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Bioessays,
2008]
Predicting the phenotype of an organism from its genotype is a central question in genetics. Most importantly, we would like to find out if the perturbation of a single gene may be the cause of a disease. However, our current ability to predict the phenotypic effects of perturbations of individual genes is limited. Network models of genes are one tool for tackling this problem. In a recent study, (Lee et al.) it has been shown that network models covering the majority of genes of an organism can be used for accurately predicting phenotypic effects of gene perturbations in multicellular organisms. BioEssays 30:707-710, 2008. (c) 2008 Wiley Periodicals, Inc.
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Biochim Biophys Acta,
2017]
The development of new microscopy techniques for super-resolved, long-term monitoring of cellular and subcellular dynamics in living organisms is revealing new fundamental aspects of tissue development and repair. However, new microscopy approaches present several challenges. In addition to unprecedented requirements for data storage, the analysis of high resolution, time-lapse images is too complex to be done manually. Machine learning techniques are ideally suited for the (semi-)automated analysis of multidimensional image data. In particular, support vector machines (SVMs), have emerged as an efficient method to analyze microscopy images obtained from animals. Here, we discuss the use of SVMs to analyze in vivo microscopy data. We introduce the mathematical framework behind SVMs, and we describe the metrics used by SVMs and other machine learning approaches to classify image data. We discuss the influence of different SVM parameters in the context of an algorithm for cell segmentation and tracking. Finally, we describe how the application of SVMs has been critical to study protein localization in yeast screens, for lineage tracing in C. elegans, or to determine the developmental stage of Drosophila embryos to investigate gene expression dynamics. We propose that SVMs will become central tools in the analysis of the complex image data that novel microscopy modalities have made possible. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.
[
1980]
A number of review articles on the nematode cuticle have been published in the last decade. The most recent of these are those of Bird and Lee and Atkinson. These authors, while emphasizing the complexity and variability of nematode cuticles, support the use of a simplified nomenclature of cuticle structure which divides the cuticle into three regions or zones-namely, cortical, median, and basal. It is obvious that many exceptions to this fundamental pattern occur, and I shall mention some of these below. However, I think that they are adaptations to survival in changing environments, particularly where parasitism is involved. In particular, I propose to consider the structure and functions of the surface or epicuticle of the cortical zone, for it is here that reactions similar to those occurring at cell surfaces and in cell membranes are thought to occur in a wide range of "helminth" organisms. At the moment, particularly for the Nematoda, these ideas require more experimental evidence to establish them as facts. However, the use of sensitive techniques currently employed by membrane physicists and chemists to isolate, label, analyze, measure, and observe interactions taking place in cell membranes have in many instances yet to be used on the nematode cuticle. There is no doubt that the free-living bacterial-feeding nematodes such as those belonging to the genus Caenorhabditis, and in particular C. elegans, are the experimental models of choice for this purpose.
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Crit Rev Biochem Mol Biol,
2012]
The CCAAT box promoter element and NF-Y, the transcription factor (TF) that binds to it, were among the first cis-elements and trans-acting factors identified; their interplay is required for transcriptional activation of a sizeable number of eukaryotic genes. NF-Y consists of three evolutionarily conserved subunits: a dimer of NF-YB and NF-YC which closely resembles a histone, and the "innovative" NF-YA. In this review, we will provide an update on the functional and biological features that make NF-Y a fundamental link between chromatin and transcription. The last 25 years have witnessed a spectacular increase in our knowledge of how genes are regulated: from the identification of cis-acting sequences in promoters and enhancers, and the biochemical characterization of the corresponding TFs, to the merging of chromatin studies with the investigation of enzymatic machines that regulate epigenetic states. Originally identified and studied in yeast and mammals, NF-Y - also termed CBF and CP1 - is composed of three subunits, NF-YA, NF-YB and NF-YC. The complex recognizes the CCAAT pentanucleotide and specific flanking nucleotides with high specificity (Dorn et al., 1997; Hatamochi et al., 1988; Hooft van Huijsduijnen et al, 1987; Kim & Sheffery, 1990). A compelling set of bioinformatics studies clarified that the NF-Y preferred binding site is one of the most frequent promoter elements (Suzuki et al., 2001, 2004; Elkon et al., 2003; Marino-Ramirez et al., 2004; FitzGerald et al., 2004; Linhart et al., 2005; Zhu et al., 2005; Lee et al., 2007; Abnizova et al., 2007; Grskovic et al., 2007; Halperin et al., 2009; Hakkinen et al., 2011). The same consensus, as determined by mutagenesis and SELEX studies (Bi et al., 1997), was also retrieved in ChIP-on-chip analysis (Testa et al., 2005; Ceribelli et al., 2006; Ceribelli et al., 2008; Reed et al., 2008). Additional structural features of the CCAAT box - position, orientation, presence of multiple Transcriptional Start Sites - were previously reviewed (Dolfini et al., 2009) and will not be considered in detail here.