{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/decoding-single-molecule-time-traces-with","title":"Decoding Single Molecule Time Traces with Dynamic Disorder","arxiv_id":"1612.04514","date":"2016-12-14","proceeding":null,"authors":[],"abstract":"Single molecule time trajectories of biomolecules provide glimpses into\ncomplex folding landscapes that are difficult to visualize using conventional\nensemble measurements. Recent experiments and theoretical analyses have\nhighlighted dynamic disorder in certain classes of biomolecules, whose dynamic\npattern of conformational transitions is affected by slower transition dynamics\nof internal state hidden in a low dimensional projection. A systematic means to\nanalyze such data is, however, currently not well developed. Here we report a\nnew algorithm - Variational Bayes-double chain Markov model (VB-DCMM) - to\nanalyze single molecule time trajectories that display dynamic disorder. The\nproposed analysis employing VB-DCMM allows us to detect the presence of dynamic\ndisorder, if any, in each trajectory, identify the number of internal states,\nand estimate transition rates between the internal states as well as the rates\nof conformational transition within each internal state. Applying VB-DCMM\nalgorithm to single molecule FRET data of H-DNA in 100 mM-Na$^+$ solution,\nfollowed by data clustering, we show that at least 6 kinetic paths linking 4\ndistinct internal states are required to correctly interpret the duplex-triplex\ntransitions of H-DNA.","url_abs":"http://arxiv.org/abs/1612.04514v1","url_pdf":"http://arxiv.org/pdf/1612.04514v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"decoding-single-molecule-time-traces-with","repo_url":"https://github.com/TBiophysG/VBDCMM","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}