Relevant bibliographies by topics / Sequence analysis methods

Academic literature on the topic 'Sequence analysis methods'

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Published: 11 March 2023

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Journal articles on the topic "Sequence analysis methods"

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Smith, CA. "Methods in Protein Sequence Analysis." Biochemical Education 18, no. 1 (January 1990): 54–55. http://dx.doi.org/10.1016/0307-4412(90)90036-n.

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Seabrook, BN. "Methods in protein sequence analysis." Biochemical Education 22, no. 1 (January 1994): 59. http://dx.doi.org/10.1016/0307-4412(94)90193-7.

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Light, Albert. "Methods of protein sequence analysis." Analytical Biochemistry 167, no. 1 (November 1987): 210. http://dx.doi.org/10.1016/0003-2697(87)90153-9.

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Rybinska, Anna. "Social Sequence Analysis: Methods and Applications." Social Forces 96, no. 1 (April 4, 2017): e6-e6. http://dx.doi.org/10.1093/sf/sox026.

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Aisenbrey, Silke. "Social Sequence Analysis: Methods and Applications." Contemporary Sociology: A Journal of Reviews 46, no. 6 (October 27, 2017): 665–67. http://dx.doi.org/10.1177/0094306117734868i.

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Kuhn, Alfred. "Methods in protein sequence analysis 1986." Journal of Chromatography A 410 (January 1987): 514. http://dx.doi.org/10.1016/s0021-9673(00)90090-6.

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Bailey, Jerome M. "Chemical methods of protein sequence analysis." Journal of Chromatography A 705, no. 1 (June 1995): 47–65. http://dx.doi.org/10.1016/0021-9673(94)01250-i.

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Wilson, Clarke. "Analysis of Travel Behavior Using Sequence Alignment Methods." Transportation Research Record: Journal of the Transportation Research Board 1645, no. 1 (January 1998): 52–59. http://dx.doi.org/10.3141/1645-07.

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Sequence alignment methods are applied to daily activity data derived from the Statistics Canada 1992 General Social Survey on Time Use, with special emphasis on travel episodes and the activities that generate travel. Sequence alignment is a combinatorial procedure that gives a quantitative measure of the similarity of character sequences, which may be used to represent daily activity patterns. It accommodates all the details supplied from activity diaries including the ordering of activity episodes, their duration, and patterns of transitions from one activity to another. Analysis of daily activity patterns by using such methods offers a new way of improving understanding of travel behavior. Such an understanding is especially critical when public transport policy is being driven increasingly by budget constraints, and traffic management through congestion is considered an acceptable response to increasing travel demands. The method successfully identifies groupings of behavioral patterns, which then may be further described by using multivariate analysis of sociodemographic characteristics. A key issue in the application of the method is to determine the circumstances in which activity sequences should or should not reflect episode duration.
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Zeltser, Maria. "Bounded Domains of Generalized Riesz Methods with the Hahn Property." Journal of Function Spaces and Applications 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/908682.

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In 2002 Bennett et al. started the investigation to which extent sequence spaces are determined by the sequences of 0s and 1s that they contain. In this relation they defined three types of Hahn properties for sequence spaces: the Hahn property, separable Hahn property, and matrix Hahn property. In general all these three properties are pairwise distinct. If a sequence spaceEis solid and(0,1ℕ∩E)β=Eβ=ℓ1then the two last properties coincide. We will show that even on these additional assumptions the separable Hahn property and the Hahn property still do not coincide. However if we assumeEto be the bounded summability domain of a regular Riesz matrixRpor a regular nonnegative Hausdorff matrixHp, then this assumption alone guarantees thatEhas the Hahn property. For any (infinite) matrixAthe Hahn property of its bounded summability domain is related to the strongly nonatomic property of the densitydAdefined byA. We will find a simple necessary and sufficient condition for the densitydAdefined by the generalized Riesz matrixRp,mto be strongly nonatomic. This condition appears also to be sufficient for the bounded summability domain ofRp,mto have the Hahn property.
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Steinke, Dirk, Miguel Vences, Walter Salzburger, and Axel Meyer. "TaxI: a software tool for DNA barcoding using distance methods." Philosophical Transactions of the Royal Society B: Biological Sciences 360, no. 1462 (September 8, 2005): 1975–80. http://dx.doi.org/10.1098/rstb.2005.1729.

