Search Results for "clustering"
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Showing 51 open source projects for "clustering"
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GromacsProSuite
Graphical User Interface for Gromacs
...Built-in monitoring tracks CPU, RAM, and disk usage to ensure stable performance during parallel processing. Beyond simulation execution, it includes advanced trajectory processing and analysis tools such as RMSD, RMSF, SASA, clustering, PCA, hydrogen-bond analysis, Ramachandran plots, and FEL mapping. With integrated visualization and plotting utilities, it offers a unified platform for researchers, educators, and students to perform complete MD workflows efficiently and reproducibly. Our Goal is to bring MD simulations to every biologist's toolkit. -
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NGSEP
NGSEP (Next Generation Sequencing Experience Platform)
...The current version provides functionalities for both de-novo and reference guided analysis of sequencing data, including genome assembly, read mapping, variants detection and genotyping and de-novo analysis of data generated from reduced representation protocols. NGSEP also provides modules for analysis of genomic variation databases (VCF files), including functional annotation, filtering, format conversion, comparison, clustering, imputation, introgression analysis and different kinds of statistics. Since version 4, we provide functionalities for management of genomes and transcriptomes, including genome alignment and annotation of transposable elements. A complete list of functionalities is available in our wiki (https://sourceforge.net/p/ngsep/wiki/Home/). ... -
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RAFTS³G
Rapid Alignment Free Tool for Sequences Similarity Search to Groups
| RAFTS3G - Rapid Alignment Free Tool for Sequences Similarity Search to Groups| % Clustering algoritm to create homology clusters based on RAFTS3 (VIALLE, R. A.) % More informations about RAFTS3 in: https://sourceforge.net/projects/rafts3/ % Professional and Technical Education Sector from the Federal University of Paraná - Bioinformatic Lab. % Federal of Paraná University - UFPR % Dr. Alcides Vieira Arco-verde street, 1225 % CEP: 81520-260 Jardim das Américas % Curitiba – PR % Brazil % % Developers and colaborators: % Roberto T. ... -
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dataMAPPs
R based pipeline for MHC-associated peptide proteomics (MAPPs) data
dataMAPPs allows routine and efficient processing of data from immunogenicity studies applying the MAPPs peptidomics technology to detect potential MHCI- or MHC-II epitopes as presented by dendritic cells (DC). It features quality control of the raw data, across-sample/across-donor normalization and visualization of results in a heatmap style (heatMAPPs). dataMAPPs' core is a generic R library that can be tailored to specific projects via dedicated control scripts which also allow... -
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QuantifyPoly(A)
Quantification of poly(A) sites from 3' end sequencing data
QuantifyPoly(A) - a tool for quantification of poly(A) sites from 3' end sequencing data. [1] QuantifyPoly(A) user manual Please visit the Wiki page of this website. [2] QuantifyPoly(A) Q&A For Q&A, please visit the Blog page of this website. [3] QuantifyPoly(A) bug report You can report a bug as a Ticket request, or start a topic session in the Discussion webpage of this website. -
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NOVA
Analysis and visualization of complexome profiling data.
