Dataset of frequency of occurrence of words in title of journal articles of different fields in biology

Article title should theoretically reflect the content to which it represents. But, there is a paucity of quantitative methods for measuring the relevance of a title to an article’s content. One approach for quantifying the relevance of a title with respect to an article’s content is through mining the frequency of occurrence of words in the article title in the main text of the article. Profiling of high frequency of occurrence of many words in the title would suggests higher degree of relevance of the title with respect to the article’s content. But this must be taken in light of the caveat that some titles are phrased to express the conclusion of a paper, and would thus suffer from a lower frequency of occurrence of words of the title in the main text. This work reports a dataset that has been obtained through analysing the frequency of occurrence of words in the title of journal article in the main text of the article. This process is aided by an in-house MATLAB software coded for the project. Articles from different fields of biology such as biochemistry, bioinformatics, biotechnology, cell biology, computational biology, genetics, genomics, microbiology, molecular biology, structural biology, synthetic biology, and systems biology were put through the same analysis, and an Excel file detailing the frequency of occurrence of words in the title of the article serve as the output. The data is also visualized as a bar chart in the same Excel file.