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DNA barcoding is a promising approach to the diagnosis of biological diversity in which DNA sequences serve as the primary key for information retrieval. Most existing software for evolutionary analysis of DNA sequences was designed for phylogenetic analyses and, hence, those algorithms do not offer appropriate solutions for the rapid, but precise analyses needed for DNA barcoding, and are also unable to process the often large comparative datasets. We developed a flexible software tool for DNA taxonomy, named TaxI. This program calculates sequence divergences between a query sequence (taxon to be barcoded) and each sequence of a dataset of reference sequences defined by the user. Because the analysis is based on separate pairwise alignments this software is also able to work with sequences characterized by multiple insertions and deletions that are difficult to align in large sequence sets (i.e. thousands of sequences) by multiple alignment algorithms because of computational restrictions. Here, we demonstrate the utility of this approach with two datasets of fish larvae and juveniles from Lake Constance and juvenile land snails under different models of sequence evolution. Sets of ribosomal 16S rRNA sequences, characterized by multiple indels, performed as good as or better than cox1 sequence sets in assigning sequences to species, demonstrating the suitability of rRNA genes for DNA barcoding.
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Dissertations / Theses on the topic "Sequence analysis methods"

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Park, Jong Hwa. "Genome sequence analysis and methods." Thesis, University of Cambridge, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.627329.

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Isgro, Francesco. "Geometric methods for video sequence analysis and applications." Thesis, Heriot-Watt University, 2001. http://hdl.handle.net/10399/495.

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Verzotto, Davide. "Advanced Computational Methods for Massive Biological Sequence Analysis." Doctoral thesis, Università degli studi di Padova, 2011. http://hdl.handle.net/11577/3426282.

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With the advent of modern sequencing technologies massive amounts of biological data, from protein sequences to entire genomes, are becoming increasingly available. This poses the need for the automatic analysis and classification of such a huge collection of data, in order to enhance knowledge in the Life Sciences. Although many research efforts have been made to mathematically model this information, for example finding patterns and similarities among protein or genome sequences, these approaches often lack structures that address specific biological issues. In this thesis, we present novel computational methods for three fundamental problems in molecular biology: the detection of remote evolutionary relationships among protein sequences, the identification of subtle biological signals in related genome or protein functional sites, and the phylogeny reconstruction by means of whole-genome comparisons. The main contribution is given by a systematic analysis of patterns that may affect these tasks, leading to the design of practical and efficient new pattern discovery tools. We thus introduce two advanced paradigms of pattern discovery and filtering based on the insight that functional and conserved biological motifs, or patterns, should lie in different sites of sequences. This enables to carry out space-conscious approaches that avoid a multiple counting of the same patterns. The first paradigm considered, namely irredundant common motifs, concerns the discovery of common patterns, for two sequences, that have occurrences not covered by other patterns, whose coverage is defined by means of specificity and extension. The second paradigm, namely underlying motifs, concerns the filtering of patterns, from a given set, that have occurrences not overlapping other patterns with higher priority, where priority is defined by lexicographic properties of patterns on the boundary between pattern matching and statistical analysis. We develop three practical methods directly based on these advanced paradigms. Experimental results indicate that we are able to identify subtle similarities among biological sequences, using the same type of information only once. In particular, we employ the irredundant common motifs and the statistics based on these patterns to solve the remote protein homology detection problem. Results show that our approach, called Irredundant Class, outperforms the state-of-the-art methods in a challenging benchmark for protein analysis. Afterwards, we establish how to compare and filter a large number of complex motifs (e.g., degenerate motifs) obtained from modern motif discovery