NOVA is a program designed to analysis complexome profiling data (Heide et al., 2012). A graphical user interface (GUI) provides various visualization tools, such as heat maps and 2D plots. Several hierarchical clustering algorithms (e.g., single linkage, average linkage, Wards linkage), different distance measures (e.g., Euclidean distance, Manhattan distance, Pearson distance), and various normalization techniques are implemented. Many additional functions like zooming, searching for proteins, image export, and automatic file format recognition support intuitive handling for biologists. ... -
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MarDRe
MapReduce-based tool to remove duplicate DNA reads
MarDRe is a de novo MapReduce-based parallel tool to remove duplicate and near-duplicate DNA reads through the clustering of single-end and paired-end sequences from FASTQ/FASTA datasets. This tool allows bioinformatics to avoid the analysis of not necessary reads, reducing the time of subsequent procedures with the dataset. MarDRe is the Big Data counterpart of ParDRe (link above), which employs HPC technologies (i.e., hybrid MPI/multithreading) to reduce runtime on multicore systems. ... -
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PanOCT
Pan-genome Ortholog Clustering Tool
PanOCT, Pan-genome Ortholog Clustering Tool, is a program written in PERL for pan-genomic analysis of closely related prokaryotic species or strains. Unlike traditional graph-based ortholog detection programs, it uses micro synteny or conserved gene neighborhood (CGN) in addition to homology to accurately place proteins into orthologous clusters. -
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irayMol
Molecular visualization
Analyses and Interactive visualizations of the structures, functions and actions of biomolecules including molecular surface computation, and protein-ligand interface and protein-ligand docking where the ligand could a small compound, a nucleic acid, membrane and other proteins, written in C++/Qt/openGL/GLSL with more than 125,000 lines of codes. In addition to Qt, the only external library needed is GSL everything else is coded from the scratch. -
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QSdpR
Viral Quasispecies Reconstruction software based on QSdpR algorithm
This is a viral quasispecies reconstruction software for quasispecies assembly problem on mRNA viruses, which is based on a correlation clustering approach and uses semidefinite optimization framework. The software accepts a reference genome, a NGS read set aligned to this reference and set of SNP locations in the form of a vcf file and outputs an optimal set of reconstructed species genomes which describes the underlying viral population. -
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ImagingAnalysis
Direct tissue-level image quantification package for Mathematica
ImagingAnalysis is a Mathematica package that performs grid-based analysis of time-lapse imaging data saved in a sequence of TIFF files. This package requires Mathematica 7.0. Revised on 14 May 2017: Bugs are fixed and incompatibility issues are resolved. The current version runs on Mathematica 11. -
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KAPPA (Key Aminoacid Pattern-based Protein Analyzer) is a sequence search program dedicated to the discovery and clustering of proteins defined by a key aminoacid pattern.
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...The former Matlab toolbox Gait-CAD was designed for the visualization and analysis of time series and features with a special focus to data mining problems including classification, regression, and clustering.
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The Maltcms - Modular Application Toolkit for Chromatography Mass-Spectrometry is a JAVA API for preprocessing, alignment, analysis and visualization of data stored in open file formats used in Proteomics and Metabolomics research.
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MCCCS
Multi Channel Classification and Clustering
Here we present an image-based Multi Channel Classification and Clustering System (MCCCS). It is an generalized, script-based classification system for processing various kinds of image data. Due to the modular design, individual processing-components can be easily adapted, extended or exchanged by own extensions. See project website for installation instructions. -
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BamBam
Tools for genomic analysis
BamBam includes numerous tools for analyzing DNA next-generation sequencing data. Tools are provided for calling SNPs and indels, identifying large scale deletions, tabulating counts of mapped reads, methylation analysis, and more. Depends on SAMtools (http://samtools.sourceforge.net/) and BAMtools (https://github.com/pezmaster31/bamtools). Also uses BioPerl, which is included in the download tarball. -
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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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rainbow
short reads clustering and local assembly
Efficient tool for clustering and assembling short reads, especially for RAD. -
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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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BiMS
BiMS (biclustering for mass spectrometry data) is a Java application d
BiMS (biclustering for mass spectrometry data) is a Java application designed to allow the application of biclustering algorithms to mass spectrometry datasets. Users can load their MS datasets and apply different clustering and biclustering algorithms (current version includes Bimax and BiBit). In adition, users can load raw datasets (in mzML or mzXML formats) and preprocess them using MALDIquant package and MassSpecWavelet. -
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Luscinia is a program for archiving and analyzing field sound recordings (especially of animals). It incorporates an interface to a database, spectrogram measurement algorithms, sound comparison algorithms, and statistical analysis.
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Deem
Analyze time-course data with significance tests, clustering, modeling
Use statistical methods to analyze time-course data (gene expression microarray and RNA-seq data in particular, but not limited to). Apply significance tests to filter out only significant genes or time series. Cluster time series into similar groups. Generate network models, including linear or non-linear models. Variable selection and optimization routines included. Written in Scala and R. The application is a cross-platform desktop app with a simple GUI and is fully functional... -
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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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Hierachical_DNAcoder
An Hierachical Approach to Multi-Reference Genome compression
...To increase the exact aligning rate, we also realign the approximately mapped and unmapped reads by changing the reference sequence or shortening the read length. Meanwhile, we further the study using “lossy” quality values through k-means clustering scheme and find its minute effect on downstream applications. The proposed method has achieved compression ratios from 0.5 to 0.65, which corresponds to space savings of 35%-50%, on experimental datasets.
