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Impact Factor In Datamining In Proteomics

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. Impact factor in data mining in proteomics of an academic journal is a measure reflecting the average number of citations to recent articles published in the journal. impact factor in data mining in proteomics related to that impact factor is a journal metric and should not be used to assess individual researchers or institutions. impact factor in data mining in proteomics is more then then the ranking for the journal is more.
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Last date updated on September, 2024

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