tools, in order to identify subtle signals in different biological contexts. In this case we employ the notion of underlying motifs. Tests on large protein families indicate that we drastically reduce the number of motifs that scientists should manually inspect, further highlighting the actual functional motifs. Finally, we combine the two proposed paradigms to allow the comparison of whole genomes, and thus the construction of a novel and practical distance function. With our method, called Unic Subword Approach, we relate to each other the regions of two genome sequences by selecting conserved motifs during evolution. Experimental results show that our approach achieves better performance than other state-of-the-art methods in the whole-genome phylogeny reconstruction of viruses, prokaryotes, and unicellular eukaryotes, further identifying the major clades of these organisms.
Con l'avvento delle moderne tecnologie di sequenziamento, massive quantità di dati biologici, da sequenze proteiche fino a interi genomi, sono disponibili per la ricerca. Questo progresso richiede l'analisi e la classificazione automatica di tali collezioni di dati, al fine di migliorare la conoscenza nel campo delle Scienze della Vita. Nonostante finora siano stati proposti molti approcci per modellare matematicamente le sequenze biologiche, ad esempio cercando pattern e similarità tra sequenze genomiche o proteiche, questi metodi spesso mancano di strutture in grado di indirizzare specifiche questioni biologiche. In questa tesi, presentiamo nuovi metodi computazionali per tre problemi fondamentali della biologia molecolare: la scoperta di relazioni evolutive remote tra sequenze proteiche, l'individuazione di segnali biologici complessi in siti funzionali tra loro correlati, e la ricostruzione della filogenesi di un insieme di organismi, attraverso la comparazione di interi genomi. Il principale contributo è dato dall'analisi sistematica dei pattern che possono interessare questi problemi, portando alla progettazione di nuovi strumenti computazionali efficaci ed efficienti. Vengono introdotti così due paradigmi avanzati per la scoperta e il filtraggio di pattern, basati sull'osservazione che i motivi biologici funzionali, o pattern, sono localizzati in differenti regioni delle sequenze in esame. Questa osservazione consente di realizzare approcci parsimoniosi in grado di evitare un conteggio multiplo degli stessi pattern. Il primo paradigma considerato, ovvero irredundant common motifs, riguarda la scoperta di pattern comuni a coppie di sequenze che hanno occorrenze non coperte da altri pattern, la cui copertura è definita da una maggiore specificità e/o possibile estensione dei pattern. Il secondo paradigma, ovvero underlying motifs, riguarda il filtraggio di pattern che hanno occorrenze non sovrapposte a quelle di altri pattern con maggiore priorità, dove la priorità è definita da proprietà lessicografiche dei pattern al confine tra pattern matching e analisi statistica. Sono stati sviluppati tre metodi computazionali basati su questi paradigmi avanzati. I risultati sperimentali indicano che i nostri metodi sono in grado di identificare le principali similitudini tra sequenze biologiche, utilizzando l'informazione presente in maniera non ridondante. In particolare, impiegando gli irredundant common motifs e le statistiche basate su questi pattern risolviamo il problema della rilevazione di omologie remote tra proteine. I risultati evidenziano che il nostro approccio, chiamato Irredundant Class, ottiene ottime prestazioni su un benchmark impegnativo, e migliora i metodi allo stato dell'arte. Inoltre, per individuare segnali biologici complessi utilizziamo la nozione di underlying motifs, definendo così alcune modalità per il confronto e il filtraggio di motivi degenerati ottenuti tramite moderni strumenti di pattern discovery. Esperimenti su grandi famiglie proteiche dimostrano che il nostro metodo riduce drasticamente il numero di motivi che gli scienziati dovrebbero altrimenti ispezionare manualmente, mettendo in luce inoltre i motivi funzionali identificati in letteratura. Infine, combinando i due paradigmi proposti presentiamo una nuova e pratica funzione di distanza tra interi genomi. Con il nostro metodo, chiamato Unic Subword Approach, relazioniamo tra loro le diverse regioni di due sequenze genomiche, selezionando i motivi conservati durante l'evoluzione. I risultati sperimentali evidenziano che il nostro approccio offre migliori prestazioni rispetto ad altri metodi allo stato dell'arte nella ricostruzione della filogenesi di organismi quali virus, procarioti ed eucarioti unicellulari, identificando inoltre le sottoclassi principali di queste specie.
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Oppermann, Madalina. "Chemical and mass spectrometrical methods in protein analysis /." Stockholm, 2000. http://diss.kib.ki.se/2000/91-628-4542-x/.

