Search Results for "genetic"
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Showing 401 open source projects for "genetic"
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SKUDONET ADC, operates at the application layer, efficiently distributing network load and application load across multiple servers. This not only enhances the performance of your application but also ensures that your web servers can handle more traffic seamlessly.
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Dialogflow can analyze multiple types of input from your customers, including text or audio inputs (like from a phone or voice recording). It can also respond to your customers in a couple of ways, either through text or with synthetic speech. Dialogflow CX and ES provide virtual agent services for chatbots and contact centers. If you have a contact center that employs human agents, you can use Agent Assist to help your human agents. Agent Assist provides real-time suggestions for human agents while they are in conversations with end-user customers.
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Alphafold
Open source code for AlphaFold
... a slightly simplified version of AlphaFold with this Colab notebook or community-supported versions. The total download size for the full databases is around 415 GB and the total size when unzipped is 2.2 TB. Please make sure you have a large enough hard drive space, bandwidth and time to download. We recommend using an SSD for better genetic search performance. -
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PyGAD
Source code of PyGAD, Python 3 library for building genetic algorithms
PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine learning algorithms. It supports Keras and PyTorch. PyGAD supports optimizing both single-objective and multi-objective problems. PyGAD supports different types of crossover, mutation, and parent selection. PyGAD allows different types of problems to be optimized using the genetic algorithm by customizing the fitness function. -
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GeneticSharp
GeneticSharp is a fast, extensible, multi-platform and multithreading
GeneticSharp is a fast, extensible, multi-platform and multithreading C# Genetic Algorithm library that simplifies the development of applications using Genetic Algorithms (GAs). Can be used in any kind of .NET 6, .NET Standard and .NET Framework apps, like ASP .NET MVC, ASP .NET Core, Blazor, Web Forms, UWP, Windows Forms, GTK#, Xamarin, MAUI and Unity3D games. GeneticSharp and extensions (TSP, AutoConfig, Bitmap equality, Equality equation, Equation solver, Function builder, etc). A Blazor... -
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pydna
Clone with Python! Data structures for double stranded DNA
Clone with Python! Data structures for double stranded DNA & simulation of homologous recombination, Gibson assembly, cut & paste cloning. Planning genetic constructs with many parts and assembly steps, such as recombinant metabolic pathways, are often difficult to properly document as is evident from the poor state of documentation in the scientific literature. The pydna python package provide a human-readable formal description of cloning and genetic assembly strategies in Python which allow... -
ConnectWise SIEM (formerly Perch) offers threat detection and response backed by an in-house Security Operations Center (SOC). Defend against business email compromise, account takeovers, and see beyond your network traffic. Our team of threat analysts does all the tedium for you, eliminating the noise and sending only identified and verified treats to action on. Built with multi-tenancy, ConnectWise SIEM helps you keep clients safe with the best threat intel on the market.
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Smile
Statistical machine intelligence and learning engine
Smile is a fast and comprehensive machine learning engine. With advanced data structures and algorithms, Smile delivers the state-of-art performance. Compared to this third-party benchmark, Smile outperforms R, Python, Spark, H2O, xgboost significantly. Smile is a couple of times faster than the closest competitor. The memory usage is also very efficient. If we can train advanced machine learning models on a PC, why buy a cluster? Write applications quickly in Java, Scala, or any JVM... -
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gplearn
Genetic Programming in Python, with a scikit-learn inspired API
gplearn implements Genetic Programming in Python, with a scikit-learn-inspired and compatible API. While Genetic Programming (GP) can be used to perform a very wide variety of tasks, gplearn is purposefully constrained to solving symbolic regression problems. This is motivated by the scikit-learn ethos, of having powerful estimators that are straightforward to implement. Symbolic regression is a machine learning technique that aims to identify an underlying mathematical expression that best... -
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Evolutionary.jl
Evolutionary & genetic algorithms for Julia
A Julia package for evolutionary & genetic algorithms. The package can be installed with the Julia package manager. -
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Java·Applied·Geodesy·3D
Least-Squares Adjustment Software for Geodetic Sciences
JAG3D is no longer developed at source-forge, and has moved to GitHub. Please visit https://github.com/applied-geodesy/jag3d or https://software.applied-geodesy.org to get the latest version. -
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Motofit co-refines Neutron and X-ray reflectometry data, using the Abeles matrix / Parratt recursion and least squares fitting (Genetic algorithm or Levenberg Marquardt). It works in the IGOR Pro environment (TM Wavemetrics).
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Built for growing businesses and well-established enterprises alike, Multiview is a highly scalable and robust ERP.
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Sudoku Maker is a generator for Sudoku number puzzles. It uses a genetic algorithm internally, so it can serve as an introduction to genetic algorithms. The generated Sudokus are usually very hard to solve -- good for getting rid of a Sudoku addiction.
