Biomedical subjects

Tim J Hutton

Publications and source records attributed to Tim J Hutton.

5 recordsLinked to original sources

PubMed2007

Evolvable self-reproducing cells in a two-dimensional artificial chemistry.

We present a novel unit of evolution: a self-reproducing cell in a two-dimensional artificial chemistry. The cells have a strip of genetic material that is used to produce enzymes, each catalyzing a specific reaction that may affect the survival of the cell. The enzymes are kept inside the cell by a loop of membrane, thus ensuring that only the cell that produced them gets their benefit. A set of reaction rules, each simple and local, allows the cells to copy their genetic information and physically divide. The evolutionary possibilities of the cells are explored, and it is suggested that the system provides a useful framework for testing hypotheses about self-driven evolution.

Biological Evolution↗

PubMed2005

Discriminating power of localized three-dimensional facial morphology.

Many genetic syndromes involve a facial gestalt that suggests a preliminary diagnosis to an experienced clinical geneticist even before a clinical examination and genotyping are undertaken. Previously, using visualization and pattern recognition, we showed that dense surface models (DSMs) of full face shape characterize facial dysmorphology in Noonan and in 22q11 deletion syndromes. In this much larger study of 696 individuals, we extend the use of DSMs of the full face to establish accurate discrimination between controls and individuals with Williams, Smith-Magenis, 22q11 deletion, or Noonan syndromes and between individuals with different syndromes in these groups. However, the full power of the DSM approach is demonstrated by the comparable discriminating abilities of localized facial features, such as periorbital, perinasal, and perioral patches, and the correlation of DSM-based predictions and molecular findings. This study demonstrates the potential of face shape models to assist clinical training through visualization, to support clinical diagnosis of affected individuals through pattern recognition, and to enable the objective comparison of individuals sharing other phenotypic or genotypic properties.

Adult↗

PubMed2004

3D analysis of facial morphology.

Dense surface models can be used to analyze 3D facial morphology by establishing a correspondence of thousands of points across each 3D face image. The models provide dramatic visualizations of 3D face-shape variation with potential for training physicians to recognize the key components of particular syndromes. We demonstrate their use to visualize and recognize shape differences in a collection of 3D face images that includes 280 controls (2 weeks to 56 years of age), 90 individuals with Noonan syndrome (NS) (7 months to 56 years), and 60 individuals with velo-cardio-facial syndrome (VCFS; 3 to 17 years of age). Ten-fold cross-validation testing of discrimination between the three groups was carried out on unseen test examples using five pattern recognition algorithms (nearest mean, C5.0 decision trees, neural networks, logistic regression, and support vector machines). For discriminating between individuals with NS and controls, the best average sensitivity and specificity levels were 92 and 93% for children, 83 and 94% for adults, and 88 and 94% for the children and adults combined. For individuals with VCFS and controls, the best results were 83 and 92%. In a comparison of individuals with NS and individuals with VCFS, a correct identification rate of 95% was achieved for both syndromes. This article contains supplementary material, which may be viewed at the American Journal of Medical Genetics website at http://www.interscience.wiley.com/jpages/0148-7299/suppmat/index.html.

Abnormalities, Multiple↗

PubMed2003

Estimating average growth trajectories in shape-space using kernel smoothing.

In this paper, we show how a dense surface point distribution model of the human face can be computed and demonstrate the usefulness of the high-dimensional shape-space for expressing the shape changes associated with growth and aging. We show how average growth trajectories for the human face can be computed in the absence of longitudinal data by using kernel smoothing across a population. A training set of three-dimensional surface scans of 199 male and 201 female subjects of between 0 and 50 years of age is used to build the model.

Adolescent↗

PubMed2002

Evolvable self-replicating molecules in an artificial chemistry.

This paper gives details of Squirm3, a new artificial environment based on a simple physics and chemistry that supports self-replicating molecules somewhat similar to DNA. The self-replicators emerge spontaneously from a random soup given the right conditions. Interactions between the replicators can result in mutated versions that can outperform their parents. We show how artificial chemistries such as this one can be implemented as a cellular automaton. We concur with Dittrich, Ziegler, and Banzhaf that artificial chemistries are a good medium in which to study early evolution.

Biological Evolution↗