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Lovmar, Lovisa. "Methods for Analysis of Disease Associated Genomic Sequence Variation." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-4525.

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Reinhardt, Astrid. "Neural network-based methods for large scale protein sequence analysis." Thesis, University of Cambridge, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.624141.

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Henderson, Daniel Adrian. "Modelling and analysis of non-coding DNA sequence data." Thesis, University of Newcastle Upon Tyne, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.299427.

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Tanaka, Emi. "Statistical Methods for Improving Motif Evaluation." Thesis, The University of Sydney, 2014. http://hdl.handle.net/2123/13922.

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Gene regulation, especially cis-regulation of gene expression by the binding of transcription factors, is a critical component of cellular physiology. Transcription regulation is heavily influenced by the binding of transcription factors, and as such, it is of great interest to characterise these binding sites. The binding sites of a transcription factor are collectively referred to as a regulatory motif. Recent advancement in sequencing technology generated vast amounts of biological data. Thus computational tools are required to process and analyse this massive information. In particular, computational tools were developed to search for over-represented words among a set of co-regulated sequences. Such tools would be somewhat incomplete without a statistical analysis that allows researchers to discern between real biological significant sites and random artefacts. By analogy, it is difficult to imagine evaluating a BLAST result without its accompanying E-value. Of the many motif finders, MEME, with over 9000 unique users recorded in the first half of 2013, is one of the most popular motif finding tools available. Currently MEME evaluates its candidate motifs using an extension of BLAST's E-value to the motif finding context. Ng et al. (2006) previously showed the drawbacks of MEME's current significance evaluation scheme, however because MEME relies on the same E-value to internally rank competing candidate motifs, the alternative evaluation offered by Keich and Ng (2007) was not a practical substitute. Here we offer a two-tiered significance analysis that can replace the E-value in selecting the best candidate motif as well as in evaluating its overall statistical significance. We show that our new approach substantially improves MEME's motif finding performance and also provides the user with a reliable significance analysis. In addition, for large input sets our new approach is faster than the currently implemented E-value analysis. After applying a motif finder to a set of co-regulated DNA sequences, researchers often are interested to know whether the reported putative motif is similar to any known motif. While several tools have been designed for this task, Habib et al. (2008) pointed out that the scores that are commonly used for measuring similarity between motifs do not distinguish between a good alignment of two informative columns (say, all-A) and one of two uninformative columns. This observation explains why motif comparison tools such as Tomtom occasionally return an alignment of uninformative columns which is clearly spurious. To address this distinguishability problem Habib et al. (2008) suggested a new score, the BLiC. This score uses a Bayesian information criterion to penalise matches that are similar to the background distribution. We show that the BLiC score exhibits other, highly undesirable properties. Therefore as an alternative, we offer a general approach to adjust any motif similarity score so as to reduce the number of reported spurious alignments of uninformative columns. We implemented our method in Tomtom and we show that, without significantly compromising Tomtom's retrieval accuracy or runtime, we drastically reduce the number of uninformative alignments. The modified Tomtom is currently available as part of the MEME Suite at http://meme.nbcr.net. A motif is not limited to sites regulating gene expression. A motif is a recurring nucleotide sequence pattern that has a biological significance. One such example is in the context of the origins of replication of Saccharomyces cerevisiae. Autonomously replicating sequences (ARSs) are DNA fragments that promote extrachromosomal maintenance of plasmids. These ARSs mostly coincide with origins of DNA replication and therefore we use the terms interchangeably. The origins of replication in Saccharomyces cerevisiae have a highly conserved sequence known as the ACS (ARS consensus sequence). Depending on the reference, its representation varies from the 11bp consensus sequence WTTTAYRTTTW to a 33bp position weight matrix. While the replication origins of some species, such as Schizosaccharomyces pombe and metazoans, do not have any known motif, Liachko et al. (2010) found that the replication origins of another budding yeast Kluyveromyces lactis share a 50-bp ACS motif which is inherently different to the ACS motif found in S. cerevisiae. Here we characterise ARSs in Lachancea (Saccharomyces) kluyveri - a pre-whole genome duplication budding yeast. In addition, we demonstrate that ARS function in L. kluyveri is dependent on a much longer sequence compared with S. cerevisiae and K. lactis. Furthermore, the system of replication initiation in L. kluyveri appears to be more permissive than in these other two species - it is able to initiate replication from all S. cerevisiae ARSs and most K. lactis ARSs, while only half of L. kluyveri ARSs function in S. cerevisiae and less than 10% function in K. lactis. Our findings demonstrate a replication initiation system with novel features and underscore its functional diversity within the budding yeasts.
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Chen, Zhuo. "Smart Sequence Similarity Search (S⁴) system." CSUSB ScholarWorks, 2004. https://scholarworks.lib.csusb.edu/etd-project/2458.

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Sequence similarity searching is commonly used to help clarify the biochemical and physiological features of newly discovered genes or proteins. An efficient similarity search relies on the choice of tools and their associated subprograms and numerous parameter settings. To assist researchers in selecting optimal programs and parameter settings for efficient sequence similarity searches, the web-based expert system, Smart Sequence Similarity Search (S4) was developed.
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Holder, Mark Travis. "Using a complex model of sequence evolution to evaluate and improve phylogenetic methods." Access restricted to users with UT Austin EID Full text (PDF) from UMI/Dissertation Abstracts International, 2001. http://wwwlib.umi.com/cr/utexas/fullcit?p3037500.

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Books on the topic "Sequence analysis methods"

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1941-, Procter Michael, Abell Peter 1939-, and Surrey Conference on Methods and Theory of Sociological Investigation (2nd : 1983 : University of Surrey), eds. Sequence analysis. Aldershot, England: Gower, 1985.

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Imahori, Kazutomo, and Fumio Sakiyama, eds. Methods in Protein Sequence Analysis. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4899-1603-7.

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Wittmann-Liebold, Brigitte, ed. Methods in Protein Sequence Analysis. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-73834-0.

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Jörnvall, Hans, Jan-Olov Höög, and Ann-Margreth Gustavsson, eds. Methods in Protein Sequence Analysis. Basel: Birkhäuser Basel, 1991. http://dx.doi.org/10.1007/978-3-0348-5678-2.

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Hans, Jörnvall, Höög J. -O, Gustavsson A. -M, and International Conference on Methods in Protein Sequence Analysis (8th : 1990 : Kiruna, Sweden), eds. Methods in protein sequence analysis. Basel: Birkhäuser Verlag, 1991.

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Kazutomo, Imahori, Sakiyama Fumio, and International Conference on Methods in Protein Sequence Analysis (9th : 1992 : Otsu, Japan), eds. Methods in protein sequence analysis. New York: Plenum Press, 1993.

