Soft molecular computing
نویسندگان
چکیده
Molecular computing (MC) utilizes the complex interaction of biomolecules and molecular biology protocols to e ect computation. Lab experiments in MC are unreliable, ine cient, unscalable, and expensive compared to conventional computing standards. A critical issue in MC is therefore to test protocols to minimize errors and mishaps that can thwart experiments when actually run in vitro. The purpose of this paper is to describe Edna , an integrated software platform developed to address this problem. The platform will allow MC practicioners to use digital computers to gain insight on the performance of a protocol before it actually unfolds in the tube. Currently, Ednaprovides tools to nd good encodings for a given set of hybridization conditions, by design or evolution, tools to visualize the quality of these encodings, tools to estimate the complexity of given protocols based on bounded complexity, and a virtual test tube simulator based on local interactions between electronic DNA molecules. The virtual tube has allowed us to reproduce Adleman's experiment in silico. Edna includes graphical interfaces, click-and-drag facilities, is object-oriented, extensible, and so that it can easily evolve as the eld progresses.
منابع مشابه
Prediction of the pharmaceutical solubility in water and organic solvents via different soft computing models
Solubility data of solid in aqueous and different organic solvents are very important physicochemical properties considered in the design of the industrial processes and the theoretical studies. In this study, experimental solubility data of 666 pharmaceutical compounds in water and 712 pharmaceutical compounds in organic solvents were collected from different sources. Three different artificia...
متن کاملUtilization of Soft Computing for Evaluating the Performance of Stone Sawing Machines, Iranian Quarries
The escalating construction industry has led to a drastic increase in the dimension stone demand in the construction, mining and industry sectors. Assessment and investigation of mining projects and stone processing plants such as sawing machines is necessary to manage and respond to the sawing performance; hence, the soft computing techniques were considered as a challenging task due to stocha...
متن کاملInvestigating electrochemical drilling (ECD) using statistical and soft computing techniques
In the present study, five modeling approaches of RA, MLP, MNN, GFF, and CANFIS were applied so as to estimate the radial overcut values in electrochemical drilling process. For these models, four input variables, namely electrolyte concentration, voltage, initial machining gap, and tool feed rate, were selected. The developed models were evaluated in terms of their prediction capability with m...
متن کاملPredicting the Coefficients of Antoine Equation Using the Artificial Neural Network (TECHNICAL NOTE)
Neural network is one of the new soft computing methods commonly used for prediction of the thermodynamic properties of pure fluids and mixtures. In this study, we have used this soft computing method to predict the coefficients of the Antoine vapor pressure equation. Three transfer functions of tan-sigmoid (tansig), log-sigmoid (logsig), and linear were used to evaluate the performance of diff...
متن کاملA COMPARATIVE STUDY OF TRADITIONAL AND INTELLIGENCE SOFT COMPUTING METHODS FOR PREDICTING COMPRESSIVE STRENGTH OF SELF – COMPACTING CONCRETES
This study investigates the prediction model of compressive strength of self–compacting concrete (SCC) by utilizing soft computing techniques. The techniques consist of adaptive neuro–based fuzzy inference system (ANFIS), artificial neural network (ANN) and the hybrid of particle swarm optimization with passive congregation (PSOPC) and ANFIS called PSOPC–ANFIS. Their perf...
متن کاملApplication of Soft Computing Methods for the Estimation of Roadheader Performance from Schmidt Hammer Rebound Values
Estimation of roadheader performance is one of the main topics in determining the economics of underground excavation projects. The poor performance estimation of roadheader scan leads to costly contractual claims. In this paper, the application of soft computing methods for data analysis called adaptive neuro-fuzzy inference system- subtractive clustering method (ANFIS-SCM) and artificial neu...
متن کامل