Biomedical subjects

Alfred O Hero

Publications and source records attributed to Alfred O Hero.

5 recordsLinked to original sources

PubMed2006

Convergent incremental optimization transfer algorithms: application to tomography.

No convergent ordered subsets (OS) type image reconstruction algorithms for transmission tomography have been proposed to date. In contrast, in emission tomography, there are two known families of convergent OS algorithms: methods that use relaxation parameters, and methods based on the incremental expectation-maximization (EM) approach. This paper generalizes the incremental EM approach by introducing a general framework, "incremental optimization transfer." The proposed algorithms accelerate convergence speeds and ensure global convergence without requiring relaxation parameters. The general optimization transfer framework allows the use of a very broad family of surrogate functions, enabling the development of new algorithms. This paper provides the first convergent OS-type algorithm for (nonconcave) penalized-likelihood (PL) transmission image reconstruction by using separable paraboloidal surrogates (SPS) which yield closed-form maximization steps. We found it is very effective to achieve fast convergence rates by starting with an OS algorithm with a large number of subsets and switching to the new "transmission incremental optimization transfer (TRIOT)" algorithm. Results show that TRIOT is faster in increasing the PL objective than nonincremental ordinary SPS and even OS-SPS yet is convergent.

Algorithms↗

PubMed2005

Network constrained clustering for gene microarray data.

UNLABELLED: Many bioinformatics problems can be tackled from a fresh angle offered by the network perspective. Directly inspired by metabolic network structural studies, we propose an improved gene clustering approach for inferring gene signaling pathways from gene microarray data. Based on the construction of co-expression networks that consists of both significantly linear and non-linear gene associations together with controlled biological and statistical significance, our approach tends to group functionally related genes into tight clusters despite their expression dissimilarities. We illustrate our approach and compare it to the traditional clustering approaches on a yeast galactose metabolism dataset and a retinal gene expression dataset. Our approach greatly outperforms the traditional approach in rediscovering the relatively well known galactose metabolism pathway in yeast and in clustering genes of the photoreceptor differentiation pathway. AVAILABILITY: The clustering method has been implemented in an R package "GeneNT" that is freely available from: http://www.cran.org.

Algorithms↗

PubMed2005

Least biased target selection in probabilistic atlas construction.

Probabilistic atlas has broad applications in medical image segmentation and registration. The most common problem building a probabilistic atlas is picking a target image upon which to map the rest of the training images. Here we present a method to choose a target image that is the closest to the mean geometry of the population under consideration as determined by bending energy. Our approach is based on forming a distance matrix based on bending energies of all pair-wise registrations and performing multidimensional scaling (MDS) on the distance matrix.

Algorithms↗

PubMed2005

High throughput screening of co-expressed gene pairs with controlled false discovery rate (FDR) and minimum acceptable strength (MAS).

Many exploratory microarray data analysis tools such as gene clustering and relevance networks rely on detecting pairwise gene co-expression. Traditional screening of pairwise co-expression either controls biological significance or statistical significance, but not both. The former approach does not provide stochastic error control, and the later approach screens many co-expressions with excessively low correlation. We have designed and implemented a statistically sound two-stage co-expression detection algorithm that controls both statistical significance (false discovery rate, FDR) and biological significance (minimum acceptable strength, MAS) of the discovered co-expressions. Based on estimation of pairwise gene correlation, the algorithm provides an initial co-expression discovery that controls only FDR, which is then followed by a second stage co-expression discovery which controls both FDR and MAS. It also computes and thresholds the set of FDR p-values for each correlation that satisfied the MAS criterion. Using simulated data, we validated asymptotic null distributions of the Pearson and Kendall correlation coefficients and the two-stage error-control procedure; we also compared our two-stage test procedure with another two-stage test procedure using the receiver operating characteristic (ROC) curve. We then used yeast galactose metabolism data to illustrate the advantage of our method for clustering genes and constructing a relevance network. The method has been implemented in an R package "GeneNT" that is freely available from the Comprehensive R Archive Network (CRAN): www.cran.r-project.org/.

Algorithms↗

PubMed2004

Expression profiling of the developing and mature Nrl-/- mouse retina: identification of retinal disease candidates and transcriptional regulatory targets of Nrl.

The rod photoreceptor-specific neural retina leucine zipper protein Nrl is essential for rod differentiation and plays a critical role in regulating gene expression. In the mouse retina, rods account for 97% of the photoreceptors; however, in the absence of Nrl (Nrl-/-), no rods are present and a concomitant increase in cones is observed. A functional all-cone mouse retina represents a unique opportunity to investigate, at the molecular level, differences between the two photoreceptor subtypes. Using mouse GeneChips (Affymetrix), we have generated expression profiles of the wild-type and Nrl-/- retina at three time-points representing distinct stages of photoreceptor differentiation. Comparative data analysis revealed 161 differentially expressed genes; of which, 78 exhibited significantly lower and 83 higher expression in the Nrl-/- retina. Hierarchical clustering was utilized to predict the function of these genes in a temporal context. The differentially expressed genes primarily encode proteins associated with signal transduction, transcriptional regulation, intracellular transport and other processes, which likely correspond to differences between rods and cones and/or retinal remodeling in the absence of rods. A significant number of these genes may serve as candidates for diseases involving rod or cone dysfunction. Chromatin immunoprecipitation assay showed that in addition to the rod phototransduction genes, Nrl might modulate the promoters of many functionally diverse genes in vivo. Our studies provide molecular insights into differences between rod and cone function, yield interesting candidates for retinal diseases and assist in identifying transcriptional regulatory targets of Nrl.

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