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Walsh, Kenneth A., ed. Methods in Protein Sequence Analysis · 1986. Totowa, NJ: Humana Press, 1987. http://dx.doi.org/10.1007/978-1-59259-480-1.

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1931-, Wittmann-Liebold B., Salnikow J. 1938-, and Erdmann V. A. 1941-, eds. Advanced methods in protein microsequence analysis. Berlin: Springer-Verlag, 1986.

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G, Gindikin S., ed. Mathematical methods of analysis of biopolymer sequences. Providence, R.I: American Mathematical Society, 1992.

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R, Swindell Simon, ed. Sequence data analysis guidebook. Totowa, N.J: Humana Press, 1997.

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Book chapters on the topic "Sequence analysis methods"

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Lange, Kenneth. "Sequence Analysis." In Mathematical and Statistical Methods for Genetic Analysis, 281–97. New York, NY: Springer New York, 2002. http://dx.doi.org/10.1007/978-0-387-21750-5_13.

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Karsch-Mizrachi, Ilene, and B. F. Francis Ouellette. "The GenBank Sequence." In Methods of Biochemical Analysis, 45–63. New York, USA: John Wiley & Sons, Inc., 2002. http://dx.doi.org/10.1002/0471223921.ch3.

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Krech, Volkhard, and Martin Radermacher. "Sequence Analysis." In The Routledge Handbook of Research Methods in the Study of Religion, 445–60. 2nd ed. London: Routledge, 2021. http://dx.doi.org/10.4324/9781003222491-31.

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Koonin, Eugene V., and Michael Y. Galperin. "Principles and Methods of Sequence Analysis." In Sequence — Evolution — Function, 111–92. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4757-3783-7_5.

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Pattini, Linda, and Sergio Cerutti. "Biomolecular Sequence Analysis." In Advanced Methods of Biomedical Signal Processing, 489–507. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118007747.ch20.

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Butler, Barbara A. "Sequence Analysis Using GCG." In Methods of Biochemical Analysis, 74–97. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/9780470110607.ch4.

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Wolfsberg, Tyra G., and David Landsman. "Expressed Sequence Tags (ESTs)." In Methods of Biochemical Analysis, 283–301. New York, USA: John Wiley & Sons, Inc., 2002. http://dx.doi.org/10.1002/0471223921.ch12.

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Ouellette, B. F. Francis. "The GenBank Sequence Database." In Methods of Biochemical Analysis, 16–45. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2006. http://dx.doi.org/10.1002/9780470110607.ch2.

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Yap, Tieng K., Ophir Frieder, and Robert L. Martino. "Sequence Analysis Algorithms." In High Performance Computational Methods for Biological Sequence Analysis, 51–97. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-1391-5_3.

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Inglis, Adam S., Robert L. Moritz, Geoffrey S. Begg, Gavin E. Reid, Richard J. Simpson, Horst Graffunder, Lothar Matschull, and Brigitte Wittmann-Liebold. "C-Terminal Sequence Analysis." In Methods in Protein Sequence Analysis, 23–34. Basel: Birkhäuser Basel, 1991. http://dx.doi.org/10.1007/978-3-0348-5678-2_2.

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Conference papers on the topic "Sequence analysis methods"

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Luo, Liaofu, Jun Lu, Theodore E. Simos, and George Maroulis. "Sequence Pattern Recognition in Genome Analysis." In COMPUTATIONAL METHODS IN SCIENCE AND ENGINEERING: Theory and Computation: Old Problems and New Challenges. Lectures Presented at the International Conference on Computational Methods in Science and Engineering 2007 (ICCMSE 2007): VOLUME 1. AIP, 2007. http://dx.doi.org/10.1063/1.2835983.

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Song, Hyun-Je, and Seong-Bae Park. "Korean Morphological Analysis with Tied Sequence-to-Sequence Multi-Task Model." In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/d19-1150.

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Bellani, Manas, Julien Epps, and Gavin A. Huttley. "A comparison of periodicity profile methods for sequence analysis." In 2012 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS). IEEE, 2012. http://dx.doi.org/10.1109/gensips.2012.6507731.

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"cswHMM: A NOVEL CONTEXT SWITCHING HIDDEN MARKOV MODEL FOR BIOLOGICAL SEQUENCE ANALYSIS." In International Conference on Bioinformatics Models, Methods and Algorithms. SciTePress - Science and and Technology Publications, 2012. http://dx.doi.org/10.5220/0003780902080213.

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Camilleri, Duncan, Brian Ellul, and Martin Muscat. "Design-by-Analysis Methods for Asymmetric or Unbalanced Cylindrical Composite Pressure Vessels." In ASME 2014 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/pvp2014-28130.

