spectrometry MGF files (Python 3 version). 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/mgfvisor3/code/ci/default/tree/README.md -
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MIVF - Medical Imaging and Visualization Factory, is a framework for medical applications. It supplies a platform, in which image processing and 3D visualization algorithms can be employed as reusable components (functional modules or plugins).
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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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MaryGold
Variation analysis of metagenomic samples
The package enables detection of sequence variation between metagenomic samples. -
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Maximal Clique Motif Reduction (MCMR) is a software program for running and then combining the output of multiple motif finder programs, such as MEME, AlignACE and Weeder, into a set of consensus predictions with associated confidence rankings.
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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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MePrId is a Python program which can be used to classify a protein, depending whether it is a membrane or a globular protein. Download link: http://meprid.svn.sourceforge.net/viewvc/meprid.tar.gz?view=tar
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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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Metaboflux is a generic approach for predicting flux distribution in metabolic networks under multiple and various constraints deducted from the experiments, to increase the biological relevance of the model.
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MiModD
Mutation Identification in Model Organism Genomes using Desktop PCs
MiModD is a software package for genomic variant identification from next-generation sequencing (NGS) data with optimized usage of system resources and a user-friendly interface. For most model organism genomes it lets the user carry out a complete analysis from unaligned genomic NGS read data to an annotated list of variants on a regular Desktop PC within a few hours. Its user-interface is beginner-friendly and designed to encourage geneticists to analyze NGS data themselves without the help of a trained bioinformatician. -
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Microarray Integrator (MAI)
Microarray Integrator for heterogeneous human/mouse Affymetrix arrays
The Microarray Integrator is freely available programs to integrate heterogeneous Affymetrix microarrays for human and mouse. The cell-type-specific genes or condition-specific genes can be screened in the integrated microarrays by MAI result.
