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Biomedical subjects

Terry Speed

Publications and source records attributed to Terry Speed.

8 recordsLinked to original sources
PubMed2006

A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes.

Recent studies suggest that thousands of genes may contribute to breast cancer pathophysiologies when deregulated by genomic or epigenomic events. Here, we describe a model "system" to appraise the functional contributions of these genes to breast cancer subsets. In general, the recurrent genomic and transcriptional characteristics of 51 breast cancer cell lines mirror those of 145 primary breast tumors, although some significant differences are documented. The cell lines that comprise the system also exhibit the substantial genomic, transcriptional, and biological heterogeneity found in primary tumors. We show, using Trastuzumab (Herceptin) monotherapy as an example, that the system can be used to identify molecular features that predict or indicate response to targeted therapies or other physiological perturbations.

Breast Neoplasms↗
PubMed2005

Colon cancer prognosis prediction by gene expression profiling.

This study assessed the possibility to build a prognosis predictor, based on microarray gene expression measures, in stage II and III colon cancer patients. Tumour (T) and non-neoplastic mucosa (NM) mRNA samples from 18 patients (nine with a recurrence, nine with no recurrence) were profiled using the Affymetrix HGU133A GeneChip. The k-nearest neighbour method was used for prognosis prediction using T and NM gene expression measures. Six-fold cross-validation was applied to select the number of neighbours and the number of informative genes to include in the predictors. Based on this information, one T-based and one NM-based predictor were proposed and their accuracies were estimated by double cross-validation. In six-fold cross-validation, the lowest numbers of informative genes giving the lowest numbers of false predictions (two out of 18) were 30 and 70 with the T and NM gene expression measures, respectively. A 30-gene T-based predictor and a 70-gene NM-based predictor were then built, with estimated accuracies of 78 and 83%, respectively. This study suggests that one can build an accurate prognosis predictor for stage II and III colon cancer patients, based on gene expression measures, and one can use either tumour or non-neoplastic mucosa for this purpose.

Adenocarcinoma↗
PubMed2005

Rooting a phylogenetic tree with nonreversible substitution models.

BACKGROUND: We compared two methods of rooting a phylogenetic tree: the stationary and the nonstationary substitution processes. These methods do not require an outgroup. METHODS: Given a multiple alignment and an unrooted tree, the maximum likelihood estimates of branch lengths and substitution parameters for each associated rooted tree are found; rooted trees are compared using their likelihood values. Site variation in substitution rates is handled by assigning sites into several classes before the analysis. RESULTS: In three test datasets where the trees are small and the roots are assumed known, the nonstationary process gets the correct estimate significantly more often, and fits data much better, than the stationary process. Both processes give biologically plausible root placements in a set of nine primate mitochondrial DNA sequences. CONCLUSIONS: The nonstationary process is simple to use and is much better than the stationary process at inferring the root. It could be useful for situations where an outgroup is unavailable.

Animals↗
PubMed2003

Normalization of cDNA microarray data.

Normalization means to adjust microarray data for effects which arise from variation in the technology rather than from biological differences between the RNA samples or between the printed probes. This paper describes normalization methods based on the fact that dye balance typically varies with spot intensity and with spatial position on the array. Print-tip loess normalization provides a well-tested general purpose normalization method which has given good results on a wide range of arrays. The method may be refined by using quality weights for individual spots. The method is best combined with diagnostic plots of the data which display the spatial and intensity trends. When diagnostic plots show that biases still remain in the data after normalization, further normalization steps such as plate-order normalization or scale-normalization between the arrays may be undertaken. Composite normalization may be used when control spots are available which are known to be not differentially expressed. Variations on loess normalization include global loess normalization and two-dimensional normalization. Detailed commands are given to implement the normalization techniques using freely available software.

DNA, Complementary↗
PubMed2002

An HMM model for coiled-coil domains and a comparison with PSSM-based predictions.

MOTIVATION: Large-scale sequence data require methods for the automated annotation of protein domains. Many of the predictive methods are based either on a Position Specific Scoring Matrix (PSSM) of fixed length or on a window-less Hidden Markov Model (HMM). The performance of the two approaches is tested for Coiled-Coil Domains (CCDs). The prediction of CCDs is used frequently, and its optimization seems worthwhile. RESULTS: We have conceived MARCOIL, an HMM for the recognition of proteins with a CCD on a genomic scale. A cross-validated study suggests that MARCOIL improves predictions compared to the traditional PSSM algorithm, especially for some protein families and for short CCDs. The study was designed to reveal differences inherent in the two methods. Potential confounding factors such as differences in the dimension of parameter space and in the parameter values were avoided by using the same amino acid propensities and by keeping the transition probabilities of the HMM constant during cross-validation. AVAILABILTY: The prediction program and the databases are available at http://www.wehi.edu.au/bioweb/Mauro/Marcoil

Algorithms↗
PubMed2002

Genes for glycosylphosphatidylinositol toxin biosynthesis in Plasmodium falciparum.

About 2.5 million people die of Plasmodium falciparum malaria every year. Fatalities are associated with systemic and organ-specific inflammation initiated by a parasite toxin. Recent studies show that glycosylphosphatidylinositol (GPI) functions as the dominant parasite toxin in the context of infection. GPIs also serve as membrane anchors for several of the most important surface antigens of parasite invasive stages. GPI anchoring is a complex posttranslational modification produced through the coordinated action of a multicomponent biosynthetic pathway. Here we present eight new genes of P. falciparum selected for encoding homologs of proteins essential for GPI synthesis: PIG-A, PIG-B, PIG-M, PIG-O, GPI1, GPI8, GAA-1, and DPM1. We describe the experimentally verified mRNA and predicted amino acid sequences and in situ localization of the gene products to the parasite endoplasmic reticulum. Moreover, we show preliminary evidence for the PIG-L and PIG-C genes. The biosynthetic pathway of the malaria parasite GPI offers potential targets for drug development and may be useful for studying parasite cell biology and the molecular basis for the pathophysiology of parasitic diseases.

Acetylation↗