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The combination of fibre volume fraction, fibre orientation and lay-up sequence in composite materials makes it possible to design a multitude of composite pressure vessels and pipes. Analytical models, based on the classical laminate theory and numerical predictive techniques offer a means to optimize the lay-up sequence in order to maximize the strength to weight / cost ratio. This study looks at the validity of using analytical models prescribed in the design by analysis filament wound composite standards and compares the results with realistic test and numerical models. The results show that the classical laminate theory accurately establishes the design load in symmetric and balanced lay-up laminates when appropriate material properties are assigned. However in the case of asymmetric or unbalanced lay-up sequences, the bending and twisting stiffness geometrically strengthens the pipes such that the classical hoop and axial loading conditions based on isotropic material properties, no longer apply. In such instances the analytical solutions can underestimate the design load by more than 33%. An analytical solution that accurately establishes the loading configuration and magnitude is required. On the other hand numerical models gave good agreement with the experimental test results immaterial of the lay-up sequences, when appropriate end coupling, pressure loading and material properties are applied.
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"APPLYING CONCEPTUAL MODELING TO ALIGNMENT TOOLS ONE STEP TOWARDS THE AUTOMATION OF DNA SEQUENCE ANALYSIS." In International Conference on Bioinformatics Models, Methods and Algorithms. SciTePress - Science and and Technology Publications, 2011. http://dx.doi.org/10.5220/0003142001370142.

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Orlov, Yurii Nikolaevich. "Language recognition methods and Voynich Manuscript analysis." In 4th International Conference “Futurity designing. Digital reality problems”. Keldysh Institute of Applied Mathematics, 2021. http://dx.doi.org/10.20948/future-2021-20.

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The statistical properties of letters frequencies in European literature texts are investigated. The determination of logarithmic dependence of letters sequence for one-languge and two-language texts are examined. The pare of languages are suggested for Voynich Manuscript. The internal structure of Manuscript is considered. The spectral portraits of two-letters distribution are constructed.
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Stanescu, Ana, Karthik Tangirala, and Doina Caragea. "Study of transductive learning and unsupervised feature construction methods for biological sequence classification." In 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2016. http://dx.doi.org/10.1109/asonam.2016.7752363.

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Cescatti, Elvis, Michol Rampado, Veronica Follador, Francesca da Porto, and Claudio Modena. "ANALYTICAL AND NUMERICAL ANALYSIS OF S. MARTINO’S DEI GUALDESI CHURCH DAMAGED DURING THE 2016 CENTRAL ITALY SEISMIC SEQUENCE." In 8th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering Methods in Structural Dynamics and Earthquake Engineering. Athens: Institute of Structural Analysis and Antiseismic Research National Technical University of Athens, 2021. http://dx.doi.org/10.7712/120121.8490.19179.

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Sun, Dabin, Zhijian Zhang, Lei Li, He Wang, Sijuan Chen, Yuhang Zhang, and Lixuan Zhang. "Security Analysis Based on Probabilistic Safety Analysis Coupled With Deterministic Safety Analysis Used RAVEN." In 2021 28th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/icone28-64361.

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Abstract Probabilistic safety analysis methods (PSA) and deterministic safety analysis methods (DSA) are classical safety analysis methods for nuclear power plant (NPP). However they can’t do a comprehensive analysis for epistemic uncertainty and aleatory uncertainty. This problem can be solved by Risk-Informed Safety Margin Characterization method (RISMC) which combines PSA and DSA. Due to Best-Estimate plus uncertainty analysis (BEPU) analysis method quantify the epistemic uncertainty in safety analysis accurately, BEPU is used for DSA. The dynamic event tree (DET) analysis method can branch the event tree according to the number of successfully invested devices, which can provide a more detailed component accident sequence, which is of great significance for serious aleatory uncertainty. In order to improve the analysis efficiency, the RAVEN platform is used for safety analysis. The uncertainty of NPP safety analysis is analyzed more accurately by using the RISMC analysis method which combines PSA and DSA. The CDF calculated by the BEPU analysis method coupled with the DET method is 3.59e−12, and the CDF obtained by the DET analysis method is 2.59E−15. Moreover, the efficiency of the analysis is greatly improved by using the RAVEN platform and the method of selecting significant sequence analysis.
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Reports on the topic "Sequence analysis methods"

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Payne, Jr., A., S. Eide, J. LaChance, and D. Whitehead. Analysis of the LaSalle Unit 2 Nuclear Power Plant: Risk Methods Integration and Evaluation Program (RMIEP). Volume 4, Initiating events and accident sequence delineation. Office of Scientific and Technical Information (OSTI), October 1992. http://dx.doi.org/10.2172/10191712.

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Payne, Jr., A., S. Daniel, D. Whitehead, T. Sype, S. Dingman, and C. Shaffer. Analysis of the LaSalle Unit 2 Nuclear Power Plant: Risk Methods Integration and Evaluation Program (RMIEP). Volume 3, Part 2, Internal events accident sequence quantification: Appendices. Office of Scientific and Technical Information (OSTI), August 1992. http://dx.doi.org/10.2172/10174542.

