Search Results for "python feature selection"
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Showing 25 open source projects for "python feature selection"
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DataPrep
Python-based data preprocessing tool
DataPrep v0.2 is a Tkinter-based GUI application/tool designed to assist users in data preprocessing, multicollinearity removal, and feature selection for a wide range of applications in Cheminformatics, Bioinformatics, Data Analysis, Feature Selection, Molecular Modeling, Machine Learning, and Quantitative-structure-property relationship (QSPR) studies. It includes functionality to load, process, and save datasets with support for different preprocessing & multicollinearity removal strategies with customizable parameter setting options. -
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MutaNET
NGS Pipeline and Automated Mutation Analysis
MutaNET comes with a next generation sequencing (NGS) pipeline that calls mutations based on paired-end NGS reads, an automated mutation analysis tool and various file converters and mergers. The mutation analysis feature considers the coding region, protein domains, regulation and transcription factor binding site information, and can be used to analyse the potential impact of mutations on antibiotic resistance. -
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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:...
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ABC-SysBio implements likelihood free parameter inference and model selection in dynamical systems. It is designed to work with both stochastic and deterministic models written in Systems Biology Markup Language (SBML).
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DualTranscriptDiscovery
Transcript-discovery approach for gene feature delimitation by RNA-seq
This project contains Python scripts usable for a dual transcript-discovery approach that improves the delimitation of gene features from RNA-seq data in the chicken model. Documentation: http://bio.biologists.org/content/biolopen/suppl/2018/01/17/bio.028498.DC1/BIO028498supp.pdf Citation: Orgeur M., Martens M., Börno S. T., Timmermann B., Duprez D. and Stricker S. (2018). A dual transcript-discovery approach to improve the delimitation of gene features from RNA-seq data in the... -
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MethyMer
Design of specific primer combinations for bisulfite sequencing
MethyMer is a Python-based tool aimed at selecting specific primers for amplification of complete CpG islands. These regions are difficult in terms of selection appropriate primers because of their low-complexity, polyN-, CG-richness, etc. MethyMer have a flexible scoring system capable of selecting primers in problematic regions (e.g. SpG islands) and includes specificity test (based on bowtie alignment against bisulfite-treated genome). -
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nmr-nessy
NMR relaxation dispersion spectroscopy analysis software
NESSY is an open source software to analyse NMR relaxation dispersion data of either CPMG or R1p (R1rho) dispersion experiments. The graphical interface enables simple management of large experimental data sets and simple and automated analysis. NESSY automatically calculates effective transverse relaxation rate (R2eff) and performs model selection between different relaxation dispersion models. -
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diCal-IBD
diCal-IBD predicts identical by descent tracts using sequence data
diCal-IBD can be used for predicting identical by descent (IBD) tracts in sequence data. It provides means for calculating the accuracy of the prediction, if the true tracts are available, plotting of the predicted tracts, their TMRCA (time to the most recent common ancestor) and corresponding posterior probabilities, and identification of putative recent positive selection through investigation of average IBD sharing -
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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... -
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Java Machine Learning Library is a library of machine learning algorithms and related datasets. Machine learning techniques include: clustering, classification, feature selection, regression, data pre-processing, ensemble learning, voting, ...
