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u n o e J Proteomics COMMENTARY
Bioinformatics Tools and Techniques: Datamining – commentary
Margaret Simonian * Department of Neurology, LA-Biomedical Research Institute at Harbor-UCLA, California, USA ABOUT THE STUDY: mining is a very powerful tool to get information for hidden patterns. Bioinformatics: Types of data mining:- Bioinformatics is defined as the multi-disciplinary field that Data mining has several types, it includes: develops methods and software tools for understanding biological data; it's the appliance of computational technology to • Relational databases handle the rapidly ever-growing depository of data associated • Data warehouses with biology. Bioinformatics includes divergent scope of the study, including computer sciences, biology, biotechnology, • Advanced DBand information repositories statistics, and engineering. • Object-oriented and object-relational databases The mathematical, statistical, and computing methods aim to • Transactional and Spatial databases resolve the biological aspects using DNA and amino acid sequences and related to the biological information. • Heterogeneous and legacy databases Keywords: Data Mining, Bioinformatics, Text Mining, DNA • Multimedia and streaming database Sequencing, Profile Tooling, Genomics. • Text databases History of bioinformatics- • Text mining and Web mining
Paulien Hogeweg and Ben Hesper coined the term DATA MINING TOOLS AND TECHNIQUES bioinformatics in 1970, the study of data processes in bioinformatics. Bioinformatics is similar to the study of the TOOLS FOR DATA MINING: chemical processes in biological systems known as biochemistry. 1) R language: DNA analysis also done similar advances in, It is a tool for statistical computing and graphics. It is all about • The biological methods have made the easier manipulation of data handling and storage capacity. DNA, and DNA sequencing. 2) Oracle Data Mining (ODM): • Computer science, which has the ever-growing miniaturized and more powerful computers, also as novel software better The factors of the ODM is a Database Option, It gives useful suited to handle bioinformatics tasks. information for the algorithms of the data mining. Data mining has done wide improvements in sequencing TECHNIQUES FOR DATA MINING: technology and rises to an exponential increase in knowledge. 1. Classification The ‘Big Data’ has laid out new challenges in terms of knowledge mining and management, calling for more expertise 2. Clustering from computing into the sector. 3. Regression Data Mining:- 4. Association Rules Data mining is elucidated, which is used to convert raw data into 5. Outer detection useful information. It uses disciplinary skills in machine 6. Sequential Patterns learning, artificial intelligence, and database technology. Data
Correspondence to: Margaret Simonian, Department of Neurology, LA-Biomedical Research Institute at Harbor-UCLA, California, USA, E-mail: maragaretsimonain@edu Received: November 4, 2020; Accepted: November 18, 2020; Published: November 25, 2020 Citation: Simonian M (2020) Bioinformatics Tools and techniques for Data Mining, J Data Mining Genomics and Proteomics.11.e001. Copyright: © 2020 Simonian M. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
J Data Mining Genomics Proteomics, Vol.11 Iss.S3 No:S3-001 1 Simonian M
7. PredictionThese techniques give relevant information about information investigation. Notwithstanding, the very beginnings data mining and Metadata. This finds the hidden data from the of bioinformatics happened over 50 years prior, when PCs were patterns of the data set. It analyses the past and predicting the as yet speculation and DNA couldn't yet be sequenced. The future for the analysis. establishments of bioinformatics were laid in the mid-1960s with the utilization of computational strategies to protein CONCLUSION: arrangement examination (eminently, all over again succession This is a short commentary about Bioinformatics Tools and get together, organic grouping information bases and Techniques: Data mining. It is simple for the present replacement models). Data mining helps in the knowledge bases understudies and specialists to accept that cutting edge information. bioinformatics arose as of late to help cutting edge sequencing
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