Uncertainty in integrative structural modeling

Dina Schneidman-Duhovny, Riccardo Pellarin, Andrej Sali

Research output: Contribution to journalReview articlepeer-review


Integrative structural modeling uses multiple types of input information and proceeds in four stages: (i) gathering information, (ii) designing model representation and converting information into a scoring function, (iii) sampling good-scoring models, and (iv) analyzing models and information. In the first stage, uncertainty originates from data that are sparse, noisy, ambiguous, or derived from heterogeneous samples. In the second stage, uncertainty can originate from a representation that is too coarse for the available information or a scoring function that does not accurately capture the information. In the third stage, the major source of uncertainty is insufficient sampling. In the fourth stage, clustering, cross-validation, and other methods are used to estimate the precision and accuracy of the models and information.

Original languageAmerican English
Pages (from-to)96-104
Number of pages9
JournalCurrent Opinion in Structural Biology
Issue number1
StatePublished - Oct 2014
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Structural Biology
  • Molecular Biology


Dive into the research topics of 'Uncertainty in integrative structural modeling'. Together they form a unique fingerprint.

Cite this