Biomedical subjects

Yuting Jia

Publications and source records attributed to Yuting Jia.

3 recordsLinked to original sources

PubMed2005

Stochastic fluctuations in gene expression far from equilibrium: Omega expansion and linear noise approximation.

The Omega expansion of the master equation is used to investigate the intrinsic noise in an autoregulatory gene expression system. This Omega expansion provides a mesoscale description of the system and is used to analyze the effect of feedback regulation on intrinsic noise when the system state is far from equilibrium. Using the linear noise approximation, analytic results are obtained for a single gene system with linear feedback that is far from equilibrium. Additionally, analytic expressions are obtained for nonlinear systems near equilibrium. Simulations of such autoregulatory reaction schemes with nonlinear feedback show that during the approach to equilibrium the noise is not always reduced by the strength of the feedback. This is contrary to results seen in the equilibrium limit which show decreased noise with feedback strength. These results demonstrate that the behavior of linearized systems near equilibrium cannot be readily applied to systems far from equilibrium and highlight the need to explore nonequilibrium domains in mesoscopic systems.

Feedback, Physiological↗

PubMed2005

A random polymer model of the statistical significance of structure alignment.

A theory for assessing the statistical significance of structure alignment is developed using a random or Gaussian chain model. In this model, we consider the statistical distribution of the root mean square distance (rmsd) of the alignment between two random chains of equal length and common center of mass (referred to as Case 1). We demonstrate that the rmsd2 is distributed as a sum of independent Gamma variables. Analytic results on the mean and variance of the rmsd2 are presented. Since rmsd is strongly dependent on the length, we define the dimensionless quantity, reduced rmsd, as the rmsd divided by the radius of gyration. We find that the reduced rmsd can be accurately approximated by an extreme value distribution (EVD) that is independent of chain length and of bond length. The parameters of the EVD can be calculated from the mean and the variance of the rmsd2. We also consider the case of two chains with a common center of mass that are then rotated to minimize the rmsd (Case 2). In this case, the distribution of reduced rmsd can again be accurately approximated by an EVD, which is independent of the chain length and expected bond length. This distribution is used to calculate the p-value for a given reduced rmsd. Performing an analogous comparison for proteins, we find that approximately M(nu) and nu = 0.28 and 0.32 for Case 1 and Case 2, respectively, where M is the chain length. This result for Case 2 exactly matches with previous scaling results and suggests that rmsd/M(nu)is an appropriate metric for protein structure alignment and will be independent of chain length. We also find that the new score roughly follows the EVD.

Computer Simulation↗

PubMed2004

A new scoring function and associated statistical significance for structure alignment by CE.

A new scoring function for assessing the statistical significance of protein structure alignment has been developed. The new scores were tested empirically using the combinatorial extension (CE) algorithm. The significance of a given score was given a p-value by curve-fitting the distribution of the scores generated by a random comparison of proteins taken from the PDB_SELECT database and the structural classification of proteins (SCOP) database. Although the scoring function was developed based on the CE algorithm, it is portable to any other protein structure alignment algorithm. The new scoring function is examined by sensitivity, specificity, and ROC curves.

Algorithms↗