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Lippolis, Nicolas. Diagnostics for Industrialisation: Growth, Sectoral Selection, and Constraints on Firms. Digital Pathways at Oxford, March 2022. http://dx.doi.org/10.35489/bsg-dp-wp_2022/03.

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This paper reviews methods that have been suggested by the development literature on diagnostics. We subdivide the variety of diagnostics into three types: revealing the most binding constraints to economy-wide growth; selecting sectors in which to diversify; and identifying sources of sectoral underperformance. Each diagnostic method is judged on whether it: provides a structured way of performing diagnostics; directs analysts towards the right questions; and is efficient in its use of data and resources. After reviewing a variety of methods, we argue that, with respect to growth diagnostics, the best approach is to combine Hausmann’s, Rodrik and Velasco’s Growth Diagnostics with more encompassing and forward-looking methods. In sectoral selection, Hausmann and Hidalgo’s 'Product Space' analysis can serve as an adequate base for choosing sectors in which to diversify, but this method must be tempered by a much more diverse set of indicators that matter for sectoral choice. Finally, diagnostics at the sectoral level can be performed through a sequence of methods: starting from easily collectable perceptions data and progressing to more data-heavy techniques, depending on the time and resources available.
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Gelb, Jr., Jack, Yoram Weisman, Brian Ladman, and Rosie Meir. Identification of Avian Infectious Brochitis Virus Variant Serotypes and Subtypes by PCR Product Cycle Sequencing for the Rational Selection of Effective Vaccines. United States Department of Agriculture, December 2003. http://dx.doi.org/10.32747/2003.7586470.bard.

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Objectives 1. Determine the serotypic identities of 40 recent IBV isolates from commercial chickens raised in the USA and Israel. 2. Sequence all IBV field isolates using PCR product cycle sequencing and analyze their S 1 sequence to detennine their homology to other strains in the Genbank and EMBL databases. 3. Select vaccinal strains with the highest S 1 sequence homology to the field isolates and perform challenge of immunity studies in chickens in laboratory trials to detennine level of protection afforded by the vaccines. Background Infectious bronchitis (IB) is a common, economically important disease of the chicken. IB occurs as a respiratory form, associated with airsacculitis, condemnation, and mortality of meat-type broilers, a reproductive form responsible for egg production losses in layers and breeders, and a renal form causing high mortality in broilers and pullets. The causative agent is avian coronavirus infectious bronchitis virus (IBV). Replication of the virus' RNA genome is error-prone and mutations commonly result. A major target for mutation is the gene encoding the spike (S) envelope protein used by the virus to attach and infect the host cell. Mutations in the S gene result in antigenic changes that can lead to the emergence of variant serotypes. The S gene is able to tolerate numerous mutations without compromising the virus' ability to replicate and cause disease. An end result of the virus' "flexibility" is that many strains of IBV are capable of existing in nature. Once formed, new mutant strains, often referred to as variants, are soon subjected to immunological selection so that only the most antigenically novel variants survive in poultry populations. Many novel antigenic variant serotypes and genotypes have been isolated from commercial poultry flocks. Identification of the field isolates of IBV responsible for outbreaks is critical for selecting the appropriate strain(s) for vaccination. Reverse transcriptase polymerase chain reaction (RT-PCR) of the Sl subunit of the envelope spike glycoprotein gene has been a common method used to identify field strains, replacing other time-consuming or less precise tests. Two PCR approaches have been used for identification, restriction fragment length polymorphism (RFLP) and direct automated cycle sequence analysis of a diagnostically relevant hypervariab1e region were compared in our BARD research. Vaccination for IB, although practiced routinely in commercial flocks, is often not protective. Field isolates responsible for outbreaks may be unrelated to the strain(s) used in the vaccination program. However, vaccines may provide varying degrees of cross- protection vs. unrelated field strains so vaccination studies should be performed. Conclusions RFLP and S1 sequence analysis methods were successfully performed using the field isolates from the USA and Israel. Importantly, the S1 sequence analysis method enabled a direct comparison of the genotypes of the field strains by aligning them to sequences in public databases e.g. GenBank. Novel S1 gene sequences were identified in both USA and Israel IBVs but greater diversity was observed in the field isolates from the USA. One novel genotype, characterized in this project, Israel/720/99, is currently being considered for development as an inactivated vaccine. Vaccination with IBV strains in the US (Massachusetts, Arkansas, Delaware 072) or in Israel (Massachusetts, Holland strain) provided higher degrees of cross-protection vs. homologous than heterologous strain challenge. In many cases however, vaccination with two strains (only studies with US strains) produced reasonable cross-protection against heterologous field isolate challenge. Implications S1 sequence analysis provides numerical similarity values and phylogenetic information that can be useful, although by no means conclusive, in developing vaccine control strategies. Identification of many novel S1 genotypes of IBV in the USA is evidence that commercial flocks will be challenged today and in the future with strains unrelated to vaccines. In Israel, monitoring flocks for novel IBV field isolates should continue given the identification of Israel/720/99, and perhaps others in the future. Strains selected for vaccination of commercial flocks should induce cross- protection against unrelated genotypes. Using diverse genotypes for vaccination may result in immunity against unrelated field strains.
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Hedrick, Ronald, and Herve Bercovier. Characterization and Control of KHV, A New Herpes Viral Pathogen of Koi and Common Carp. United States Department of Agriculture, January 2004. http://dx.doi.org/10.32747/2004.7695871.bard.

