Prospects and expectations of ehealth services in north-lima from mathematical modeling and computational simulation

2015 ◽  
Author(s):  
Huber Nieto-Chaupis
Keyword(s):  
Mathematical Modeling ◽  
Computational Simulation ◽  
Ehealth Services

Computational Biology: Development in the Field of Medicine

2021 ◽  
Keyword(s):  
Mathematical Modeling ◽  
Computational Biology ◽  
Social Systems ◽  
Computational Simulation ◽  
Analytical Data ◽  
Theoretical Methods ◽  
Simulation Techniques

Computational biology involves the development and application of analytical-data and theoretical methods, computational simulation techniques, and mathematical modeling to the study of biological, behavioral, ecological, and social systems.

The Mathematical Modeling and Computational Simulation for Error-Prone PCR

2013 ◽  
pp. 798-804
Author(s):  
Lixin Luo ◽  
Fang Zhu ◽  
Si Deng
Keyword(s):  
Mathematical Modeling ◽  
Enzyme Activity ◽  
Quantitative Analysis ◽  
Industrial Production ◽  
Computational Simulation ◽  
Catalytic Efficiency ◽  
Computational Method ◽  
Mathematical Principle ◽  
Replication Process ◽  
Modelling Error

Many enzymes have been widely used in industrial production, for they have higher catalytic efficiency and catalytic specificity than the traditional catalysts. Therefore, the performance of enzymes has attracted wide attention. However, due to various factors, enzymes often cannot show their greatest catalytic efficiency and the strongest catalytic ability in industrial production. In order to improve the enzyme activity and specificity, people become increasingly interested in the transformation and modification of existing enzymes. For the structure modification of proteinase, this chapter introduces a computational method for modelling error-prone PCR. Error-prone PCR is a DNA replication process that intentionally introduces copying errors by imposing mutagenic reaction condition. We then conclude about the mathematical principle of error-prone PCR which may be applied to the quantitative analysis of directed evolution in future studies.

scholarly journals Mathematical Modeling and Computational Simulation of a New Biomedical Instrument Design

2012 ◽  
Vol 2012 ◽  
pp. 1-5
Author(s):  
Zheng Jeremy Li
Keyword(s):  
Mathematical Modeling ◽  
Computational Simulation ◽  
Manufacturing Cost ◽  
Research Papers ◽  
Biomedical Instrument ◽  
Additional Manufacturing ◽  
Biomedical Industry ◽  
Surgical Operations ◽  
Made In ◽  
Prototype Testing

Endo surgiclip instrument is the biomedical instrument that can be applied for endoscopic surgery to assist surgeons in homeostasis and secure mucosal gap surfaces during surgical operations. Since some clinic feedbacks show the surgiclip drop-off incidents which can potentially sever organ and tissue, the improvement of endo surgiclip instrument has been made in these years. Since few research papers were involved in the study of endo surgiclip instrument performance via mathematical modeling and computational simulation, currently some instrumental modifications are mainly based on clinic lab tests which prolong the improvement cycle and increase additional manufacturing cost. This paper introduces a new biomedical surgiclip instrument based on mathematical modeling, computer-aided simulation, and prototype testing. The analytic methodology proposed in this paper can help engineers in biomedical industry develop and improve biomedical instrument. Compared to the current conventional surgiclip instruments, this new surgiclip instrument can properly assist surgeon in surgical procedure with less operational force and no surgiclip drop-off incident. The prototype has also been built and tested. Both computational simulation and prototype testing show close results which validate the feasibility of this newly developed endo surgiclip instrument and the methodologies of mathematical modeling based computational simulation proposed in this paper.

The Mathematical Modeling and Computational Simulation for Error-Prone PCR

2011 ◽  
pp. 234-240
Author(s):  
Lixin Luo ◽  
Fang Zhu ◽  
Si Deng
Keyword(s):  
Mathematical Modeling ◽  
Enzyme Activity ◽  
Quantitative Analysis ◽  
Industrial Production ◽  
Computational Simulation ◽  
Catalytic Efficiency ◽  
Computational Method ◽  
Mathematical Principle ◽  
Replication Process ◽  
Modelling Error

Many enzymes have been widely used in industrial production, for they have higher catalytic efficiency and catalytic specificity than the traditional catalysts. Therefore, the performance of enzymes has attracted wide attention. However, due to various factors, enzymes often cannot show their greatest catalytic efficiency and the strongest catalytic ability in industrial production. In order to improve the enzyme activity and specificity, people become increasingly interested in the transformation and modification of existing enzymes. For the structure modification of proteinase, this chapter introduces a computational method for modelling error-prone PCR. Error-prone PCR is a DNA replication process that intentionally introduces copying errors by imposing mutagenic reaction condition. We then conclude about the mathematical principle of error-prone PCR which may be applied to the quantitative analysis of directed evolution in future studies.

Synthetic Biology as a Proof of Systems Biology

2009 ◽  
pp. 97-115
Author(s):  
Andrew Kuznetsov
Keyword(s):  
Mathematical Modeling ◽  
Systems Biology ◽  
Synthetic Biology ◽  
Biological Systems ◽  
Computational Simulation ◽  
Global Scale ◽  
New Science ◽  
Scientific Disciplines ◽  
Molecular Compounds ◽  
Reductionist Approach

Biologists have used a reductionist approach to investigate the essence of life. In the last years, scientific disciplines have merged with the aim of studying life on a global scale in terms of molecules and their interactions. Based on high-throughput measurements, Systems Biology adopts mathematical modeling and computational simulation to reconstruct natural biological systems. Synthetic Biology seeks to engineer artificial biological systems starting from standard molecular compounds coding in DNA. Can Systems and Synthetic Biology be combined with the idea of creating a new science—‘SYS Biology’ that will not demarcate natural and artificial realities? What will this approach bring to medicine?

Synthetic Biology as a Proof of Systems Biology

2011 ◽  
pp. 1981-1998
Author(s):  
Andrew Kuznetsov
Keyword(s):  
Mathematical Modeling ◽  
Systems Biology ◽  
Synthetic Biology ◽  
Biological Systems ◽  
Computational Simulation ◽  
Global Scale ◽  
New Science ◽  
Scientific Disciplines ◽  
Molecular Compounds ◽  
Reductionist Approach

Biologists have used a reductionist approach to investigate the essence of life. In the last years, scientific disciplines have merged with the aim of studying life on a global scale in terms of molecules and their interactions. Based on high-throughput measurements, Systems Biology adopts mathematical modeling and computational simulation to reconstruct natural biological systems. Synthetic Biology seeks to engineer artificial biological systems starting from standard molecular compounds coding in DNA. Can Systems and Synthetic Biology be combined with the idea of creating a new science—‘SYS Biology’ that will not demarcate natural and artificial realities? What will this approach bring to medicine?

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