How Does Computer Science Change Molecular Biology?

2010 ◽  
pp. 13-13
Author(s):  
Alain Viari
Keyword(s):  
Molecular Biology ◽  
Computer Science

Bioinformatics Research in Australia

2003 ◽  
Vol 07 (03) ◽  
pp. 82-84
Author(s):  
Yi-Ping Phoebe Chen ◽  
Geoff McLachlan
Keyword(s):  
Molecular Biology ◽  
Research And Development ◽  
Computer Science ◽  
21St Century ◽  
Asia Pacific ◽  
Research Areas ◽  
Bioinformatics Community

Bioinformatics is the intersection of computer science, statistics, molecular biology and genetics. It is one of the most important emerging research areas of the 21st century and has already attracted worldwide interest. It is clear that major initiatives are being undertaken which will establish Australia both as a vital link in the international bioinformatics community for research and development and also as an Asia-Pacific service for bioinformatics. This article briefly notes some groups carrying out bioinformatics research in Australia.

Natural Language Processing and Biological Methods

2011 ◽  
pp. 1173-1178
Author(s):  
Gemma Bel Enguix ◽  
M. Dolores Jiménez López
Keyword(s):  
Natural Language Processing ◽  
Molecular Biology ◽  
Natural Language ◽  
Computer Science ◽  
Genetic Code ◽  
20Th Century ◽  
Language Processing ◽  
Dna Sequences ◽  
Theoretical Computer Science ◽  
Automated Generation

During the 20th century, biology—especially molecular biology—has become a pilot science, so that many disciplines have formulated their theories under models taken from biology. Computer science has become almost a bio-inspired field thanks to the great development of natural computing and DNA computing. From linguistics, interactions with biology have not been frequent during the 20th century. Nevertheless, because of the “linguistic” consideration of the genetic code, molecular biology has taken several models from formal language theory in order to explain the structure and working of DNA. Such attempts have been focused in the design of grammar-based approaches to define a combinatorics in protein and DNA sequences (Searls, 1993). Also linguistics of natural language has made some contributions in this field by means of Collado (1989), who applied generativist approaches to the analysis of the genetic code. On the other hand, and only from theoretical interest a strictly, several attempts of establishing structural parallelisms between DNA sequences and verbal language have been performed (Jakobson, 1973, Marcus, 1998, Ji, 2002). However, there is a lack of theory on the attempt of explaining the structure of human language from the results of the semiosis of the genetic code. And this is probably the only arrow that remains incomplete in order to close the path between computer science, molecular biology, biosemiotics and linguistics. Natural Language Processing (NLP) –a subfield of Artificial Intelligence that concerns the automated generation and understanding of natural languages— can take great advantage of the structural and “semantic” similarities between those codes. Specifically, taking the systemic code units and methods of combination of the genetic code, the methods of such entity can be translated to the study of natural language. Therefore, NLP could become another “bio-inspired” science, by means of theoretical computer science, that provides the theoretical tools and formalizations which are necessary for approaching such exchange of methodology. In this way, we obtain a theoretical framework where biology, NLP and computer science exchange methods and interact, thanks to the semiotic parallelism between the genetic code and natural language.

Promises and Challenges of Systems Biology

2020 ◽  
Author(s):  
Srijani Chakraborty
Keyword(s):  
Systems Biology ◽  
Molecular Biology ◽  
Computer Science ◽  
And Mathematics ◽  
Engineering Physics

Modern systems biology is essentially interdisciplinary, tying molecular biology, the omics, bioinformatics and non-biological disciplines like computer science, engineering, physics, and mathematics together.

Towards a Bio-Inspired Theoretical Linguistics to Model Man-Machine Communication

2013 ◽  
Vol 1 (1) ◽  
pp. 14-28
Author(s):  
Gemma Bel-Enguix ◽  
M. Dolores Jiménez-López
Keyword(s):  
Molecular Biology ◽  
Natural Language ◽  
Computer Science ◽  
Dna Computing ◽  
Membrane Computing ◽  
Theoretical Computer Science ◽  
Theoretical Computer ◽  
Theoretical Linguistics ◽  
Machine Communication ◽  
Natural Description

The paper provides an overview of what could be a new biological-inspired linguistics. The authors discuss some reasons for attempting a more natural description of natural language, lying on new theories of molecular biology and their formalization within the area of theoretical computer science. The authors especially explore three bio-inspired models of computation –DNA computing, membrane computing and networks of evolutionary processors (NEPs) – and their possibilities for achieving a simpler, more natural, and mathematically consistent theoretical linguistics.

