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Online 1. Bayesian approaches to building models for biological systems [2018]
 Shi, Jiakun, author.
 [Stanford, California] : [Stanford University], 2018.
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 Book — 1 online resource.
 Summary

Understanding the structure and dynamics of biological macromolecules is a central focus of biological research. To be able to study and gain insights into these systems, it is first necessary to have an accurate and informative model for the system of interest. However, such a model is often difficult to build. For example, during protein folding, many proteins collapse into transient kinetic intermediates on timescales too fast for highresolution experimental techniques to detect, preventing structural characterization of these species. Alternatively, current algorithms for RNA design (i.e. predicting a sequence that folds into a desired target structure) cannot accurately model structuresequence relationships and rely primarily on brute force stochastic search, leading to poor performance on complex targets. Here, we show that it is possible to improve the quality of models for biological systems by applying a common Bayesian approach to building them, i.e. incorporating prior information to impose informative constraints on the model parameters. Through this approach, it is possible to build highresolution models of protein dynamics given limited experimental data, as well as a stateoftheart computational RNA design agent that outperforms all currently existing algorithms.
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Online 2. Challenges, solutions, and biological applications of threedimensional nanoscale spatial localization of single molecules [electronic resource] [2015]
 Backlund, Mikael P.
 2015.
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 Book — 1 online resource.
 Summary

Single fluorescent molecules and particles can be localized in space with precision on the order of tens of nanometers (i.e. "super localized") using stateoftheart microscopy techniques. The ability to probe complex environments at the subdiffraction size scale has proven invaluable in revealing fundamental heterogeneity and improving overall understanding across the applied physical sciences. Superlocalization microscopy is at the heart of both singlemolecule superresolution microscopy and singleparticle tracking. The work presented in this dissertation concerns the application of superlocalization microscopy to problems of biophysical interest, as well as theoretical and experimental advances in the methodology of this class of techniques. While the most common methods of superlocalized position estimation ensure high localization precision, they might not always ensure high accuracy. In particular, the anisotropy of singlemolecule dipole emission can result in mislocalizations of hundreds of nanometers, depending on the orientation of the molecule and its distance from the focal plane. In this dissertation I discuss different ways to correct this potential source of error. On the one hand, a theory based on a wobblinginacone model is presented that shows how this error is mitigated by molecular rotational mobility. On the other hand, for the worstcase scenario of a rotationally fixed emitter, an experimental approach based on Fourier optics is also discussed that allows for estimation of molecular orientation and enables active correction of mislocalization effects. The last third of this dissertation discusses applications of superlocalization microscopy to threedimensional tracking of fluorescently labeled genetic loci in budding yeast. In order to localize loci in the axial dimension, I used a Fourier optics approach to engineer the point spread function of the microscope into a DoubleHelix Point Spread Function (DHPSF). With this method, many single copies of a specific locus were analyzed, each with 3D spatial precision on the order of 10 nm at a rate of 10 Hz. A twocolor implementation of the microscope allowed measurement of the correlations of 3D motion between pairs of loci under variable transcriptional pressure. I also discuss the importance of properly accounting for the inescapable effects of static and dynamic tracking errors caused by finite photon statistics and motion blur, respectively. These errors affect the statistics of the estimated motion and distort common metrics for characterizing stochastic motion such as the meansquared displacement (MSD) and velocity autocorrelation (VAC). Analytical expressions for the MSD and VAC in the presence of these errors are given, along with applications to chromosomal locus tracking.
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3781 2015 B  Inlibrary use 
 Wong, Daryl Brian.
 2013.
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 Book — 1 online resource.