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pgapack, the parallel genetic algorithm library is a powerfull genetic algorithm library by D. Levine, Mathematics and Computer Science Division Argonne National Laboratory. The library is written in C. PGAPy wraps this library for use with Python.
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sRNAWorkbench
The UEA sRNA Workbench
A suite of tools for analysing small RNA (sRNA) data from Next Generation Sequencing devices. Including expression profiling of known mirco RNA (miRNA), identification of novel miRNA in deep-sequencing data and identification of other interesting landmarks within high-throughput genetic data -
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This is the official repository for the CUSTOMHyS-Qt software. CUSTOMHyS-Qt is a GUI for the CUSTOMHyS framework, which is an interactive tool for customysing heuristic-based algorithms. The CUSTOMHyS-Qt is written in Python and uses the PyQt5 library for the GUI. Further references about the backend can be found in the CUSTOMHyS repository.
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Evolutionary Computation Framework
C++ framework for application of any type of evolutionary computation.
ECF is a framework intended for application of any type of evolutionary computation (GA/GP, DE, Clonalg, ES, PSO, ABC, GAn, local search...). It offers simplicity for the end-user (parameterless usage, tutorial) and customization for experienced EC practicioners. -
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GOBU
Gene Browsing Utility
Gene Ontology Browsing Utility (hereinafter, GOBU, pronounced as "go-boo") is a browsing and manipulating tool for Post-Pipeline genetic data, especially useful for data with GO annotations. With help of GOBU, we expect biologists and their cooperating technicians can pay less effort on common programming stuff. At the same time, GOBU provides an Extendable Architecture which guarantees the possibility of 1. Arbitrary Data Description, 2. Data Integration, and 3. Extendable User Interface. -
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irixjoker-sensing-utils
sensing in IRIX emulator lib
Uses machine learning to compute with genetic programming for emulators. -
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MolMarker
Java software to evaluate the results obtained by molecular markers
Journal article to cite: Jahnke, G.; Smidla, J.; Poczai, P. MolMarker: A Simple Tool for DNA Fingerprinting Studies and Polymorphic Information Content Calculation. Diversity 2022, 14, 497. https://doi.org/10.3390/d14060497 Leave a review, please! Your opinion matters! :-) MolMarker is user-friendly software to help evaluate the research results obtained by molecular markers. The software can handle genetic (e.g. SSR) and biochemical (e.g. isozyme) data, can construct similarity matrices... -
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DFE-alpha
inference of the distribution of fitness effects of new mutations and
... and genetic drift and the other set of sites assumed to be evolving neutrally. The DFE is assumed to be a gamma distribution with shape parameter beta (β), or a model in which all mutations have equal effects can be run. The mean mutational effect is estimated on a scale Nes, where Ne is a measure of the recent effective population size and s is the selection strength acting on a new mutation. -
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genome-wb3-asm
A Genetic Algorithm Library written in Amiga Workbench 3.x assembler
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Triangula
Generate high-quality triangulated and polygonal art from images
Generate high-quality triangulated and polygonal art from images. Triangula uses a modified genetic algorithm to triangulate or polygonate images. It works best with images smaller than 3000px and with fewer than 3000 points, typically producing an optimal result within a couple of minutes. For a full explanation of the algorithm, see this page in the wiki. You can try the algorithm out in your browser, but the desktop app will typically be 20-50x faster. If the app isn't running on Linux, go... -
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quire-lang
A programming language for genetic data
quire is a scripting language for performing calculations on information from genetic experiments. Although quire is capable of performing arbitrary calculations, it is really a domain-specific language driven by convenience in working in the problem domain over speed or memory usage. quire has a facility to add in binary modules to perform more intensive calculations. -
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GenoCline
GenoCline is a free Java software for genetic cline analysis
Identification of clines from allele frequency or genome-wide databases. Angular transformation. Sigmoid function. Parameterization of a cline: orientation, Pearson’s product-moment correlation coefficient, linear and sigmoid regression and coefficient of determination. Graphical representation of the cline. Confidence limits. Spatial autocorrelation. Moran's index. Isolation by distance. Exponential regression. Correlation Fst/Distance. Centroid method. Cline's expected vs. predicted... -
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BioNetExplorer
Framework for Exploration of Bio-signal Processing DNNs in Wearables
The BioNetExplorer framework systematically generates and explores multiple DNN architectures for bio-signal processing in wearable devices. Our framework varies key neural architecture parameters to search for an embedded DNN with low hardware overhead that can be deployed in wearable edge devices to analyze the bio-signal data and to extract the relevant information, such as arrhythmia and seizure. Furthermore, BioNetExplorer reduces the exploration time by deploying genetic algorithms... -
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bioweb
polyglot language framework to analyze genetic data
polyglot framework using Python/C++/JavaScript to fast develop applications to analyze biological sequences -
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fas2svg
Visualize genetic code structure from fasta file.
Generate svg file from fasta file.