Publications by authors named "Alexander V Spirov"

Recent computational modeling of early fruit fly () development has characterized the degree to which gene regulation networks can be robust to natural variability. In the first few hours of development, broad spatial gradients of maternally derived transcription factors activate embryonic gap genes. These gap patterns determine the subsequent segmented insect body plan through pair-rule gene expression.

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Structurally and functionally isolated domains in biological macromolecular evolution, both natural and artificial, are largely similar to "schemata", building blocks (BBs), in evolutionary computation (EC). The problem of preserving in subsequent evolutionary searches the already found domains / BBs is well known and quite relevant in biology as well as in EC. Both biology and EC are seeing parallel and independent development of several approaches to identifying and preserving previously identified domains / BBs.

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Evolutionary computing (EC) is an area of computer sciences and applied mathematics covering heuristic optimization algorithms inspired by evolution in Nature. EC extensively study all the variety of methods which were originally based on the principles of selectionism. As a result, many new algorithms and approaches, significantly more efficient than classical selectionist schemes, were found.

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The Bicoid (Bcd) protein is a primary determinant of early anterior-posterior (AP) axis specification in Drosophila embryogenesis. This morphogen is spatially distributed in an anterior-high gradient, and affects particular AP cell fates in a concentration-dependent manner. The early distribution and dynamics of the bicoid (bcd) mRNA, the source for the Bcd protein gradient, is not well understood, leaving a number of open questions for how Bcd positional information develops and is regulated.

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The field of evolutionary algorithms (EAs) emerged in the area of computer science due to transfer of ideas from biology and developed independently for several decades, enriched with techniques from probability theory, complexity theory and optimization methods. In this paper, we consider some recent results form the EAs theory transferred back into biology. The well-known biotechnological procedure SELEX (Systematic Evolution of Ligands by EXponential enrichment) is viewed as an experimental implementation of an evolutionary algorithm.

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Anterior-posterior (AP) body segmentation of the fruit fly (Drosophila) is first seen in the 7-stripe spatial expression patterns of the pair-rule genes, which regulate downstream genes determining specific segment identities. Regulation of pair-rule expression has been extensively studied for the even-skipped (eve) gene. Recent live imaging, of a reporter for the 2nd eve stripe, has demonstrated the stochastic nature of this process, with 'bursts' in the number of RNA transcripts being made over time.

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Gene network simulations are increasingly used to quantify mutual gene regulation in biological tissues. These are generally based on linear interactions between single-entity regulatory and target genes. Biological genes, by contrast, commonly have multiple, partially independent, cis-regulatory modules (CRMs) for regulator binding, and can produce variant transcription and translation products.

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In early development, genes are expressed in spatial patterns which later define cellular identities and tissue locations. The mechanisms of such pattern formation have been studied extensively in early Drosophila (fruit fly) embryos. The gap gene hunchback (hb) is one of the earliest genes to be expressed in anterior-posterior (AP) body segmentation.

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Modern evolutionary computation utilizes heuristic optimizations based upon concepts borrowed from the Darwinian theory of natural selection. Their demonstrated efficacy has reawakened an interest in other aspects of contemporary biology as an inspiration for new algorithms. However, amongst the many excellent candidates for study, contemporary models of biological macroevolution attract special attention.

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Biological development depends on the coordinated expression of genes in time and space. Developmental genes have extensive cis-regulatory regions which control their expression. These regions are organized in a modular manner, with different modules controlling expression at different times and locations.

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A central question in evolutionary biology concerns the transition between discrete numbers of units (e.g. vertebrate digits, arthropod segments).

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Gene recruitment or cooption occurs when a gene, which may be part of an existing gene regulatory network (GRN), comes under the control of a new regulatory system. Such re-arrangement of pre-existing networks is likely more common for increasing genomic complexity than the creation of new genes. Using evolutionary computations (EC), we investigate how cooption affects the evolvability, outgrowth and robustness of GRNs.

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In Drosophila embryonic development, the Bicoid (Bcd) protein establishes positional information of downstream developmental genes like hunchback (hb), which has a strong anterior expression and a sharp on-off boundary in the mid-embryo. The role of Bcd cooperative binding in the positioning of the Hb pattern has been previously demonstrated. However, there are discrepancies in the reported results about the role of this mechanism in the sharp Hb border.

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In recent years the analysis of noise in gene expression has widely attracted the attention of experimentalists and theoreticians. Experimentally, the approaches based on in vivo fluorescent reporters in single cells appear to be straightforward and effective tools for bacteria and yeast. However, transferring these approaches to multicellular organisms presents many methodological problems.

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Positional information in developing embryos is specified by spatial gradients of transcriptional regulators. One of the classic systems for studying this is the activation of the hunchback (hb) gene in early fruit fly (Drosophila) segmentation by the maternally-derived gradient of the Bicoid (Bcd) protein. Gene regulation is subject to intrinsic noise which can produce variable expression.

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A new approach to design a dynamic model of genes with multiple autonomous regulatory modules by evolutionary computations is proposed. The approach is based on Genetic Algorithms (GA), with new crossover operators especially designed for these purposes. The new operators use local homology between parental strings to preserve building blocks found by the algorithm.

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Developing embryos exhibit a robust capability to reduce phenotypic variations that occur naturally or as a result of experimental manipulation. This reduction in variation occurs by an epigenetic mechanism called canalization, a phenomenon which has resisted understanding because of a lack of necessary molecular data and of appropriate gene regulation models. In recent years, quantitative gene expression data have become available for the segment determination process in the Drosophila blastoderm, revealing a specific instance of canalization.

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The variation in the expression patterns of the gap genes in the blastoderm of the fruit fly Drosophila melanogaster reduces over time as a result of cross regulation between these genes, a fact that we have demonstrated in an accompanying article in PLoS Biology (see Manu et al., doi:10.1371/journal.

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During embryonic development, the positional information provided by concentration gradients of maternal factors directs pattern formation by providing spatially dependent cues for gene expression. In the fruit fly, Drosophila melanogaster, a classic example of this is the sharp on-off activation of the hunchback (hb) gene at midembryo, in response to local concentrations of the smooth anterior-posterior Bicoid (Bcd) gradient. The regulatory region for hb contains multiple binding sites for the Bcd protein as well as multiple binding sites for the Hb protein.

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We analyze the relation between maternal gradients and segmentation in Drosophila, by quantifying spatial precision in protein patterns. Segmentation is first seen in the striped expression patterns of the pair-rule genes, such as even-skipped (eve). We compare positional precision between Eve and the maternal gradients of Bicoid (Bcd) and Caudal (Cad) proteins, showing that Eve position could be initially specified by the maternal protein concentrations but that these do not have the precision to specify the mature striped pattern of Eve.

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We quantify fluctuations in protein expression for three of the segmentation genes in the fruit fly, Drosophila melanogaster. These proteins are representative members of the first three levels of a signalling hierarchy which determines the segmented body plan: maternal (Bicoid protein); gap (Hunchback protein); and pair-rule (Even-skipped protein). We quantify both inter-embryo and inter-nucleus (within a single embryo) variability in expression, especially with respect to positional specification by concentration gradient reading.

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The HOX Pro database contains information about the organization, function and evolution of gene ensembles, notably the homeobox-containing genes. It is now clear that a subset of genes containing the homeobox motif play key roles in the orchestration of genes which control embryonic patterning, morphogenesis, cell differentiation and malignant transformation. The HOX Pro contains a broad spectrum of information including images, diagrams and animations.

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