A Comparison of Second Order and Non-Second Order Limit Language Generated by Yusof-Goode Splicing System

2014 ◽  
Vol 72 (1) ◽  
Author(s):  
Muhammad Azrin Ahmad ◽  
Nor Haniza Sarmin ◽  
Wan Heng Fong ◽  
Yuhani Yusof
Keyword(s):  
Mathematical Model ◽  
Restriction Enzyme ◽  
Formal Language ◽  
Laboratory Experiments ◽  
Second Order ◽  
Language Theory ◽  
Double Stranded Dna ◽  
The Difference ◽  
Splicing Systems ◽  
Limit Language

DNA splicing process is a study on the recombinant behavior of double-stranded DNA molecules with the existence of restriction enzyme and ligase. Head introduced the first mathematical model of splicing systems by using the relation of informational macromolecules and formal language theory. In addition, a few laboratory experiments have been conducted in order to verify certain types of splicing language called inert/adult, transient and limit language. Previously, researchers have focused on those types of splicing languages.   Recently, an extension of limit languages namely second order limit language has been introduced. In this paper, the difference between second order limit languages and non-second order limit languages is depicted in some examples. Then, the formations of second order limit language in Yusof-Goode splicing system are investigated. 

A New Relation of Second Order Limit Language in Simple and Semi-Simple Splicing System

2014 ◽  
Vol 71 (5) ◽  
Author(s):  
Muhammad Azrin Ahmad ◽  
Nor Haniza Sarmin ◽  
Wan Heng Fong ◽  
Yuhani Yusof
Keyword(s):  
Formal Language ◽  
Theoretical Study ◽  
Second Order ◽  
Language Theory ◽  
Biological Traits ◽  
Dna Molecules ◽  
Double Stranded Dna ◽  
New Type ◽  
Limit Language ◽  
Dna Splicing

Splicing system, which is an abstraction of operations on DNA molecules, can be modelled mathematically under the framework of formal language theory and informational macromolecules. The recombinant behavior of the set of double-stranded DNA molecules under the influence of restriction enzyme and ligase further lead to the cut and paste phenomenon in splicing system. The theoretical study of splicing language has contributed to a new type of splicing language known as a second order limit language, which is an extension of limit language. Some types of splicing system can produce second order limit language. Y-G splicing system is chosen among other models to model the DNA splicing process as this model preserves the biological traits and presents the transparent behavior of the DNA splicing process. In this paper, the relation between second order limit language with simple splicing and semi-simple splicing system are presented.

scholarly journals Generalisations of DNA Splicing Systems with One Palindromic Restriction Enzyme

MATEMATIKA ◽  
2018 ◽  
Vol 34 (1) ◽  
pp. 59-71 ◽  
Author(s):  
Fong Wan Heng ◽  
Nurul Izzaty Ismail
Keyword(s):  
Restriction Enzyme ◽  
Formal Language ◽  
Restriction Enzymes ◽  
Potential Effect ◽  
Language Theory ◽  
Regular Expressions ◽  
Nitrogen Bases ◽  
Restriction Sites ◽  
Splicing Systems ◽  
Dna Splicing

In DNA splicing system, the potential effect of sets of restriction enzymes and a ligase that allow DNA molecules to be cleaved and re-associated to produce further molecules is modelled mathematically.  This modelling is done in the framework of formal language theory, in which the nitrogen bases, nucleotides and restriction sites are modelled as alphabets, strings and rules respectively.  The molecules resulting from a splicing system is depicted as the splicing language.  In this research, the splicing language resulting from DNA splicing systems with one palindromic restriction enzyme for one and two (non-overlapping) cutting sites are generalised as regular expressions.

scholarly journals Generalisations of Splicing Languages in DNA Splicing Systems Involving Two Palindromic Restriction Enzymes

2021 ◽  
Vol 17 (2) ◽  
pp. 128-138
Author(s):  
Wan Heng Fong ◽  
Nurul Izzaty Ismail ◽  
Nor Haniza Sarmin
Keyword(s):  
Restriction Enzyme ◽  
Dna Computing ◽  
Formal Language ◽  
Restriction Enzymes ◽  
Language Theory ◽  
Dna Molecules ◽  
Induction Method ◽  
Different Types ◽  
Splicing Systems ◽  
Dna Splicing

