Search Results for "genetic library"
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Showing 159 open source projects for "genetic library"
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Red Hat Enterprise Linux (RHEL) on Microsoft Azure provides a secure, reliable, and flexible foundation for your cloud infrastructure. Red Hat Enterprise Linux on Microsoft Azure is ideal for enterprises seeking to enhance their cloud environment with seamless integration, consistent performance, and comprehensive support.
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HubSpot is an AI-powered customer platform with all the software, integrations, and resources you need to connect your marketing, sales, and customer service. HubSpot's connected platform enables you to grow your business faster by focusing on what matters most: your customers.
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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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TPOT
A Python Automated Machine Learning tool that optimizes ML
Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming. -
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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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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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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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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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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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genome-wb3-asm
A Genetic Algorithm Library written in Amiga Workbench 3.x assembler
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Geophysical Library is a C++-library to handle geophysical data. At the moment the focus is on magnetotelluric and seismic data. It also includes a genetic algorithm for data inversion, signal processing and statistics routines.
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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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TurboGP
Genetic Programming library in Python
TurboGP is a Genetic Programming library written entirely in Python, primarily aimed at Machine Learning tasks. Currently being developed, and in beta version. Lino Rodriguez-Coayahuitl et al. 2020 -
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The source code has been migrated and is now hosted on Github: https://github.com/jenetics/jenetics Jenetics is an advanced Genetic Algorithm, Evolutionary Algorithm and Genetic Programming library, respectively, written in modern day Java. It is designed with a clear separation of the several algorithm concepts, e. g. Gene, Chromosome, Genotype, Phenotype, Population and fitness Function. Jenetics allows you to minimize or maximize the given fitness function without tweaking it. In contrast...
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TEESer
Tool for Engineering Emergent Selforganizing bEhavioR
Teeser is a java-based integration framework for engineering emergent self-organizing behavior in distributed systems. It contains tools for analysis, tuning, macroscopic probing and simulations of distributed systems. Library of tools can be extended and everybody is encouraged to provide and share its tools with the community. The main idea is to provide application designers ability to seamlessly use tools which are helpful to design self-organizing behavior. Designers can continue... -
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popt4jlib
Parallel Optimization Library for Java
popt4jlib is an open-source parallel optimization library for the Java programming language supporting both shared memory and distributed message passing models. Implements a number of meta-heuristic algorithms for Non-Linear Programming, including Genetic Algorithms, Differential Evolution, Evolutionary Algorithms, Simulated Annealing, Particle Swarm Optimization, Firefly Algorithm, Monte-Carlo Search, Local Search algorithms, Gradient-Descent-based algorithms, as well as some well-known... -
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This application allow user to predict dissolution profile of solid dispersion systems based on algorithms like symbolic regression, deep neural networks, random forests or generalized boosted models. Those techniques can be combined to create expert system. Application was created as a part of project K/DSC/004290 subsidy for young researchers from Polish Ministry of Higher Education.
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Swift AI
The Swift machine learning library
Swift AI is a high-performance deep learning library written entirely in Swift. We currently offer support for all Apple platforms, with Linux support coming soon. Swift AI includes a collection of common tools used for artificial intelligence and scientific applications. A flexible, fully-connected neural network with support for deep learning. Optimized specifically for Apple hardware, using advanced parallel processing techniques. We've created some example projects to demonstrate the usage... -
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diauxic growth model ensemble
An ensemble of models showing diauxic growth behavior
... be categorized according to regulatory, stoichiometric, and physiological constraints and differ from each other on only a single aspect. We distinguish four groups of models: (1) flux balance models that only define reaction kinetics for substrate uptake and by-product excretion, (2) kinetic models without and (3) kinetic models with regulation on the metabolic and/or genetic level, and (4) resource allocation models. -
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Jade
Evolutionary Algorithms for Time-Dependent Optimization & Learning
A Java library of Genetic Algorithms, Artificial Immune Systems and Pittsburgh Classifier Systems meant to operate in time-dependent environments. -
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Opt4J
Modular Java framework for meta-heuristic optimization
Opt4J is an open source Java-based framework for evolutionary computation. It contains a set of (multi-objective) optimization algorithms such as evolutionary algorithms (including SPEA2 and NSGA2), differential evolution, particle swarm optimization, and simulated annealing. The benchmarks that are included comprise ZDT, DTLZ, WFG, and the knapsack problem. The goal of Opt4J is to simplify the evolutionary optimization of user-defined problems as well as the implementation of arbitrary... -
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NEW OPTIMIZATION TECHNOLOGY & PLANNING EXPERIMENT. Technology is designed for multidimensional optimization practical problems with continuous object functions. Technology higher efficiency than traditional optimization methods.
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BAGEL: analysis of gene knockout screens
BAGEL: Bayesian Analysis of Gene EssentiaLity
BAGEL: software for Bayesian analysis of gene knockout screens using pooled library CRISPR or RNAi. BAGEL is a Bayesian classifier for pooled library genetic perturbation screens, using either CRISPR-Cas9 or shRNA libraries. It uses training sets of known essential and nonessential genes to estimate what the fold change distribution of an essential or nonessential gene should look like. Then, for each uncharacterized gene, it takes all observations of reagents targeting that gene (guide RNA... -
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AAARF, written in PERL and with numerous adjustable parameters, identifies sequence overlaps in small shotgun sequence datasets and walks them out to create long pseudomolecules representing the most abundant repeats in a genome.
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JGAP is a Genetic Algorithms and Genetic Programming package written in Java. It is designed to require minimum effort to use, but is also designed to be highly modular. JGAP features grid functionality and a lot of examples. Many unit tests included. Legal notice/Impressum: Klaus Meffert An der Struth 25 D-65510 Idstein sourceforge <at> klausmeffert.de
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MOEA Framework
A Free and Open Source Java Framework for Multiobjective Optimization
The MOEA Framework is a free and open source Java library for developing and experimenting with multiobjective evolutionary algorithms (MOEAs) and other general-purpose multiobjective optimization algorithms. The MOEA Framework supports genetic algorithms, differential evolution, particle swarm optimization, genetic programming, grammatical evolution, and more. A number of algorithms are provided out-of-the-box, including NSGA-II, NSGA-III, ε-MOEA, GDE3 and MOEA/D. In addition, the MOEA... -
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JAS is a java library for creating agent based simulations. It features a discrete-event time engine, APIs for network simulation design, powerful yet easy-to-use implementations of Genetic Algorithms and Neural Networks.