3,247 research outputs found

    Caenorhabditis nomenclature

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    Genetic nomenclature allows the genetic features of an organism to be structured and described in a uniform and systematicway. Genetic features, including genes, variations (both natural and induced), and gene products, are assigned descriptorsthat inform on the nature of the feature. These nomenclature designations facilitate communication among researchers (in publications,presentations, and databases) to advance understanding of the biology of the genetic feature and the experimental utilizationof organisms that contain the genetic feature. The nomenclature system that is used for C. elegans was first employed by Sydney Brenner (1974) in his landmark description of the genetics of this model organism, and then substantially extended and modified in Horvitz et al., 1979. The gene, allele, and chromosome rearrangement nomenclature, described below, is an amalgamation of that from bacteria andyeast, with the rearrangement types from Drosophila. The nomenclature avoids standard words, subscripts, superscripts, and Greek letters and includes a hyphen (-) to separatethe gene name from gene number (distinct genes with similar phenotypes or molecular properties). As described by Jonathan Hodgkin, ‘the hyphen is about 1 mm in length in printed text and therefore symbolizes the 1 mm long worm’. These nomenclature propertiesmake C. elegans publications highly suitable for informatic text mining, as there is minimal ambiguity. From the founding of the CaenorhabditisGenetics Center (CGC) in 1979 until 1992, Don Riddle and Mark Edgley acted as the central repository for genetic nomenclature. Jonathan Hodgkin was nomenclature czar from 1992 through 2013; this was a pivotal period with the elucidation of the genome sequence of C. elegans, and later that of related nematodes, and the inception of WormBase. Thus, under the guidance of Hodgkin, the nomenclature system became a central feature of WormBase and the number and types of genetic features significantly expanded. The nomenclature system remains dynamic, with recentadditions including guidelines related to genome engineering, and continued reliance on the community for input. WormBase assigns specific identifying codes to each laboratory engaged in dedicated long-term genetic research on C. elegans. Each laboratory is assigned a laboratory/strain code for naming strains, and an allele code for naming genetic variation(e.g., mutations) and transgenes. These designations are assigned to the laboratory head/PI who is charged with supervisingtheir organization in laboratory databases and their associated biological reagents that are described on WormBase, in publications, and distributed to the scientific community on request. The laboratory/strain code is used: a) to identifythe originator of community-supplied information on WormBase, which, in addition to attribution, facilitates communicationbetween the community/curators and the originator if an issue related to the information should arise at a later date; andb) to provide a tracking code for activities at the CGC. The laboratory/strain designation consists of 2-3 uppercase letters while the allele designation has 1-3 lowercase letters.The final letter of a laboratory code should not be an “O” or an “I” so as not to be mistaken for the numbers “0” or “1” respectively.Additionally, allele designations should also not end with the letter “l” which could also be mistaken for the number “1.” These codes are listed at the CGC and in WormBase. Investigators generating strains, alleles, transgenes, and/or defining genes require these designations and should applyfor them at [email protected]. Information for several other nematode species, in addition to C. elegans, is curated at WormBase. All species are referred to by their Linnean binomial names (e.g,. Caenorhabditis elegans or C. elegans). Details of all the genomes available at WormBase and the degree of their curation can be found at www.wormbase.org/species/al

    An evolving process: patterns and objects

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    This thesis investigates my life experiences,inspired by the surroundings in New England and India. My process is characterized by a multidisciplinary approach. I integrate diverse media moving fluidly between two dimensional and three dimensional work, creating multiple layers of pattern and objects

    Allogenic Decal-Bone Grafts: A Viable Option in Clinical Orthopedics

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    One has to resort to allogenic source of bone grafts especially in filling up of large or multiple containable cavitary lesions, structural reconstruction of large circumferential osteoperiosteal defects, extensive spinal fusions for gross deformities, or extensive operative reconstruction after total joint replacements. These procedures demand an abundant quantity of bone material in which a patient’s (recipient’s) body cannot supply without significant morbidity and risks. At present most of the allogenic bone banks use deep-freezing or freeze-drying or radiation for long-term preservation. The techniques maintain sterility, reduce immunogenicity, and provide adequate structural integrity; however, such procedures reduce the bone-forming biological activity and are expensive. We have worked for clinical translation of the basic research performed by Marshal Urist (1965–1994). After extensive experimental observations, we have been using partially decalcified allogenic bone as grafts in clinical cases since 1978. Favorable outcome has been observed in benign cystic lesions, wide-gap grafting, and spinal fusions. Minimum follow-up for declaring “success” or “failure” of the procedure was 2 years after implantation

    THE ROLE OF MOLECULAR DYNAMICS SIMULATIONS IN INVESTIGATING DIFFUSION ON MESOSCOPIC SCALES

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    In order to investigate transport properties of molecular solutions on mesoscopic scales, we use the fluctuation-dissipation theorem and velocity and noise autocorrelation to determine the diffusion constant of two simulated solutions of particles interacting through Lennard-Jones potentials. This thesis describes classical transport theories which are valid for macroscopic diffusion, and includes a discussion of the nature of the force on solute particles which are comparable in size to solvent particles (we call diffusion in this limit ‘mesoscopic diffusion’). Next, it discusses transport theories of systems in this limit, and methods of determining their diffusion constant by extracting the velocity autocorrelation of particles in simulations. Finally, it includes results from a molecular dynamics simulation with GROMACS, and the details of preparing and running a force-field dependent simulation on MATLAB. The MATLAB simulation of liquid methyl red (or, otherwise, methyl red in a solvent whose molecules have mass and size properties exactly like itself) gives a value for the diffusion constant to be 7 1 10 . This is value is significantly different from several experimentally determined diffusion coefficients of methyl red in organic solvents

    THE PERFORMANCE OF SOFT CHEKPOINTING APPROACH IN MOBILE COMPUTING SYSTEMS

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    Mobile computing raises many new issues such as lack of stable storage, low bandwidth of wireless channel, high mobility, and limited battery life. These new issues make traditional checkpointing algorithms unsuitable. Coordinated checkpointing is an attractive approach for transparently adding fault tolerance to distributed applications since it avoids domino effects and minimizes the stable storage requirement. However, it suffers from high overhead associated with the checkpointing process in mobile computing systems. In literature mostly, two approaches have been used to reduce the overhead: First is to minimize the number of synchronization messages and the number of checkpoints; the other is to make the checkpointing process nonblocking. Since MHs are prone to failure, so they have to transfer a large amount of checkpoint data and control information to its local MSS which increases bandwidth overhead. In this paper, we introduce the concept of 201C;Soft checkpoint201D; which is neither a tentative checkpoint nor a permanent checkpoint, to design efficient checkpointing algorithms for mobile computing systems. Soft checkpoints can be saved anywhere, e.g., the main memory or local disk of MHs. Before disconnecting from the MSS, these soft checkpoints are converted to hard checkpoints and are sent to MSSs stable storage. In this way, taking a soft checkpoint avoids the overhead of transferring large amounts of data to the stable storage at MSSs over the wireless network. We have also shown that our soft checkpointing scheme also adapts its behaviour to the characteristics of network
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