Transparency Market Research Report Added "Bioinformatics Market" to its database.
Albany, NY -- (SBWIRE) -- 08/27/2015 -- Bioinformatics refers to an interdisciplinary approach to store, retrieve, organize and analyze biological and genetic data. A major part of this field comprises of the activity of developing software tools to generate and process useful biological data.
Bioinformatics is not to be confused with biological computation. While bioinformatics simply makes use of computers for the better understanding of biology can its related concepts, biological computation refers to the subfield of computer engineering that seeks to build biological computers by using biology and bioengineering concepts.
Bioinformatics is, however, much similar to computational biology, only the scale of application and study differs - bioinformatics studies biological data on a molecular scale with keen attention to details while computational biology studies biological data by building large-scale theoretical models of biological systems and studying them with an abstract view to expand our knowledge about them.
Bioinformatics makes use of various laws of computer science, engineering, applied math and statistics to conceptualize biology in terms of bio-molecules (RNAs, DNAs) and process the resulting data in various ways in attempt to decode the code of life.
The use of computers has made the process of reading complex biological data much faster and efficient than before. Huge databases and information systems are used to store and retrieve data; analytical algorithms in soft computing, artificial intelligence, data mining, image processing, etc. are used to analyze data; algorithms in turn depend on theoretical principles of statistics, applied and discrete mathematics, system theory and control theory. As such, bioinformatics uses a good mix of many fundamental principles as well as many applied theories and sciences to manage biological data.
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Aims of bioinformatics
Bioinformatics has threefold aims. Firstly, it manages data in such a manner that it becomes quite easy for researchers to access existing data and submit new data as they are produced. While data storage is an essential task for data management, any kind of data is practically useless unless it is analyzed. Thus, the purpose of bioinformatics is extended further because of data analysis.
The second aim of bioinformatics is to develop systems and tools to analyze data properly. For instance, after having a particular protein sequenced, it is necessary to compare it with a previously sequenced sample. To do this, a program a lot more advanced than a simple text-based comparator is required to understand the biological significance between the differences as well as the similarities in the two sequences studied. Bioinformatics aims at development of such complex tools by using expertise in computational theory and biological understanding.
The third aim of bioinformatics is to analyze the biological data through the use of complex mechanisms and convert the data in such a form that is biologically meaningful. In traditional biological studies, examining individual systems and comparison with only a few related fields was possible. But Bioinformatics has allowed the global analysis and comparison of data available from a variety of fields. Clearly, developing methods to assess the differences between different varieties of biomolecules and identifying similarities over a wide range of dissimilar sources is an essential aspect of managing the huge volumes of data and thus of bioinformatics.
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This field, which was originally developed for the analysis of biological sequences, has now grown to encompass a wide range of areas such as genomics, gene expression, structural biology, etc.
Almost all studies in bioinformatics underpin to two basic approaches. First is that of comparing and grouping biological data according to biological similarities and the second that of analyzing one type of data and using the information thus obtained to infer the observations from some other type of data.
These two approaches in bioinformatics are reflected in the main aims of the field that are storing, organizing and analyzing biological data with keen attention to details on a molecular scale. This has allowed bioinformatics in providing not only greater depth but also adding the dimension of breadth to biological investigations.
This has essentially provided us the opportunity to study individual systems in details with the ones that are related to reveal the similar traits between some systems and underline some unusual features, if any, which are unique
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