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Data mining in bio-informatics

In the world, the computer science industry is moving ahead towards more and more development and efficient outcomes. This report explains some basic  concepts of  data mining in bio informatics. Some essential fields of bioinformatics are explained. The application of data mining in bioinformatics is also described. It also highlights some of the current limitations and advantages of data mining in bioinformatics. It is extremely important that we study and research on the topics so that we take a responsibility towards making this world happy and prosperous and take it to a light . let’s  not forget what It is to be a computer student and we should always contribute towards the development of the field we all indulged it with extreme sincerity and obtain good outcomes. 

Key words
 Data Mining, Bioinformatics

    • Introduction
    • Literature review & related work
    • My perspective about the topic
    • Applications
    • Impact of the topic
    • Discussion & conclusions
    • references

Data mining is the act of looking at vast databases keeping in mind the goal to create new data.
Data mining is the way towards breaking down shrouded examples of information as per alternate points of view for classification into valuable data, which is gathered and collected. It’s also called as data discovery.
It simply means to dig out the information from a data base.  

Bio informatics is the act of studying and analysing the biological and bio chemical information using computers.

Now the question arises how bio informatics do and data mining go hand in hand.
Basically, data mining is the technique that is applied to study various biological data especially used for analysis of genomic data

Data mining today is very important and it can be understood at various levels.  To study and analyze data through statistical understanding and concepts is what makes us collect and store large amounts of data in sets.
The goal of data mining is as simple as drawing water from a calm lake but its implementation makes the lake a sea. 
It is not a single dimensional method or term, it contains steps which are necessary for proper analysis of data and therefore curving out predictions.
Mining of  bio-information is the joining area between the two terms . Data mining has a very big role in examination of biological data and the databases.
The initial step of studying the concept of data mining in bio informatics is to clear up the idea. It has originated from alternate points of view inside practice and the scholarly world. Here are some of the researches of data mining & bio informatics. Let us understand that what the researchers think about these concepts.

The weka data mining software   
The WEKA project aims to provide a comprehensive collection of machine learning algorithms and data pre-processing tools to researchers and practitioners alike. [1]

                              Mark hall
Journal of Data Mining and Bioinformatics
The objective of IJDMB is to facilitate collaboration between data mining researchers and bioinformaticians by presenting cutting edge research topics and methodologies in the area of data mining for bioinformatics.[2]
                 Prof. Xiaohua (Tony) Hu
The author explains various applications of the same topic, he has also mentioned some limiations faced by the topic itself  etc. [3]

                    Khalid Raza
This paper looks at the use of Data Mining in the domain of Bioinformatics.[4]

My Perspective :
Starting with the first research work, i believe its a good software as it helps many of the scholars to understand and work effectively so it is a good block or a helping hand for those who are working on a topic or a project related or in accordance with data mining.

For the second one , its a very informative series started by the author himself as it is a journal so it is kept updated with more and more material related to the particular field , it helped me as well as i provided me some good information.

The third one is a very comprehensive and brief paper by the author, it is concise and concrete. it gives a cut to chase idea and knowledge about the topic.

Also , the paper by Sebastian is a great one it has been effectively created and designed to strike the important topics and highlight the major lines in a very beautiful manner.

Although its a very good topic but there has not been much done to it yet .
Over all i am pretty satisfied with all the work done on the topic so far.

The application of data mining to bio-informatics include
 quality discovering 
 protein work area location
 work theme identification
 protein work deduction
malady analysis
infection anticipation
 ailment treatment streamlining
 protein and quality connection arrange recreation
 data purifying    
 protein sub-cell area forecast etc.

BIOINFORMATICS is a multidisciplinary field, it inculcates various methods and tools for biological data.
Its a very vast field as it includes various other implementations of maths , sciences and computers.
A very simple thing to understand is that in bio informatics there is scope for computer programming. 
It simply uses the computer skills of a person to implicate the functional mechanism of bio informatics.
It has a variety of uses, however mostly its dealing with genes etc.
Not only this it also deals with the information and structure of the nucleic acid and proteomics.
The most important goal is to increase the knowledge a person has about biological processes.

    • Sequence analysis
    • Genome annotation
    • Analysis of gene expression
    • Analysis of protein expression
    • Protein structure prediction
    • Protein protein docking

Both of these topics are as interdisciplinary science. Information mining approaches appear to be preferably suited for bioinformatics, since bioinformatics is information rich yet does not have a thorough hypothesis of life's association at the atomic .

Data mining in bioinformatics revolutionarily affects biology, New groups of computers are crunching on amounts of numbers, more than ever. This has consequently lead to new methodologies in information mining, advancing the calculations and mixes of those tossed at the natural information.

Data mining & bioinformatics are quickly developing examination territory today.

 It is vital to analyze what are the several research issues in bio-informatics and grow 
new data-mining strategies for effective and good examination.

[1] Mark Hall, “The WEKA Data Mining Software: An Update” department of computer science, university of Waikato.

[2] Prof. Xiaohua (Tony) Hu, “Journal of Data Mining and Bioinformatics”.

 [3] KHALID RAZA,” APPLICATION OF DATA MINING IN BIOINFORMATICS” Centre for     Theoretical Physics, Jamia Millia Islamia, New Delhi-110025, India.

[4] Sebastian Kropp,”data mining & bio informatics” Monash University Faculty of Information Technology

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