Pattern it is machine learning or machine pattern

Pattern recognition is one of the key strategies by
which brain performs analogical reasoning of many life problems based on the
information accumulated through its sense organs.  In a general perspective, pattern recognition
involves receiving an input data, analysing it for similar, specific, regular
patterns based on which meaningful interpretation is made. Pattern recognition
can be employed to make computers execute tasks like humans, even faster and
more accurately, by figuring out actual problems and using a collection of
mathematical, statistical, heuristic and inductive techniques to find solutions.
When a computer program is trained to learn the pattern and categorize the data,
then it is machine learning or machine pattern recognition.  Solutions based on pattern recognition may be
employed almost everywhere and anywhere – medicine, health and pharma industry,
agriculture, financial markets, forensic investigations. During the last few
decades, enormous amount of biological data in different formats has been
generated using advanced technologies. Moreover, number of databases are also
developed by researchers, which accumulates huge molecular data. Consequently,
demand for new computational techniques is also increased for better processing
of this data.  Mining the useful
information as well as the biological interpretation has become one of the most
impressive bioinformatics problems. The different processes in the nature are
analysed and many nature inspired algorithms have been derived for
computational pattern recognition. 

Studies reveal that biomolecules (DNA, RNA, proteins) in
sequence form and structural form contain different patterns that are
functionally relevant. These patterns also known as motifs are very much
involved in the characterization of these biomolecules. In proteins, patterns
may also occur for which the elements found in secondary structure. Helix turn
helix is a widely studied motif that falls in the category of DNA binding
motifs. Detection techniques of such patterns make use of the structural
features as well 1. Recent studies in drug discovery show that proline rich
linear motifs are excellent mediators for intermolecular interactions seen in
many faces of immune response activities, and hence these motifs are considered
as drug targets in immune mediated diseases. Alignment method, local search,
heuristic approach etc. are a few among the applied techniques for this pattern
identification task. Within medical science, pattern recognition is the basis
for computer-aided diagnosis (CAD) systems. CAD describes a procedure that
supports the doctor’s interpretations and findings. Detection of patterns
demands computational techniques that produce optimum results. 


I'm Mary!

Would you like to get a custom essay? How about receiving a customized one?

Check it out