Data Mining - High Impact Factor Journals|OMICS International|Journal Of Computer Science And Systems Biology

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Data Mining - High Impact Factor Journals

Data mining is a branch of computer science which analyses the data from various perspectives and transforms into useful information. This computational process of large data sets involves various methods artificial intelligence, statistics and other database systems. This kind of input data is further used in Machine leaning, data management aspects. Data mining is widely used in the field of science and Engineering such as bioinformatics, genetics, medicine, education and electrical power engineering. In the case of human genetics sequence mining is employed to detect the changes the sequence of DNA which is causing the disease. Data mining methods are utilized in electrical power engineering to monitor the high voltage equipments. High-impact journals are those considered to be highly influential in their respective fields. The impact factor of journal provides quantitative assessment tool for grading, evaluating, sorting and comparing journals of similar kind. It reflects the average number of citations to recent articles published in science and social science journals in a particular year or period, and is frequently used as a proxy for the relative importance of a journal within its field. It is first devised by Eugene Garfield, the founder of the Institute for Scientific Information. The impact factor of a journal is evaluated by dividing the number of current year citations to the source items published in that journal during the previous two years. The Journal of Computer Science & Systems Biology includes a wide range of fields in its discipline to create a platform for the authors to make their contribution in the form of review, research, mini-review, short communication etc towards the journal and the editorial office promises a peer review process for the submitted manuscripts for quality publishing.
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Last date updated on August, 2021