Search Results for "cluster analysis"
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21 projects for "cluster analysis" with 1 filter applied:
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Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
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EFAK-AI
A AI-Driven, Distributed and high-performance monitoring system
EFAK (Eagle For Apache Kafka) is an open-source monitoring and management platform designed to provide comprehensive visibility and operational control over Apache Kafka clusters through a unified web interface. The project focuses on simplifying Kafka administration by offering real-time insights into cluster health, performance metrics, and consumer activity, allowing engineers to quickly diagnose issues and optimize system behavior. It integrates advanced features such as intelligent monitoring, alerting, and automated analysis, enabling proactive management rather than reactive troubleshooting. The platform supports multiple Kafka clusters simultaneously, making it suitable for enterprise environments with distributed data pipelines. ... -
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AudioMuse-AI is an open-source, Dockerized environment that brings automatic playlist generation to your self-hosted music library. Using tools such as Librosa and ONNX, it performs sonic analysis on your audio files locally, allowing you to curate playlists for any mood or occasion without relying on external APIs. Deploy it easily on your local machine with Docker Compose or Podman, or scale it in a Kubernetes cluster (supports AMD64 and ARM64). It integrates with the main music servers' APIs such as Jellyfin, Navidrome, LMS, Lyrion, and Emby. ...
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miARma-Seq
a A suite designed to study mRNAs, miRNAs and circRNAs
miARma-Seq, which stands for miRNA-Seq And RNA-Seq Multiprocess Analysis, is a suite designed to study mRNAs, miRNAs and circRNAs. It is able to perform differential expression analysis, miRNA-mRNA target prediction and functional analysis among others. Most importantly, it can be applied to any sequenced organism, and it can be initiated at any step of the workflow. As a stand-alone tool, is both easy to install and extremely flexible in terms of its use. It brings together... -
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Spark Python Notebooks
Apache Spark & Python (pySpark) tutorials for Big Data Analysis
Spark Python Notebooks is a curated collection of example Jupyter notebooks designed to help developers and data engineers learn Apache Spark using Python in an interactive environment. Rather than only providing static code files, this project uses notebooks to teach practical data processing workflows, exposing users to real Spark programming patterns like working with RDDs, DataFrames, and distributed computations. These notebooks often demonstrate how to transform, analyze, and visualize... -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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CIMS
Crosslinking induced mutation site analysis
This package includes the scripts to detect statistically reproducible crosslinking induced mutation sites (CIMS) and cross linking induced truncation sites (CITS) from HITS-CLIP data. References: Moore, M.*, Zhang, C.*, Gantman, E.C., Mele, A., Darnell, J.C., Darnell, R.B. 2014. Mapping Argonaute and conventional RNA-binding protein interactions with RNA at single-nucleotide resolution using HITS-CLIP and CIMS analysis. Nat Protocols, 9:263-293. Zhang,C.†, Darnell, R.B.† 2011.... -
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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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piv_clustering
structural clustering of atomic trajectories based on PIV
This program allows to perform a structural cluster analysis of atomic trajectories obtained, e.g., from molecular dynamics simulations. At variance with other approaches, it is possible to analyse also processes in solution, e.g., chemical reactions in liquid water, since the distance metric is based on a Permutation Invariant Vector (PIV) that is symmetric under exchange of identical atoms or molecules, including on the same footing both solute and solvent degrees of freedom. ... -
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XNDiff
X-ray and Neutron powder pattern simulation analysis
Keywords (XNDiff): -SAXS -SANS -absolute units -core (double)shell crystalline nanoparticles -with a parallelepidal shape -particle assemblies -powder and ensemble average -C/C++ -Unix -OpenMP -HPC Cluster Keywords (BatchMultiFit): -simultaneous fits for several SAXS and SANS curves with simulation data from XNDiff -SANS data can be smeared with dq values from experimental data sets or analytical functions -Mathematica console -local and global optimizers (simulated... -
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AWclust is easy to use non-parametric population structure analysis software written for R with a GUI interface. Just point and click and you will be on your way to discovering the important cluster information in your SNP data sets.
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Cbench is intended as a relatively straightforward toolbox of tests, benchmarks, applications, utilities, and framework to hold them together with the goal to facilitate scalable testing, benchmarking, and analysis of a Linux parallel compute cluster.
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IMPORTANT: The project moved over to github! You can find it at: https://github.com/exhuma/python-cluster
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QSAS plug-ins
Plug-ins for the space physics data analysis software QSAS.
The project is concerned with developing new plug-ins for the space plasma analysis software QSAS. The plug-ins are developed mainly for the Cluster II mission, Champ and Swarm. QSAS can be downloaded from: http://www.sp.ph.ic.ac.uk/csc-web/QSAS/ -
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QUASR
Cross-platform NGS processing and analysis pipeline in Python
QUASR is a lightweight pipeline written to process and analyse next-generation sequencing (NGS) data from Illumina, 454, and Ion Torrent platforms. Although originally written for viral data, it is generic enough to work on any NGS dataset. Functions include: duplicate removal demultiplexing primer-removal quality-assurance (QA) graphing quality control (QC) consensus-generation minority-variant determination minority-variant graphing The main current version is 6.X, which is... -
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Ocean Sync
Hadoop Management System
OceanSync is an Hadoop Management System that allows users to control a variety of aspects of Hadoop. This includes a Graphical User Interface that allows a user to perform HDFS maintenance tasks and submit new jobs to the cluster. The OceanSync product sits on top of any Hadoop Architecture. -
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Facelift is a visualization and analysis software for online social networking services. It displays a given community as a node-link diagram and provides several search / filtering functions as well as cluster analysis features.
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FORce based Cluster Editing (FORCE) is a Java software heuristically solving the graph cluster editing problem on weighted edges using BLAST E-values. It further provides a training mode for heuristic parameter estimation.
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A powerfull tool for analysing application servers logs (websphere, websphere portal, j2ee, custom) in a cluster (or not). It can analyse any log format thanks to a parser plugin approache. You can easily develop your own parser in java (for jboss, bea,.
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The CHIP Cluster Generator attempts to create spatio-temporal cluster data in an automated fashion to help evaluate epidemic detection software. The spatio-temporal data will then be used to determine robustness of spatial detection algorithms.
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clusterviz allows to cluster three-dimensional data. The clustering process is visualized using OpenGL. As clustering algorithms the family of k-means algorithms is implemented, including mixture models.
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For a given signal, pstool calculates a one-sided power spectrum, i.e. the portion of a signal's power falling within given frequency bins. This is done by employing a one-dimensional real-to-complex FFT routine on an MPI cluster.
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A non-parametric filter for image restoration using cluster analysis written in C and GTK+. The first source code may be found in http://smoked.homelinux.org/
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