DNA splicing system is initiated by Head to mathematically model a relation between formal language theory and DNA molecules. In DNA splicing systems, DNA molecules are cut and recombined in specific ways with the existence of enzymes, which are also known as endonucleases, to produce further molecules. The resulting molecules are depicted as splicing languages by using concepts in formal languages theory. A sequence of restriction enzyme that reads the same forward and backward is called as a palindromic rule. Previously, researches on different types of splicing languages have been done. In this research, generalisations of splicing languages resulting from DNA splicing systems with non-overlapping cutting sites of two palindromic restriction enzymes are presented as theorems using the induction method. The results from this research are beneficial for researchers in the field of DNA computing since it contributes to the development of splicing languages generated from DNA splicing systems with different palindromic restriction enzymes by using these generalisations.

scholarly journals Automata for DNA Splicing Languages with Palindromic and Non-Palindromic Restriction Enzymes using Grammars

MATEMATIKA ◽  
2019 ◽  
Vol 35 (4) ◽  
pp. 1-14
Author(s):  
Wan Heng Fong ◽  
Nurul Izzaty Ismail ◽  
Nor Haniza Sarmin
Keyword(s):  
Dna Sequences ◽  
Formal Language ◽  
Restriction Enzymes ◽  
Language Theory ◽  
Dna Assembly ◽  
Dna Molecules ◽  
Splicing Systems ◽  
Transition Graphs ◽  
Palindromic Sequences ◽  
Dna Splicing

In DNA splicing system, DNA molecules are cut and recombined with the presence of restriction enzymes and a ligase. The splicing system is analyzed via formal language theory where the molecules resulting from the splicing system generate a language which is called a splicing language. In nature, DNA molecules can be read in two ways; forward and backward. A sequence of string that reads the same forward and backward is known as a palindrome. Palindromic and non-palindromic sequences can also be recognized in restriction enzymes. Research on splicing languages from DNA splicing systems with palindromic and non-palindromic restriction enzymes have been done previously. This research is motivated by the problem of DNA assembly to read millions of long DNA sequences where the concepts of automata and grammars are applied in DNA splicing systems to simplify the assembly in short-read sequences. The splicing languages generated from DNA splicing systems with palindromic and nonpalindromic restriction enzymes are deduced from the grammars which are visualised as automata diagrams, and presented by transition graphs where transition labels represent the language of DNA molecules resulting from the respective DNA splicing systems.

scholarly journals Logic and the Generative Power of Autosegmental Phonology

2014 ◽  
Vol 1 (1) ◽  
Author(s):  
Adam Jardine
Keyword(s):  
Formal Language ◽  
Second Order ◽  
Order Logic ◽  
Language Theory ◽  
Preliminary Conclusion ◽  
Autosegmental Phonology ◽  
Finite State ◽  
Regular Sets ◽  
Second Order Logic ◽  
Monadic Second Order Logic

<p>Autosegmental Phonology is studied in the framework of Formal Language Theory, which classifies the computational complexity of patterns. In contrast to previous computational studies of Autosegmental Phonology, which were mainly concerned with finite-state implementations of the formalism, a methodology for a model-theoretic study of autosegmental diagrams with monadic second-order logic is introduced. Monadic second order logic provides a mathematically rigorous way of studying autosegmental formalisms, and its complexity is well understood. The preliminary conclusion is that autosegmental diagrams which conform to the well-formedness constraints defined here likely describe at most regular sets of strings.</p>

scholarly journals An Improved Measurement Uncertainty Calculation Method of Profile Error for Sculptured Surfaces

2019 ◽  
Vol 32 (1) ◽  
Author(s):  
Chenhui Liu ◽  
Zhanjie Song ◽  
Yicun Sang ◽  
Gaiyun He
Keyword(s):  
Mathematical Model ◽  
Linear Models ◽  
Second Order ◽  
Sculptured Surfaces ◽  
Profile Error ◽  
Adaptive Monte Carlo ◽  
Uncertainty In Measurement ◽  
Uncertainty Calculation ◽  
The Difference ◽  
Adaptive Monte Carlo Method

Abstract The current researches mainly adopt “Guide to the expression of uncertainty in measurement (GUM)” to calculate the profile error. However, GUM can only be applied in the linear models. The standard GUM is not appropriate to calculate the uncertainty of profile error because the mathematical model of profile error is strongly non-linear. An improved second-order GUM method (GUMM) is proposed to calculate the uncertainty. At the same time, the uncertainties in different coordinate axes directions are calculated as the measuring points uncertainties. In addition, the correlations between variables could not be ignored while calculating the uncertainty. A k-factor conversion method is proposed to calculate the converge factor due to the unknown and asymmetrical distribution of the output quantity. Subsequently, the adaptive Monte Carlo method (AMCM) is used to evaluate whether the second-order GUMM is better. Two practical examples are listed and the conclusion is drawn by comparing and discussing the second-order GUMM and AMCM. The results show that the difference between the improved second-order GUM and the AMCM is smaller than the difference between the standard GUM and the AMCM. The improved second-order GUMM is more precise in consideration of the nonlinear mathematical model of profile error.