A point of contact between computer science and molecular biology

1994 ◽  
Vol 1 (1) ◽  
pp. 69-78 ◽  
Author(s):  
W. Miller ◽  
S. Schwartz ◽  
R.C. Hardison
Keyword(s):  
Molecular Biology ◽  
Computer Science

Computational Biology

2011 ◽  
pp. 641-646
Author(s):  
Andrew LaBrunda ◽  
Michelle LaBrunda
Keyword(s):  
Systems Biology ◽  
Molecular Biology ◽  
Computational Biology ◽  
Computer Science ◽  
Structure Prediction ◽  
Evolutionary Biology ◽  
Deterministic Model ◽  
Computational Genomics ◽  
Exact Moment ◽  
And Mathematics

It is impossible to pinpoint the exact moment at which computational biology became a discipline of its own, but one could say that it was in 1997 when the society of computational biology was formed. Regardless of its exact birthday, the research community has rapidly adopted computational biology and its applications are being vigorously explored. The study and application of medicine is a dynamic challenge. Changes in medicine usually take place as a result of new knowledge acquired through observation and experimentation. When a tamping rod 1-inch thick went through Phineas Gage’s head in 1848, his survival gave the medical field an unusual opportunity to observe behavior of a person missing their prefrontal cortex. This observation lead to the short-lived psychosurgical procedure known as a lobotomy, which attempted to change a person’s behavior by separating two portions of a person’s brain (Pols, 2001). Countless observations, experiments and mistakes represent how almost all medical knowledge has been acquired. The relatively new field of computational biology offers a nontraditional approach to contribute to the medical body of knowledge. Computational biology is a new field combining biology, computer science, and mathematics to solve problems that are unworkable with traditional biological techniques. It includes traditional areas such as systems biology, molecular biology, biochemistry, biophysics, statistics, and computer science, as well as recently developed disciplines including bioinformatics and computational genomics. Algorithms, which are able to closely model biological behavior, validate the medical understanding of the observed processes and can be used to model scenarios that might not be able to be physically reproduced. The goal of computational biology is to use mathematics and computer science to model biological systems on the molecular level. Instead of taking on large complex systems, computational biology is starting small, literally. Modeling problems in molecular biology and biochemistry is a far less daunting task. At a microscopic level, patient’s characteristics drop out of the equation and all information behavior affecting is known. This creates a deterministic model which, given the same input, will always produce the same output. Some of the major subdisciplines of computational biology are computational genomics, systems biology, protein structure prediction, and evolutionary biology, all of which model microscopic structures.

scholarly journals Towards a Bio-Inspired Theoretical Linguistics to Model Man-Machine Communication

2014 ◽  
pp. 1422-1437
Author(s):  
Gemma Bel-Enguix ◽  
M. Dolores Jiménez-López
Keyword(s):  
Molecular Biology ◽  
Natural Language ◽  
Computer Science ◽  
Dna Computing ◽  
Membrane Computing ◽  
Theoretical Computer Science ◽  
Theoretical Computer ◽  
Theoretical Linguistics ◽  
Machine Communication ◽  
Natural Description

The article provides an overview of what could be a new biological-inspired linguistics. The authors discuss some reasons for attempting a more natural description of natural language, lying on new theories of molecular biology and their formalization within the area of theoretical computer science. The authors especially explore three bio-inspired models of computation –DNA computing, membrane computing and networks of evolutionary processors (NEPs) – and their possibilities for achieving a simpler, more natural, and mathematically consistent theoretical linguistics.

Electron Microscopy in Molecular Biology

1967 ◽  
Vol 25 ◽  
pp. 2-3
Author(s):  
Cecil E. Hall
Keyword(s):  
Electron Microscopy ◽  
Molecular Biology ◽  
Noise Level ◽  
Molecular Structures ◽  
Material Structure ◽  
The Arts ◽  
Shadow Casting ◽  
Electron Image ◽  
High Degree ◽  
Very High

The visualization of organic macromolecules such as proteins, nucleic acids, viruses and virus components has reached its high degree of effectiveness owing to refinements and reliability of instruments and to the invention of methods for enhancing the structure of these materials within the electron image. The latter techniques have been most important because what can be seen depends upon the molecular and atomic character of the object as modified which is rarely evident in the pristine material. Structure may thus be displayed by the arts of positive and negative staining, shadow casting, replication and other techniques. Enhancement of contrast, which delineates bounds of isolated macromolecules has been effected progressively over the years as illustrated in Figs. 1, 2, 3 and 4 by these methods. We now look to the future wondering what other visions are waiting to be seen. The instrument designers will need to exact from the arts of fabrication the performance that theory has prescribed as well as methods for phase and interference contrast with explorations of the potentialities of very high and very low voltages. Chemistry must play an increasingly important part in future progress by providing specific stain molecules of high visibility, substrates of vanishing “noise” level and means for preservation of molecular structures that usually exist in a solvated condition.

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