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Despite the widespread application of microarray imaging for biomedical research, barriers still exist regarding its reliability and reproducibility for clinical use. A critical problem lies in accurate spot segmentation and quantification of gene expression level (mRNA) from microarray images. A variety of commercial and research freeware packages are available, but most cannot handle array spots...
Many genes and proteins are required to carry out the processes of innate and adaptive immunity. For many studies, including systems biology and evolutionary studies, it is necessary to have a clear and comprehensive definition of the immune system, including the genes and proteins that take part in immunological processes. We have identified and cataloged a large portion of the human immunology-related...
In this paper, we infer Boolean networks based on simulated data. Depending on the approach, the simulated data is either extracted from Boolean networks or from a biochemical network model. Noise was added using the existing hierarchical error model (HEM). We use Boolean inference algorithms based on best-fit to find the connections between nodes. In order to validate the inference processes, we...
This paper presents a simple way of predicting locations in protein sequences that are prone to disease-causing mutations. These locations are found with the help of outlier analysis of recurrence quantification analysis (RQA) applied to protein solvent accessibility measurements. The detected locations are related to the deterministic patterns of the protein sequences. These deterministic patterns...
Microarrays are powerful tools for simultaneous monitoring of the expression levels of large number of genes. Their analysis is usually achieved by using clustering techniques. In this paper, we present a new clustering method based on Linear Predictive Coding to provide enhanced microarray data analysis. In this approach, spectral analysis of microarray data is performed to classify samples according...
There is growing interest in using rank-ordered gene lists to avoid excessive dependence on measured gene expression levels, which can vary strongly across experiments, platforms, or analysis methods. As a useful tool for working with these lists, this paper describes two extensions of an ordered list comparison measure, recently proposed for comparing Internet search engines: the use of random permutations...
Gene network motifs are the recurring regulatory structural patterns in gene networks. For uncovering gene network motifs, we investigate a novel Bayesian approach based on the popular turbo algorithm. The motivation for using turbo algorithm is based on the subtle similarity between the network motifs detection and turbo decoding in communications. The proposed method has been tested on two types...
aCGH and expression profiling are two major high throughput genomic tools for functional genomics. Although each tool provides invaluable information, full exposition of disease initiation, progression, and manifestation requires synergistic integration of both measurements. In this paper, we will describe an approach to prioritize genomic regions or molecular signatures through the integration of...
A novel approach is presented to the detection of homological, eroded and latent periodicities in DNA sequences. Each symbol in a DNA sequence is assumed to be generated from an information source with an underlying probability mass function (pmf) in a cyclic manner. The number of sources can be interpreted as the periodicity of the sequence. The maximum likelihood estimates are developed for the...
The automated inference or prediction of protein-protein interaction networks from large-scale measurements and other genomic data has become a standard technique in systems biology. However, typically these networks only represent undirected interactions between proteins, without classifying the type and directionality of interactions. Regulatory interactions transmit signals and are activating or...
This article introduces a universal algorithm for creating compressed archives with instantaneous access and decodability of designated functional elements. A special-purpose variant is also given to enhance performance for DNA sequences. The resulting algorithm integrated into an earlier scheme achieves a marked improvement at the randomly accessible coding for annotated genome files, while completely...
In this paper we study the problem of jointly encoding the amino acid sequence and the secondary structure information of proteins, in the current format in which more and more proteins are stored in Swiss-Prot database. The new method, dubbed ProtCompSecS, combines the compressor ProtComp previously designed only for amino acid sequences, with a dictionary based method, where the dictionary containing...
Carbon balance is a common requirement in various mathematical modeling approaches which aim to model operation of a bioreactor. In this work, we study whether carbon balance is attained in a bioreactor which runs through various operational states. We conclude that carbon balance seems to be related to bioreactor stability. In the studied experimental data, carbon balance is closer during stable...
Among the main interests in many biological studies are the structure of gene regulatory network, and in particular differences in the regulatory interactions between different conditions. However, since the number of available samples is always very small and estimating the network structure is extremely hard, most current algorithms have to assume that the gene regulation does not change between...
The following topics are dealt with: genomic signal processing; genomic statistics; genetic regulatory networks; gene expression analysis; gene sequence detection.
In this work, firefly luciferase activities are studied to create a new model for the kinetics of the system. In the previous studies, the experimental and simulation results of light intensities generated from a firefly luciferin-luciferase system have not been identical. We show that small changes in the previous theoretical model allow a far better match to experimental results. In addition to...
This study evaluates parameter estimation methodology in the context of neuronal signaling networks. Based on the results of a previous study, four parameter estimation methods, Evolutionary Programming, Genetic Algorithm, Multistart, and Levenberg-Marquardt, are selected. All the reaction rate constants of the test case, the protein kinase C (PKC) pathway model, are estimated using the selected four...
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