Biomedical subjects

Stuart Aitken

Publications and source records attributed to Stuart Aitken.

5 recordsLinked to original sources

PubMed2006

Mining housekeeping genes with a Naive Bayes classifier.

BACKGROUND: Traditionally, housekeeping and tissue specific genes have been classified using direct assay of mRNA presence across different tissues, but these experiments are costly and the results not easy to compare and reproduce. RESULTS: In this work, a Naive Bayes classifier based only on physical and functional characteristics of genes already available in databases, like exon length and measures of chromatin compactness, has achieved a 97% success rate in classification of human housekeeping genes (93% for mouse and 90% for fruit fly). CONCLUSION: The newly obtained lists of housekeeping and tissue specific genes adhere to the expected functions and tissue expression patterns for the two classes. Overall, the classifier shows promise, and in the future additional attributes might be included to improve its discriminating power.

Animals↗

PubMed2005

Feature selection and classification for microarray data analysis: evolutionary methods for identifying predictive genes.

BACKGROUND: In the clinical context, samples assayed by microarray are often classified by cell line or tumour type and it is of interest to discover a set of genes that can be used as class predictors. The leukemia dataset of Golub et al. 1 and the NCI60 dataset of Ross et al. 2 present multiclass classification problems where three tumour types and nine cell lines respectively must be identified. We apply an evolutionary algorithm to identify the near-optimal set of predictive genes that classify the data. We also examine the initial gene selection step whereby the most informative genes are selected from the genes assayed. RESULTS: In the absence of feature selection, classification accuracy on the training data is typically good, but not replicated on the testing data. Gene selection using the RankGene software 3 is shown to significantly improve performance on the testing data. Further, we show that the choice of feature selection criteria can have a significant effect on accuracy. The evolutionary algorithm is shown to perform stably across the space of possible parameter settings - indicating the robustness of the approach. We assess performance using a low variance estimation technique, and present an analysis of the genes most often selected as predictors. CONCLUSION: The computational methods we have developed perform robustly and accurately, and yield results in accord with clinical knowledge: A Z-score analysis of the genes most frequently selected identifies genes known to discriminate AML and Pre-T ALL leukemia. This study also confirms that significantly different sets of genes are found to be most discriminatory as the sample classes are refined.

Algorithms↗

PubMed2005

Formalizing concepts of species, sex and developmental stage in anatomical ontologies.

MOTIVATION: Anatomy ontologies have a growing role in bioinformatics-for example, in indexing gene expression data in model organisms. To relate or draw conclusions from data so indexed, anatomy ontologies must be equipped with the formal vocabulary that would allow statements about meronomy to be qualified by constraints such as part of the male or part at the embryonic stage. Lacking such a vocabulary, anatomists have built this information into the structure of the ontology or into anatomical terms. For example, in the FlyBase anatomy for drosophila, the term larval abdominal segment encodes the stage in the term, while the terms male genital disc and female genital disc encode the sex. It remains implicit that a fly has one and only one of these parts during its larval stage. Such indicators of context can and should be represented explicitly in the ontology. RESULTS: The framework we have defined for anatomical ontologies allows the canonical anatomy structures of a given species to be those common to all sexes, and to have either male, female or hermaphrodite parts--but not combinations of the latter. Temporal aspects of development are addressed by associating a stage with organism parts and requiring a connected anatomy to have parts that exist at a common stage. Both sex and anatomical stage are represented by attributes. This formalization clarifies ontological structure and meaning and increases the capacity for formal reasoning about anatomy. The framework also supports generalizations such as vertebrate and invertebrate, thereby allowing the representation of anatomical structures that are common across a sub-phylum.

Anatomy↗

PubMed2004

COBrA: a bio-ontology editor.

COBrA is a Java-based ontology editor for bio-ontologies that distinguishes itself from other editors by supporting the linking of concepts between two ontologies, and providing sophisticated analysis and verification functions. In addition to the Gene Ontology and Open Biology Ontologies formats, COBrA can import and export ontologies in the Semantic Web formats RDF, RDFS and OWL.

Cell Physiological Phenomena↗

PubMedDate not supplied

The influence of pre-operative electrocardiographic abnormalities and cardiovascular risk factors on patient and graft survival following renal transplantation.

Premature cardiovascular disease (CVD) is the leading cause of mortality and of graft loss in renal transplant recipients. However, the pattern of cardiovascular risk factors (specifically modifiable risk factors) is not well established and may be different from the general population. In this study we investigated the importance of electrocardiographic abnormalities and conventional cardiovascular risk factors present at the time of first renal transplantation in a longitudinal follow-up study of 515 patients. Overall, 45.8% were cigarette smokers, 13.0% were diabetic, 75.1% had "hypertension", 12.2% had symptoms of angina pectoris and 9.1% had a past history of myocardial infarction or stroke. Two thirds of ECG tracings were abnormal. 58.7% of men and 37.5% of women had left ventricular hypertrophy (LVH). Overall, 28.2% had simple LVH, 20.5% had LVH with repolarisation changes ('strain'). 434 patients had complete data for multivariate analyses of patient and graft survival. A Cox multivariate analysis of patient survival (patients whose graft failed were censored in the analysis) identified: age (hazard ratio 1.03/year), diabetes (2.72), smoking (1.81) and family history of premature CVD (2.17) as independent risk factors for patient survival. An abnormal ECG was also independently associated with outcome, with the exception of isolated left ventricular hypertrophy. Left ventricular hypertrophy with strain, or ischaemic changes were associated with adverse outcome with a hazard ratio of 1.96 and 3.30 respectively. A similar analysis of the determinants of graft survival (patients who died with a functioning graft were censored in the analysis) identified: acute rejection (hazard ratio 2.38), cigarette smoking (1.48) and age (1.04/year) as independent predictors of graft failure. These data demonstrate a high prevalence of ECG abnormalities and CV risk factors in renal transplant recipients. Moreover, ECG abnormalities and "conventional" cardiovascular risk factors are associated with poor graft and patient outcome and represent potentially remediable risk factors for renal transplant recipients.

Adult↗