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.
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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.
Conclusion:
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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