title: 0j.py: a software tool for low complexity proteins and protein domains.
abstract: Low complexity proteins and protein domains have sequences which appear highly non-random. Over the years, these sequences have been routinely filtered out during sequence similarity searches because interest has been focused on globular proteins, and inclusion of these domains can severely skew search results. However, early work on these proteins and more recent studies of the related area of repeated protein sequences suggests that low complexity protein domains have function and therefore are in need of further investigation. 0j.py is a new tool for demarcating low complexity protein domains more accurately than has been possible to date. The paper describes 0j.py and its use in revealing proteins with repeated and poly-amino-acid peptides. Statistical methods are then employed to to examine the distribution of these proteins across species, while keyword clustering is used to suggest roles performed by proteins through the use of low complexity domains.
authors.affiliation: Centre for Communications Systems Research, 10 Downing Street, Cambridge, CB2 3DS, England. M.Wise@ccsr.cam.ac.uk
authors.forename: M J
authors.initials: MJ
authors.lastname: Wise
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D019295:Computational Biology; D008969:Molecular Sequence Data; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry* / Q000235:genetics*; D012984:Software; D013045:Species Specificity
chemical_list: D011506:Proteins