{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T14:18:16Z","timestamp":1774448296606,"version":"3.50.1"},"reference-count":57,"publisher":"Oxford University Press (OUP)","issue":"12","license":[{"start":{"date-parts":[[2009,6,30]],"date-time":"2009-06-30T00:00:00Z","timestamp":1246320000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009,6,30]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Inspection of protein\u2013protein interaction maps illustrates that a hub protein can interact with a very large number of proteins, reaching tens and even hundreds. Since a single protein cannot interact with such a large number of partners at the same time, this presents a challenge: can we figure out which interactions can occur simultaneously and which are mutually excluded? Addressing this question adds a fourth dimension into interaction maps: that of time. Including the time dimension in structural networks is an immense asset; time dimensionality transforms network node-and-edge maps into cellular processes, assisting in the comprehension of cellular pathways and their regulation. While the time dimensionality can be further enhanced by linking protein complexes to time series of mRNA expression data, current robust, network experimental data are lacking. Here we outline how, using structural data, efficient structural comparison algorithms and appropriate datasets and filters can assist in getting an insight into time dimensionality in interaction networks; in predicting which interactions can and cannot co-exist; and in obtaining concrete predictions consistent with experiment. As an example, we present p53-linked processes.<\/jats:p>\n                  <jats:p\/>","DOI":"10.1039\/b905661k","type":"journal-article","created":{"date-parts":[[2009,6,30]],"date-time":"2009-06-30T07:00:10Z","timestamp":1246345210000},"page":"1770-1778","source":"Crossref","is-referenced-by-count":71,"title":["Towards inferring time dimensionality in protein\u2013protein interaction networks by integrating structures: the p53 example"],"prefix":"10.1093","volume":"5","author":[{"given":"Nurcan","family":"Tuncbag","sequence":"first","affiliation":[{"name":"Koc University, Center for Computational Biology and Bioinformatics, and College of Engineering a , Rumelifeneri Yolu, 34450 Sariyer Istanbul Turkey agursoy@ku.edu.tr okeskin@ku.edu.tr"}]},{"given":"Gozde","family":"Kar","sequence":"additional","affiliation":[{"name":"Koc University, Center for Computational Biology and Bioinformatics, and College of Engineering a , Rumelifeneri Yolu, 34450 Sariyer Istanbul Turkey agursoy@ku.edu.tr okeskin@ku.edu.tr"}]},{"given":"Attila","family":"Gursoy","sequence":"additional","affiliation":[{"name":"Koc University, Center for Computational Biology and Bioinformatics, and College of Engineering a , Rumelifeneri Yolu, 34450 Sariyer Istanbul Turkey agursoy@ku.edu.tr okeskin@ku.edu.tr"}]},{"given":"Ozlem","family":"Keskin","sequence":"additional","affiliation":[{"name":"Koc University, Center for Computational Biology and Bioinformatics, and College of Engineering a , Rumelifeneri Yolu, 34450 Sariyer Istanbul Turkey agursoy@ku.edu.tr okeskin@ku.edu.tr"}]},{"given":"Ruth","family":"Nussinov","sequence":"additional","affiliation":[{"name":"Sackler Inst. of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler School of Medicine, Tel Aviv University c , Tel Aviv 69978, Israel"},{"name":"Basic Research Program, SAIC-Frederick, Inc., Center for Cancer Research Nanobiology Program b , NCI-Frederick, Frederick, MD 21702, USA ruthnu@helix.nih.gov"}]}],"member":"286","published-online":{"date-parts":[[2009,6,30]]},"reference":[{"issue":"1","key":"2026012914040041400_cit1","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.sbi.2005.01.012","article-title":"Protein complexes: structure prediction challenges for the 21st century","volume":"15","author":"Aloy","year":"2005","journal-title":"Curr. 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