Biomedical subjects

D Meads

Publications and source records attributed to D Meads.

3 recordsLinked to original sources

PubMed1999

Protalign: a 3-dimensional protein alignment assessment tool.

Protein fold recognition (sometimes called threading) is the prediction of a protein's 3-dimensional shape based on its similarity to a protein of known structure. Fold predictions are low resolution; that is, no effort is made to rotate the protein's component amino acid side chains into their correct spatial orientations. The goal is simply to recognize the protein family member that most closely resembles the target sequence of unknown structure and to create a sensible alignment of the target to the known structure (i.e., a structure-sequence alignment). To facilitate this type of structure prediction, we have designed a low resolution molecular graphics tool. ProtAlign introduces the ability to interact with and edit alignments directly in the 3-dimensional structure as well as in the usual 2-dimensional layout. It also contains several functions and features to help the user assess areas within the alignment. ProtAlign implements an open pipe architecture to allow other programs to access its molecular graphics capabilities. In addition, it is capable of "driving" other programs. Because amino acid side chain orientation is not relevant in fold recognition, we represent amino acid residues as abstract shapes or glyphs much like Lego (tm) blocks and we borrow techniques from comparative flow visualization using streamlines to provide clean depictions of the entire protein model. By creating a low resolution representation of protein structure, we are able to at least double the amount of information on the screen. At the same time, we create a view that is not as busy as the corresponding representations using traditional high resolution visualization methods which show detailed atomic structure. This eliminates distracting and possibly misleading visual clutter resulting from the mapping of protein alignment information onto a high resolution display of the known structure. This molecular graphics program is implemented in Open GL to facilitate porting to other platforms.

Amino Acid Sequence↗

PubMed1999

PROMUSE: a system for multi-media data presentation of protein structural alignments.

We present and evaluate PROMUSE: an integrated visualization/sonification system for analyzing pairwise protein structural alignments (superpositions of two protein structures in three-dimensional space). We also explore how the use of sound can enhance the perception and recognition of specific aspects of the local environment at given positions in the represented molecular structure. Sonification presents several opportunities to researchers. For those with visual impairment, data sonification can be a useful alternative to visualization. Sonification can further serve to improve understanding of information in several ways. One use for data sonification is in tasks such as background monitoring, in which case sounds can be used to indicate thresholding events. With PROMUSE, data represented visually may be enhanced or disambiguated by adding sound to the presentation. This aspect of data representation is particularly important for showing features that are difficult to represent visually, due to occlusion or other factors. Another feature of our system is that by representing some variables through sound and others visually, the amount of information that may be represented simultaneously is extended. Our tool aims to augment the power of data visualization rather than replace it. To maximize the utility of our sonifications to represent data, we employed musical voices and melodic components with unique characteristics. We also used sound effects such as panning a voice to the left or right speaker and changing its volume to maximize the individuality of the sonification elements. By making the sonification parameters distinct, we allow the user to focus on those portions of the sonification necessary to resolve possible ambiguities in the visual display. Sonifications of low level data such as raw protein or DNA sequences tend to sound random, and not very musical. We chose instead to sonify an analysis of data features, and thereby present a higher level view of the data. We also used brief melodic phrases rather than single notes in order to generate sounds that were more pleasing and musically idiomatic. To validate the utility of our system, we present the results of an experiment in which PROMUSE was used to test the use of sound as an aid for clarifying visual information. We also compare the overall effectiveness of visual versus aural information delivery.

Computer Graphics↗

PubMed1993

In vitro validation of color velocity imaging and spectral Doppler for velocity determination.

Color velocity imaging (CVI) is a new non-Doppler ultrasound technique for vascular color flow imaging. Using information contained in the two-dimensional B-mode, gray-scale image to determine velocity, CVI offers potential advantages over Doppler color flow imaging methods. In order to be used clinically, velocity determination with CVI must be validated by other current methods. A Doppler string phantom was studied with a Philips CVI ultrasound system. Velocity measurements were obtained by both CVI and duplex Doppler spectral analysis for constant string speeds from 10 to 200 cm/sec, at intervals of 10 cm/sec. Twenty separate estimates were obtained with each method, at each string speed. Linear regression assessed the relationship between estimated and actual string velocities, with CVI and spectral Doppler analysis yielding highly valid results (CVI = -0.713 + 1.000997 x phantom; r 2 = 0.9979). At all string speeds tested, the averaged estimated and the actual velocities for both methods were within the 95% confidence estimates. The range for the CVI 95% confidence limits from the regression line varied from +/-1.07 cm/sec at the lowest speed of 10 cm/sec (11.6%) to +/-7.72 cm/sec at 200 cm/sec (3.87%). Based on in vitro testing, CVI is as accurate as Doppler spectral analysis for the estimation of flow velocity.

Blood Flow Velocity↗