DNA Sequencing plays a vital role in the modern research. It allows large number of multiple areas to progress, as well genetics, meta-genetics, and phylogenetics. involves extracting reading strands DNA. This research paper aims at comparing using “Machine Learning algorithms (Decision Trees, Random Forest, Naive Bayes) Deep (Transform CNN)”. The aim our proposed system is implement better pre...

task in that good explanations of the positive examples is of more importance tions of genetic algorithms to various research questions in human genetics. 2 Genetic Algorithms, Constraints, and the Knapsack Problem. 10 5.2 Inductive Learning From Examples. 6.3 Genetic Algorithms and Concept Learning. In this paper, we explore Genetic Algorithms (GA) as an alternative approach to derive these mo...

Two metaheuristic algorithms namely Artificial Immune Systems (AIS) and Genetic Algorithms are classified as computational systems inspired by theoretical immunology and genetics mechanisms. In this work we examine the comparative performances of two algorithms. A special selection algorithm, Clonal Selection Algorithm (CLONALG), which is a subset of Artificial Immune Systems, and Genetic Algor...

Genetic algorithms [1, 2] are stochastic optimization methods inspired by natural evolution and genetics. Over the last few decades, genetic algorithms have been successfully applied to many problems of business, engineering, and science. Because of their operational simplicity and wide applicability, genetic algorithms are now playing an increasingly important role in computational optimizatio...

a new structure learning approach for bayesian networks (bns) based on asexual reproduction optimization (aro) is proposed in this letter. aro can be essentially considered as an evolutionary based algorithm that mathematically models the budding mechanism of asexual reproduction. in aro, a parent produces a bud through a reproduction operator; thereafter the parent and its bud compete to survi...

Introduction: Physicians have to visit, diagnose and refer patients with genetic disorders, so they need to be familiar with the basics and indications of genetic tests. In other words, they should have effective theoretical and practical knowledge about medical genetics before they do their job. Medical genetics courses at Medical Universities of Iran are generally presented as a theoretical s...

This paper introduces graphical models as a natural environment in which to formulate and solve problems in genetics and related areas. Particular emphasis is given to the relationships among various local computation algorithms which have been developed within the hitherto mostly separate areas of graphical models and genetics. The potential of graphical models is explored and illustrated thro...

This paper presents an Asynchronous Team Algorithms (ATeam) implementation, in a parallel heterogeneous asynchronous environment, to optimize the design of reliable communication networks given the set of nodes an possible links. The proposed Team combines parallel genetics algorithms (GA), with different reliability calculation approaches in a network of personal computers, proving good experi...

We present and discuss particle based algorithms to numerically study the dynamics of population subjected to an advecting flow condition. We discuss few possible variants of the algorithms and compare them in a model compressible flow. A comparison against appropriate versions of the continuum stochastic Fisher equation (sFKPP) is also presented and discussed. The algorithms can be used to stu...

cancer-genetics epidemiology and genetics investigation in colorectal carcinomas: directions towards prevention