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mitoMaker
mitoMaker - a mitochondria pipeline wrapper script
...If a feature was missing, or it hasn't circularized, try and assemble again with different assembler parameters (mainly k-mer). Rinse and repeat until the best build is found. -
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SeqSelector
Tools to select sequences for capture enrichment of next-gen libraries
The SeqSelector toolset is a suite of user-friendly, platform independent python scripts to facilitate selection of sequences for targeted enrichment of next-generation libraries through hybridization-based sequence capture. The scripts require no knowledge of programming, and can be applied to genome sequences of model or non-model species. We suggest a workflow in which genes of interest are first identified from previous studies and publicly available datasets of functional gene annotation. ... -
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ScreenSifter
ScreenSifter is a unique tool for RNAi Screen analysis and management
ScreenSifter can help you in managing all your RNAi screens related projects in organized fashion. ScreenSifter, to perform the sequential, user friendly, guided, and advanced statistical analyses of RNAi screening results. User can upload their raw signal intensities and will avail complete quality control of screen, hit selection, plotting of hit genes with gene ontology, comparing of replicates or comparing of channels. In addition, ScreenSifter has visualization tools to plot specific... -
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CDSbank
multi-sequence extraction, filtering & formatting
CDSbank is a database that stores both the protein-coding DNA sequence (CDS) and amino acid sequence for each protein annotated in Genbank. CDSbank also stores Genbank feature annotation, a flag to indicate incomplete 5’ and 3’ ends, full taxonomic data, and a heuristic to rank the scientific interest of a species. This rich information allows fully automated data set preparation with a level of sophistication that meets or exceeds manual processing. Defaults ensure ease of use for typical... -
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lonestar
A feature selection and classification algorithm based on L1 Norm SVM
A feature selection and classification algorithm. It is based on L1 Norm Support Vector Machine with t-test and Recursive Feature Elimination. -
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GEPETTO - Gene Prioritization in Java
GEPETTO (GEne Prioritization ExTended TOol)
...GEPETTO is written in Java/Python and supported by an advanced modular architecture, which means that it can easily be modified and extended by the user, in order to include alternative scoring methods and new data sources. We intend to extend the system from gene-level to variant-level prioritization, by exploiting the variant data in the MSV3D database. Contact: bmhoan@gmail.com or walter.vincent.fr@gmail.com -
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SpiKeDeteKt
An automatic spike detection program to be used with new KlustaKwik
This is an automatic spike detection program which takes account of probe geometry and produces a .mask file to be used with the new masked version of KlustaKwik. We recommend you use Python 2.6 or 2.7, e.g. a free academic version can be obtained from Entthought Python. The input files for SpiKeDeteKt are: .dat (raw data file) .probe (probe file, described below - user constructed) parameters.py (optional - otherwise it uses defaultparameters.py) SpiKeDeteKt outputs the following files: .fet.n (feature file) .mask.n (needed for using the new (masked) KlustaKwik) .clu.n (a trivial clue file where everything is put into a single cluster) .fmask.n (trial - float masks instead of binary, we are using this for testing masked KlustaKwik) .spk.n (spike file) .upsk.n (unfiltered spike waveform) .res.n (list of spike times) .xml (an xml file with all the parameters that can subsequently be used by neuroscope or klusters) .fil (highpass filtered data) .h5 ( -
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imDEV
Tools for multivariate data visualization, exploration and analysis.
You may also like some newer work: http://createdatasol.com/ Project imDEV is an application of RExcel, which seamlessly integrates Excel and R for tasks focused on multivariate data visualization, exploration, and analysis. Interactive modules for dimensional reduction (imPCA), prediction (imPLS), feature selection, analysis of correlation (imCorrelations) and generation of networked structures (imGraph) provide an integrated environment for systems level analysis of multivariate data. -
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Protein ALignment Optimiser (PALO) is a script for the selection and alignment of the best combination of transcripts among orthologous genes. PALO is mainly written in Python, although other programming languages are also implemented (R, Perl...).
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DimReduction project provide an open-source multiplatform (Java) graphical environment for bioinformatics problems that supports many feature selection algorithms, pattern recognition techniques, criterion functions and graphic visualization tools.
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Java GUI to analyze one (or more, in batch mode) datasets with several feature selection methods at the same time and also performing an "ensemble" analysis. It can be easily extended to include any feature selection algorithm.
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A small simulator for Mendelian genetics, genetic drift, natural selection and random mutations, built on matplotlib and wxpython. A graph will be generated that traces the distribution of genotypes at successive generations.
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Tools to build molecular-docking activity prediction models by PLS regression with iterative training and pose-selection. Descriptors include (i) docking score(s), (ii) pharmacophore features, (iii) multi-feature descriptors learned by decision trees.
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A python library for handling and analyzing biological sequence annotations as described in GFF files (General Feature Format). The library is intended to be a complete framework for this file format.
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