Biomedical subjects

Shing-Chung Ngan

Publications and source records attributed to Shing-Chung Ngan.

4 recordsLinked to original sources

PubMed2006

A knowledge-based scoring function based on residue triplets for protein structure prediction.

One of the general paradigms for ab initio protein structure prediction involves sampling the conformational space such that a large set of decoy (candidate) structures are generated and then selecting native-like conformations from those decoys using various scoring functions. In this study, based on a physical/geometric approach first suggested by Banavar and colleagues, we formulate a knowledge-based scoring function, which uses the radii of curvature formed among triplets of residues in a protein conformation. By analyzing its performance on various decoy sets, we determine a good set of parameters--the distance cutoff and the number of distance bins--to use for configuring such a function. Furthermore, we investigate the effect of using various approaches for compiling the prior distribution on the performance of the knowledge-based function. Possible extensions to the current form of the residue triplet scoring function are discussed.

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PubMed2005

PROTINFO: new algorithms for enhanced protein structure predictions.

We describe new algorithms and modules for protein structure prediction available as part of the PROTINFO web server. The modules, comparative and de novo modelling, have significantly improved back-end algorithms that were rigorously evaluated at the sixth meeting on the Critical Assessment of Protein Structure Prediction methods. We were one of four server groups invited to make an oral presentation (only the best performing groups are asked to do so). These two modules allow a user to submit a protein sequence and return atomic coordinates representing the tertiary structure of that protein. The PROTINFO server is available at http://protinfo.compbio.washington.edu.

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PubMed2002

Functional magnetic resonance imaging of the retina.

PURPOSE: This study explored the feasibility of mapping the retina's responses to visual stimuli noninvasively, by using functional magnetic resonance imaging (fMRI). METHODS: fMRI was performed on a 9.4-Tesla scanner to map activity-evoked signal changes of the retina-choroid complex associated with visual stimulation in anesthetized cats (n = 6). Three to 12 1-mm slices were acquired in a single shot using inversion-recovery, echo-planar imaging with a nominal in-plane resolution of 468 x 468 microm(2). Visual stimuli were presented to the full visual field and to the upper and lower visual fields. The stimuli were drifting or stationary gratings, which were compared with the dark condition. Activation maps were computed using cross-correlation analysis and overlaid on anatomic images. Multislice activation maps were reconstructed and flattened onto a two-dimensional surface. RESULTS: fMRI activation maps showed robust increased activity in the retina-choroid complex after visual stimulation. The average stimulus-evoked fMRI signal increase associated with drifting-grating stimulus was 1.7% +/- 0.5% (P < 10(-4), n = 6) compared with dark. Multislice functional images of the retina flattened onto a two-dimensional surface showed relatively uniform activation. No statistically significant activation was observed in and around the optic nerve head. Hemifield stimulation studies demonstrated that stimuli presented to the upper half of the visual field activated the lower part of the retina, and stimuli presented to the lower half of the visual field activated the upper part of the retina, as expected. Signal changes evoked by the stationary gratings compared with the dark basal condition were positive but were approximately half that evoked by the drifting gratings (1.0% +/- 0.1% versus 2.1% +/- 0.3%, P < 10(-4)). CONCLUSIONS: To the best of our knowledge, this is the first fMRI study of the retina, demonstrating its feasibility in imaging retinal function dynamically in a noninvasive manner and at relatively high spatial resolution.

Animals↗

PubMed2002

Cluster significance testing using the bootstrap.

Many of the statistical methods currently employed to analyze fMRI data depend on a response template. However, the true form of the hemodynamic response, and thereby the response template, is often unknown. Consequently, cluster analysis provides a complementary, template-free method for exploratory analysis of multidimensional fMRI data sets. Clustering algorithms currently being applied to fMRI data separate the data into a predefined number of clusters (k). A poor choice of k will result in erroneously partitioning well-defined clusters. Although several clustering algorithms have been successfully applied to fMRI data, techniques for statistically testing cluster separation are still lacking. To address this problem we suggest a method based on Fisher's linear discriminant and the bootstrap. Also introduced in this paper is a measure based on the projection of multidimensional data from two clusters onto the vector, maximizing the ratio of the between- to the within-cluster sums of squares. The resulting one-dimensional distribution may be readily visualized and used as a heuristic for estimating cluster homogeneity. These methods are demonstrated for the self-organizing maps clustering algorithm when applied to event-related fMRI data.

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