{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T22:30:23Z","timestamp":1758925823941},"reference-count":100,"publisher":"Springer Science and Business Media LLC","issue":"1","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2011,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>Intrinsically disordered proteins play important roles in various cellular activities and their prevalence was implicated in a number of human diseases. The knowledge of the content of the intrinsic disorder in proteins is useful for a variety of studies including estimation of the abundance of disorder in protein families, classes, and complete proteomes, and for the analysis of disorder-related protein functions. The above investigations currently utilize the disorder content derived from the per-residue disorder predictions. We show that these predictions may over-or under-predict the overall amount of disorder, which motivates development of novel tools for direct and accurate sequence-based prediction of the disorder content.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>We hypothesize that sequence-level aggregation of input information may provide more accurate content prediction when compared with the content extracted from the local window-based residue-level disorder predictors. We propose a novel predictor, DisCon, that takes advantage of a small set of 29 custom-designed descriptors that aggregate and hybridize information concerning sequence, evolutionary profiles, and predicted secondary structure, solvent accessibility, flexibility, and annotation of globular domains. Using these descriptors and a ridge regression model, DisCon predicts the content with low, 0.05, mean squared error and high, 0.68, Pearson correlation. This is a statistically significant improvement over the content computed from outputs of ten modern disorder predictors on a test dataset with proteins that share low sequence identity with the training sequences. The proposed predictive model is analyzed to discuss factors related to the prediction of the disorder content.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>DisCon is a high-quality alternative for high-throughput annotation of the disorder content. We also empirically demonstrate that the DisCon's predictions can be used to improve binary annotations of the disordered residues from the real-value disorder propensities generated by current residue-level disorder predictors. The web server that implements the DisCon is available at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"http:\/\/biomine.ece.ualberta.ca\/DisCon\/\" ext-link-type=\"uri\">http:\/\/biomine.ece.ualberta.ca\/DisCon\/<\/jats:ext-link>.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-12-245","type":"journal-article","created":{"date-parts":[[2011,6,18]],"date-time":"2011-06-18T06:20:08Z","timestamp":1308378008000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["In-silico prediction of disorder content using hybrid sequence representation"],"prefix":"10.1186","volume":"12","author":[{"given":"Marcin J","family":"Mizianty","sequence":"first","affiliation":[]},{"given":"Tuo","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Bin","family":"Xue","sequence":"additional","affiliation":[]},{"given":"Yaoqi","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"A Keith","family":"Dunker","sequence":"additional","affiliation":[]},{"given":"Vladimir N","family":"Uversky","sequence":"additional","affiliation":[]},{"given":"Lukasz","family":"Kurgan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2011,6,17]]},"reference":[{"issue":"Suppl 2","key":"4635_CR1","doi-asserted-by":"publisher","first-page":"S1","DOI":"10.1186\/1471-2164-9-S2-S1","volume":"9","author":"AK Dunker","year":"2008","unstructured":"Dunker AK, Oldfield CJ, Meng J, Romero P, Yang JY, Chen JW, Vacic V, Obradovic Z, Uversky V: The unfoldomics decade: an update on intrinsically disordered proteins. 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