Search Results for "parallel genetic algorithm"

Mendel’s Accountant is a biologically realistic, forward-time, parallel, numerical simulation program which models genetic change within a population, as affected by mutation and selection.

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. ...

...By default, the class "GeneticCode" generates alternative genetic codes, with the reqirement of block structure, and, optionally, with the assumption of stereochemical or biosynthetic models (to impose the assumption of the adaptive model, simply filter the codes using the error_cost() function). See Appendix in Makukov & shCherbak (2017) for the description of the algorithm. The code requires Qt 5.

GeneticAlgorithms is a simple and lightweight framework to implement an optimization heuristic following the Genetic Algorithms model. A genetic algorithm mimics the natural processes of evolution, selection and "survival of the fittest". This framework is intuitive and good integrated with Java 1.5 SDK and later.

...The model used in the application is based on two significant papers: 1.1997 Pablo Umana, James E.Bailey A Mathematical Model of N-linked Glycoform Biosynthesis. 2.2005 Frederick J.Krambeck, Michael J.Betenbaugh A Mathematical Model of N-linked Glycosylation. The application allow to simulate the network in dynamic form with various ODE solvers(Euler, Runge-Kutta etc). Genetic Algorithm is used to adjust the kinetic parameters of Michaelis-Menten equations in glycosylation reaction network. A dynamic plot is supplied to show the value of mole amout and mole fraction of various glycoform. Thanks to Alexey Balakin and Alessandro Presta. Alexey Balakin supply mathgl(https://sourceforge.net/projects/mathgl) that make the implementation of dynamic plot in this application easily. ...

...FamSeq accommodates de novo mutations and can perform variant calling at chromosome X. To accommodate variations in data complexity, FamSeq consists of three distinct implementations of the Mendelian genetic model: the Bayesian network algorithm, Elston-Stewart algorithm and Markov chain Monte Carlo algorithm. To make the software efficient and applicable to large families, we parallelized the Bayesian network algorithm that copes with pedigrees with inbreeding loops without losing calculation precision on an NVIDIA® graphics processing unit.

Ezys is a non-linear 3D medical image registration program. Ezys fully exploits the parallel computing power of inexpensive commercial graphics processing units (GPU), resulting in a very fast and accurate program capable of running on desktop PCs and even some laptops. On these systems, non-linear image registrations take less than a minute to complete. Ezys implements a diffeomorphic inverse consistent image registration algorithm with a demons-style regularization based on a non-parametric free form deformation model. ...

a FreeBasic-written Genetic Algorithm code is here deployed

Gene-gene interaction in genetic association studies is computationally intensive when a large number of SNPs are involved. Most of the latest Central Processing Units (CPUs) have multiple cores, whereas Graphics Processing Units (GPUs) also have hundreds of cores and have been recently used to implement faster scientific software. However, currently there are no genetic analysis software packages that allow users to fully utilize the computing power of these multi-core devices for genetic...

Darwin 2: Java Framework for Evolutionary Computation (genetic algorithm, GA). A true framework with out-of-the-box functionality and extensibility of all classes. Interface-based pattern with dependency-injection to configure components.

CloudBurst is a parallel read-mapping algorithm optimized for mapping next-generation sequence data to the human genome and other reference genomes, for use in a variety of biological analyses including SNP discovery, genotyping, and personal genomics.

BIL++ is a set of standalone C++ packages for data processing in Bioinformatics (Graph mining, Bayesian networks, Genetic algorithm, Discretization, Gene expression data analysis, Hypothesis testing).

This library is a lightweight implementation of genetic algorithm, contains the most popular types of chromosomes and the basic algorithms for selection, elitism, crossing and mutation.

Java API for implementing any kind of Genetic Algorithm and Genetic Programming applications quickly and easily. Contains a wide range of ready-to-use GA and GP algorithms and operators to be plugged-in or extended. Includes Tutorials and Examples.

DrPangloss is a python implementation of a three operator genetic algorithm, complete with a java swing GUI for running the GA and visualising performance, generation by generation

Molevolve is a Java library for running a Genetic Algorithm to model the 3-dimensional structures of peptide chains from amino-acid sequences. Client code can specify its own peptide chain model, fitness functions and GA operations. Requires JDK 1.5.

IslandEv distributes a Genetic Algorithm (like <a href="/projects/jaga">JaGa</a>) across a network (see <a href="/projects/distrit">DistrIT</a>) using an island based coevolutionary model in which neighbouring islands swap migrating individuals every

Galileo is a library for developing custom distributed genetic algorithms developed in Python. It provides a robust set of objects that can be used directly or as the basis of derived objects. Its modularity makes it easy to extend the functionality. The

MAGMA: Multiobjective Analyzer for Genetic Marker Acquisition A genetic algorithm for generating SNP tiling paths from a large SNP database based on the competing objectives of cost (number of SNPs) and coverage (haplotype blocks): Hubley R., Zitzler