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      Frequency-rank Distributions in Proteomics

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            Abstract

            This paper analyzes the protein abundances in 8 organisms to determine if they fit any of a number of commonly-seen distributions in frequency-rank analyses, with the intention of drawing analogies between biochemistry and linguistics. The organisms were chosen so as to be representative and come from a wide range of body complexities. Our analysis suggests that while individual organisms fit certain distributions quite well, there is no overarching thread that unifies the protein distributions found across the living world, at least on the scale of individual proteins.

            Content

            Author and article information

            Journal
            ScienceOpen Preprints
            ScienceOpen
            17 June 2021
            Affiliations
            [1 ] Department of Physics, Indian Institute of Technology Hyderabad, IITH Main Road near NH-65, Kandi, Telangana, India
            Author notes
            Article
            10.14293/S2199-1006.1.SOR-.PP2VSKF.v1
            cfbf0fe9-d53a-4d0d-8a2a-287b625b1612

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .


            All data generated or analysed during this study are included in this published article (and its supplementary information files).
            Statistics,Biostatistics,Bioinformatics & Computational biology,Life sciences
            bioinformatics,statistical linguistics,protein abundance,rank-size,fat-tailed distributions,power law,proteomics,frequency-rank distribution,zipf’s law

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