A comprehensive survey on genetic algorithms for DNA motif prediction

2018 ◽  
Vol 466 ◽  
pp. 25-43 ◽  
Author(s):  
Nung Kion Lee ◽  
Xi Li ◽  
Dianhui Wang
Keyword(s):  
Genetic Algorithms ◽  
Motif Prediction ◽  
Dna Motif ◽  
Comprehensive Survey

scholarly journals Evaluation of Convolutionary Neural Networks Modeling of DNA Sequences using Ordinal versus one-hot Encoding Method

2017 ◽  
Author(s):  
Allen Chieng Hoon Choong ◽  
Nung Kion Lee
Keyword(s):  
Dna Sequences ◽  
Motif Discovery ◽  
Matrix Representation ◽  
Training Time ◽  
Motif Prediction ◽  
Dna Motif ◽  
Sequence Encoding ◽  
Dna Motif Discovery ◽  
Encoding Method ◽  
The One

AbstractConvolutionary neural network (CNN) is a popular choice for supervised DNA motif prediction due to its excellent performances. To employ CNN, the input DNA sequences are required to be encoded as numerical values and represented as either vectors or multi-dimensional matrices. This paper evaluates a simple and more compact ordinal encoding method versus the popular one-hot encoding for DNA sequences. We compare the performances of both encoding methods using three sets of datasets enriched with DNA motifs. We found that the ordinal encoding performs comparable to the one-hot method but with significant reduction in training time. In addition, the one-hot encoding performances are rather consistent across various datasets but would require suitable CNN configuration to perform well. The ordinal encoding with matrix representation performs best in some of the evaluated datasets. This study implies that the performances of CNN for DNA motif discovery depends on the suitable design of the sequence encoding and representation. The good performances of the ordinal encoding method demonstrates that there are still rooms for improvement for the one-hot encoding method.

Genetic Algorithms—a Tool for OR?

1996 ◽  
Vol 47 (4) ◽  
pp. 550-561 ◽  
Author(s):  
Kathryn A Dowsland
Keyword(s):  
Genetic Algorithms

Enhanced Artificial Intelligent Method for Representing the Photonic Crystal Fiber Profile Index

2018 ◽  
Vol 1 (1) ◽  
pp. 2-19
Author(s):  
Mahmood Sh. Majeed ◽  
Raid W. Daoud
Keyword(s):  
Genetic Algorithms ◽  
Photonic Crystal ◽  
Photonic Crystal Fiber ◽  
New Method ◽  
Proper Solution ◽  
Artificial Intelligent ◽  
Crystal Fiber ◽  
Fitness Value ◽  
First Pass ◽  
Crossover And Mutation

A new method proposed in this paper to compute the fitness in Genetic Algorithms (GAs). In this new method the number of regions, which assigned for the population, divides the time. The fitness computation here differ from the previous methods, by compute it for each portion of the population as first pass, then the second pass begin to compute the fitness for population that lye in the portion which have bigger fitness value. The crossover and mutation and other GAs operator will do its work only for biggest fitness portion of the population. In this method, we can get a suitable and accurate group of proper solution for indexed profile of the photonic crystal fiber (PCF).

Doxastic Naturalism and Hume's Voice in theDialogues

2016 ◽  
Vol 14 (3) ◽  
pp. 253-274 ◽  
Author(s):  
C. M. Lorkowski
Keyword(s):  
Comprehensive Survey ◽  
Naturalistic Interpretation ◽  
New Evidence

I argue that acknowledging Hume as a doxastic naturalist about belief in a deity allows an elegant, holistic reading of his Dialogues. It supports a reading in which Hume's spokesperson is Philo throughout, and enlightens many of the interpretive difficulties of the work. In arguing this, I perform a comprehensive survey of evidence for and against Philo as Hume's voice, bringing new evidence to bear against the interpretation of Hume as Cleanthes and against the amalgamation view while correcting several standard mistakes. I ultimately isolate the interpretation of Philo's Reversal at the end of the Dialogues as of paramount importance, and show how my naturalistic interpretation makes this, and other notoriously difficult passages, unproblematic.

Sign in / Sign up

Export Citation Format

Share Document