New Generation Discovery: A Systematic View for Its Development, Issues and Future
KAUST DepartmentUniversity Library
Permanent link to this recordhttp://hdl.handle.net/10754/313408
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AbstractCollecting, storing, discovering, and locating are integral parts of the composition of the library. To fully utilize the library and achieve its ultimate value, the construction and production of discovery has always been a central part of the library’s practice and identity. That is the reason why the new generation (also called the next-generation discovery) discovery gets such striking effect since it came into library automation arena. However, when we talk about the new generation of discovery in the library domain, we should see it in the entirety of the library as one of its organic parts and consider its progress along with the evolution of the whole library world. We should have a deeper understanding about its relationship and interaction with the internet, the rapidly changing digital environment, and the elements and the chain of library services. To address above issues, this paper overviews the different versions of the definition for the new generation discovery by combining our own understanding. The paper also gives our own description for its properties and characteristics. The paper points out what challenges, which extends the technology domain to commercial interests and business strategy, are faced by the discovery applications, and how library and library professionals deal with those challenges. Finally, the paper elaborates on the promise brought by the new discovery development and what the next exploration might be for its future.
DescriptionThis paper is presented for the international conference: “Change and Challenge: Redefine the Future of Academic Libraries” on November 4-5th, 2012 in Beijing.
JournalSSRN Electronic Journal
Conference/Event nameChange and Challenge: Redefine the Future of Academic Libraries
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MobiSeq: De novo SNP discovery in model and non-model species through sequencing the flanking region of transposable elementsRey-Iglesia, Alba; Gopalakrishan, Shyam; Carøe, Christian; Alquezar-Planas, David E.; Ahlmann Nielsen, Anne; Röder, Timo; Bruhn Pedersen, Lene; Næsborg-Nielsen, Christina; Sinding, Mikkel-Holger S.; Fredensborg Rath, Martin; Li, Zhipeng; Petersen, Bent; Gilbert, M. Thomas P.; Bunce, Michael; Mourier, Tobias; Hansen, Anders Johannes (Molecular Ecology Resources, Wiley, 2018-12-21) [Article]In recent years, the availability of reduced representation library (RRL) methods has catalysed an expansion of genome-scale studies to characterize both model and non-model organisms. Most of these methods rely on the use of restriction enzymes to obtain DNA sequences at a genome-wide level. These approaches have been widely used to sequence thousands of markers across individuals for many organisms at a reasonable cost, revolutionizing the field of population genomics. However, there are still some limitations associated with these methods, in particular the high molecular weight DNA required as starting material, the reduced number of common loci among investigated samples, and the short length of the sequenced site-associated DNA. Here, we present MobiSeq, a RRL protocol exploiting simple laboratory techniques, that generates genomic data based on PCR targeted enrichment of transposable elements and the sequencing of the associated flanking region. We validate its performance across 103 DNA extracts derived from three mammalian species: grey wolf (Canis lupus), red deer complex (Cervus sp.) and brown rat (Rattus norvegicus). MobiSeq enables the sequencing of hundreds of thousands loci across the genome and performs SNP discovery with relatively low rates of clonality. Given the ease and flexibility of MobiSeq protocol, the method has the potential to be implemented for marker discovery and population genomics across a wide range of organisms—enabling the exploration of diverse evolutionary and conservation questions.
Species-independent MicroRNA Gene DiscoveryKamanu, Timothy K. (2012-12) [Dissertation]
Advisor: Bajic, Vladimir B.
Committee members: Gao, Xin; Gehring, Christoph A; Narasimhan, Kothandaraman; Pain, ArnabMicroRNA (miRNA) are a class of small endogenous non-coding RNA that are mainly negative transcriptional and post-transcriptional regulators in both plants and animals. Recent studies have shown that miRNA are involved in different types of cancer and other incurable diseases such as autism and Alzheimer’s. Functional miRNAs are excised from hairpin-like sequences that are known as miRNA genes. There are about 21,000 known miRNA genes, most of which have been determined using experimental methods. miRNA genes are classified into different groups (miRNA families). This study reports about 19,000 unknown miRNA genes in nine species whereby approximately 15,300 predictions were computationally validated to contain at least one experimentally verified functional miRNA product. The predictions are based on a novel computational strategy which relies on miRNA family groupings and exploits the physics and geometry of miRNA genes to unveil the hidden palindromic signals and symmetries in miRNA gene sequences. Unlike conventional computational miRNA gene discovery methods, the algorithm developed here is species-independent: it allows prediction at higher accuracy and resolution from arbitrary RNA/DNA sequences in any species and thus enables examination of repeat-prone genomic regions which are thought to be non-informative or ’junk’ sequences. The information non-redundancy of uni-directional RNA sequences compared to information redundancy of bi-directional DNA is demonstrated, a fact that is overlooked by most pattern discovery algorithms. A novel method for computing upstream and downstream miRNA gene boundaries based on mathematical/statistical functions is suggested, as well as cutoffs for annotation of miRNA genes in different miRNA families. Another tool is proposed to allow hypotheses generation and visualization of data matrices, intra- and inter-species chromosomal distribution of miRNA genes or miRNA families. Our results indicate that: miRNA and miRNA genes are not only species-specific but may also be DNA strand-specific and chromosome-specific; the genomic distribution of miRNA genes is conserved at the chromosomal level across species; miRNA are conserved; More than one miRNA with different regulatory targets can be excised from one miRNA gene; Repeat-related miRNA and miRNA genes with palindromic sequences may be the largest subclass of miRNA class that have eluded detection by most computational and experimental methods.
Unique prokaryotic consortia in geochemically distinct sediments from Red Sea Atlantis II and discovery deep brine pools.Siam, Rania; Mustafa, Ghada A; Sharaf, Hazem; Moustafa, Ahmed; Ramadan, Adham R; Antunes, Andre; Bajic, Vladimir B.; Stingl, Ulrich; Marsis, Nardine G R; Coolen, Marco J L; Sogin, Mitchell; Ferreira, Ari J S; Dorry, Hamza El (PLoS ONE, Public Library of Science (PLoS), 2012-08-20) [Article]The seafloor is a unique environment, which allows insights into how geochemical processes affect the diversity of biological life. Among its diverse ecosystems are deep-sea brine pools - water bodies characterized by a unique combination of extreme conditions. The 'polyextremophiles' that constitute the microbial assemblage of these deep hot brines have not been comprehensively studied. We report a comparative taxonomic analysis of the prokaryotic communities of the sediments directly below the Red Sea brine pools, namely, Atlantis II, Discovery, Chain Deep, and an adjacent brine-influenced site. Analyses of sediment samples and high-throughput pyrosequencing of PCR-amplified environmental 16S ribosomal RNA genes (16S rDNA) revealed that one sulfur (S)-rich Atlantis II and one nitrogen (N)-rich Discovery Deep section contained distinct microbial populations that differed from those found in the other sediment samples examined. Proteobacteria, Actinobacteria, Cyanobacteria, Deferribacteres, and Euryarchaeota were the most abundant bacterial and archaeal phyla in both the S- and N-rich sections. Relative abundance-based hierarchical clustering of the 16S rDNA pyrotags assigned to major taxonomic groups allowed us to categorize the archaeal and bacterial communities into three major and distinct groups; group I was unique to the S-rich Atlantis II section (ATII-1), group II was characteristic for the N-rich Discovery sample (DD-1), and group III reflected the composition of the remaining sediments. Many of the groups detected in the S-rich Atlantis II section are likely to play a dominant role in the cycling of methane and sulfur due to their phylogenetic affiliations with bacteria and archaea involved in anaerobic methane oxidation and sulfate reduction.