scholarly journals Some relations on different types of splicing systems

2014 ◽  
Vol 6 (2) ◽  
Author(s):  
Yuhani Yusof ◽  
Nor Haniza Sarmin ◽  
Fong Wan Heng ◽  
Fariba Karimi
Keyword(s):  
Computer Science ◽  
Formal Language ◽  
Theoretical Computer Science ◽  
Language Theory ◽  
Discrete Mathematics ◽  
Generative Capacity ◽  
Theoretical Computer ◽  
Different Types ◽  
Splicing Systems

Splicing system is a formal characterization of the generative capacity of specified enzymatic activities acting on initial DNA molecules that was first initiated by Head in 1987. This splicing system is formally illustrated under the framework of Formal Language Theory which is a branch of Theoretical Computer Science and Applied Discrete Mathematics. There are many types of splicing systems including null-context, simple, semi-simple and seminull. In this paper, some relations for those types of splicing systems are presented.

scholarly journals THE CHARACTERIZATIONS OF DIFFERENT SPLICING SYSTEMS

2012 ◽  
Vol 09 ◽  
pp. 89-94
Author(s):  
FARIBA KARIMI ◽  
NOR HANIZA SARMIN ◽  
FONG WAN HENG
Keyword(s):  
Formal Language ◽  
Biological Process ◽  
Dna Recombination ◽  
Restriction Enzymes ◽  
Theoretical Computer Science ◽  
Language Theory ◽  
Discrete Mathematics ◽  
Theoretical Computer ◽  
Points Of View ◽  
Splicing Systems

The concept of splicing system was first introduced by Head in 1987 to model the biological process of DNA recombination mathematically. This model was made on the basis of formal language theory which is a branch of applied discrete mathematics and theoretical computer science. In fact, splicing system treats DNA molecule and the recombinant behavior by restriction enzymes and ligases in the form of words and splicing rules respectively. The notion of splicing systems was taken into account from different points of view by many mathematicians. Several modified definitions have been introduced by many researchers. In this paper, some properties of different kinds of splicing systems are presented and their relationships are investigated. Furthermore, these results are illustrated by some examples.

Observation and Experimentation

2018 ◽  
Author(s):  
Massimiliano Di Ventra
Keyword(s):  
Laboratory Experiments ◽  
The Difference

This chapter expands on the previous one on the role of experiments in Science. It explains the difference between observations of phenomena and controlled laboratory experiments.

scholarly journals Modelling time efficiency of cobot-supported kit preparation

2019 ◽  
Vol 106 (5-6) ◽  
pp. 2227-2241 ◽  
Author(s):  
Patrik Fager ◽  
Martina Calzavara ◽  
Fabio Sgarbossa
Keyword(s):  
Experimental Data ◽  
Mathematical Model ◽  
Cycle Time ◽  
Laboratory Experiments ◽  
Spare Parts ◽  
Batch Preparation ◽  
Assembly Quality ◽  
Numerical Example ◽  
Business To Business ◽  
Support Time

AbstractKitting – meaning to supply assembly with components in presorted kits – is widely seen as beneficial for assembly quality and efficiency when there is a multitude of component variants. However, the process by which kits are prepared – the kit preparation – is labour-intensive, and kit errors are problematic at assembly processes. The use of robotics to support kit preparation has received some attention by researchers, but literature is lacking with respect to how collaborative robots – cobots – can support kit preparation activities. The purpose of this paper is to identify the potential of a cobot to support time-efficient batch preparation of kits. To address the purpose, the paper presents a mathematical model for estimation of the cycle time associated with cobot-supported kit preparation. The model is applied in a numerical example with experimental data from laboratory experiments, and cobot-supported kit preparation is compared with manual kit preparation. The findings suggest that cobot-supported kit preparation is beneficial with diverse kits and smaller components quantities per SKU (Stock Keeping Unit) and provides less variability of the outcome, when compared to manual kit preparation. The paper reveals several insights about cobot-supported kit preparation that can be valuable for both academics and practitioners. The model developed can be used by practitioners to assess the potential of cobots to support kit-batch preparation in association with assembly, spare parts, repair and maintenance, or business to business industry.

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