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The dynamic structure of water and its hydrogen bond network are important in nature. Water molecules make highly directed hydrogen bonds that allow it to form extended hydrogen bond networks in the bulk. In this extended network, water's directional hydrogen bonds are readily fluctuating and exchanging. When interacting with molecules other than itself, water behaves differently than what is observed in the bulk. The dynamics of water molecules in a heterogeneous environment is dictated in large part by the size and hydrogen bonding nature of the interacting nonwater species. While water still forms directed hydrogen bonds in heterogeneous environments, the dynamics of the water molecules are altered by disruption of water's extended hydrogen bond network. The studies described herein are concerned with how water's orientational and structural dynamics change as it interacts with nonwater species in solution which has relevance to chemical and biological systems. Ultrafast infrared spectroscopic techniques are used to examine water and its hydrogen bonding network. These methods interrogate molecular systems with femtosecond infrared pulses which can probe the dynamics of water molecules (100s of fs to ps) on the time scale with which they move. Changes in local molecular structure can be monitored by observing changes in vibrational frequency. The stretching mode of deuterated hydroxyl (OD) groups serves as the vibrational probe for the experiments. In these studies, both twodimensional infrared vibrational echo (2D IR) spectroscopy and polarization selective pumpprobe spectroscopy are employed to monitor the dynamics of water molecules in nonaqueous environments. The pumpprobe experiments provide information on both the vibrational lifetime and orientational relaxation of water molecules within the sample. 2D IR experiments characterize the spectral diffusion of the vibrational mode through the frequencyfrequency correlation function (FFCF) which monitors the structural evolution of water's hydrogen bonds. The dynamics of water in two systems are discussed in this thesis. The first study examines the dynamics of dimethyl sulfoxide (DMSO)/water solutions over a wide range of water concentrations. Both linear IR absorption spectra and vibrational population relaxation studies show that waterwater and waterDMSO interactions are present, even at very low water concentration. Though water forms multiple hydrogen bonding partners, observation of a single ensemble anisotropy indicates the concerted reorientation between water and DMSO molecules in solution. In addition to OHDOKE experiments, which track the orientational relaxation timescales to be similar to that of water suggests that the reorientation of water is coupled to that of the DMSO molecules in solution. Interpretation of FFCF measurements from the 2D IR experiment shows fast, local hydrogen bond fluctuations and slower longer structural fluctuations associated with global hydrogen bond rearrangement. In the second system, the vibrational dynamics of spatially isolated water molecules were examined in the room temperature ionic liquid (RTIL) 1butyl3methylimidazolium hexafluorophosphate (BmImPF6). The antisymmetric and symmetric modes of D2O are well resolved, which is unusual for the condensed phase. The spectral separation of the two peaks make it possible to study the inter and intramolecular dynamics of a vibrationally excited water molecule. Examination of the intramolecular dynamics focused mainly on the redistribution of vibrational energy throughout the water molecule. Both population exchange between vibrational modes and excitedstate relaxation were monitored to determine the timescales vibrational energy exchange and relaxation. In addition, coherent quantum beats were observed in short time amplitude and frequency correlation trajectories. Oscillations in the crosspeak shape, from highly correlated to slightly anticorrelated, show that coherent transfer of energy between the two modes occurs in a slightly anticorrelated fashion. The slight anticorrelation can be explained by a distribution in the coupling strength between the local hydroxyl modes. The water's dynamics as influenced by the surrounding salt molecules was examined using both FFCF of the crosspeak shape as well as the orientational relaxation. Timescales for orientational relaxation and structural rearrangements of the isolated water molecules within solution were determined.
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Online 4. A Bayesian method for construction of Markov models to describe dynamics on various time scales [electronic resource] [2011]
 Rains, Emily Kathleen.
 2010, c2011.
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 Book — 1 online resource.
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The dynamics of many biological processes of interest, such as the folding of a protein, are slow and complicated enough that a single molecular dynamics simulation trajectory of the entire process is difficult to obtain in any reasonable amount of time. Moreover, one such simulation may not be sufficient to develop an understanding of the mechanism of the process, and multiple simulations may be necessary. One approach to circumvent this computational barrier is the use of Markov state models. These models are useful because they can be constructed using data from a large number of shorter simulations instead of a single long simulation. This thesis presents a new Bayesian method for the construction of Markov models from simulation data. A Markov model is specified by (t, P, T), where t is the mesoscopic time step, P is a partition of configuration space into mesostates, and T is an N x N transition rate matrix for transitions between the mesostates in one mesoscopic time step, where N is the number of mesostates in P. The method presented here is different from previous Bayesian methods in several ways. 1. The method uses Bayesian analysis to determine the partition as well as the transition probabilities. 2. The method allows the construction of a Markov model for any chosen mesoscopic time scale t. 3. It constructs Markov models for which the diagonal elements of T are all equal to or greater than 0.5. Such a model will be called a 'consistent mesoscopic Markov model' (or CMMM). Such models have important advantages for providing an understanding of the dynamics on a mesoscopic time scale. The Bayesian method uses simulation data to find a posterior probability distribution for (P, T) for any chosen t. This distribution can be regarded as the Bayesian probability that the kinetics observed in the atomistic simulation data on the mesoscopic time scale t was generated by the CMMM specified by (P, T). An optimization algorithm is used to find the most probable CMMM for the chosen mesoscopic time step. We applied this method of Markov model construction to several toy systems (random walks in one and two dimensions) as well as the dynamics of alanine dipeptide in water and of trpzip2 in water. The resulting Markov state models were indeed successful in capturing the dynamics of our test systems on a variety of mesoscopic time scales.
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3781 2010 R  Inlibrary use 
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