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In this project we proposed to characterize the virus genome and the structural virion polypeptides to allow development of improved diagnostic approaches and potential vaccination strategies. These goals have been mostly achieved and the corresponding data were published in three papers (see below) and three more manuscripts are in preparation. The virion polypeptides of KHV strains isolated from USA (KHV-U) and Israel (KHV-I) were found to be identical. Purified viral DNA analyzed with a total of 5 restriction enzymes demonstrated no fragment length polymorphism between KHV-I and KHV-U but both KHV isolates differed significantly from the cyprinid herpesvirus (CHV) and the ictalurid herpesvirus (channel catfish virus or CCV). Using newly obtained viral DNA sequences two different PCR assays were developed that need to be now further tested in the field. We determined by pulse field analysis that the size of KHV genome is around 280 kbp (1-1. Bercovier, unpublished results). Sequencing of the viral genome of KHV has reached the stage where 180 kbp are sequenced (twice and both strands). Four hypothetical genes were detected when DNA sequences were translated into amino acid sequences. The finding of a gene of real importance, the thymidine kinase (TK) led us to extend the study of this specific gene. Four other genes related to DNA synthesis were found. PCR assays based on defined sequences were developed. The PCR assay based on TK gene sequence has shown improved sensitivity in the detection of KHV DNA compared to regular PCR assays. </P> <P><SPAN>With the ability to induce experimental infections in koi with KHV under controlled laboratory conditions we have studied the progress and distribution of virus in host tissues, the development of immunity and the establishment of latent infections. Also, we have investigated the important role of water temperature on severity of infections and mortality of koi following infections with KHV. These initial studies need to be followed by an increased focus on long-term fate of the virus in survivors. This is essential in light of the current &quot;controlled exposure program&quot; used by farmers to produce KHV &quot;naturally resistant fish&quot; that may result in virus or DNA carriers. </SPAN></P> <P><SPAN>The information gained from the research of this project was designed to allow implementation of control measures to prevent the spread of the virus both by improved diagnostic approaches and preventive measures. We have accomplished most of these goals but further studies are needed to establish even more reliable methods of prevention with increased emphases on improved diagnosis and a better understanding of the ecology of KHV. </SPAN>
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Berube, Paul M., Scott M. Gifford, Bonnie Hurwitz, Bethany Jenkins, Adrian Marchetti, and Alyson E. Santoro. Roadmap Towards Communitywide Intercalibration and Standardization of Ocean Nucleic Acids ‘Omics Measurements. Woods Hole Oceanographic Institution, March 2022. http://dx.doi.org/10.1575/1912/28054.

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In January 2020, the US Ocean Carbon & Biogeochemistry (OCB) Project Office funded the Ocean Nucleic Acids 'omics Intercalibration and Standardization workshop held at the University of North Carolina in Chapel Hill. Thirty-two participants from across the US, along with guests from Canada and France, met to develop a framework for standardization and intercalibration (S&I) of ocean nucleic acid ‘omics (na’omics) approaches (i.e., amplicon sequencing, metagenomics and metatranscriptomics). During the three-day workshop, participants discussed numerous topics, including: a) sample biomass collection and nucleic acid preservation for downstream analysis, b) extraction protocols for nucleic acids, c) addition of standard reference material to nucleic acid isolation protocols, d) isolation methods unique to RNA, e) sequence library construction, and f ) integration of bioinformatic considerations. This report provides a summary of these and other topics covered during the workshop and a series of recommendations for future S&I activities for na’omics approaches.
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Cohen, Yuval, Christopher A. Cullis, and Uri Lavi. Molecular Analyses of Soma-clonal Variation in Date Palm and Banana for Early Identification and Control of Off-types Generation. United States Department of Agriculture, October 2010. http://dx.doi.org/10.32747/2010.7592124.bard.

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Date palm (Phoenix dactylifera L.) is the major fruit tree grown in arid areas in the Middle East and North Africa. In the last century, dates were introduced to new regions including the USA. Date palms are traditionally propagated through offshoots. Expansion of modern date palm groves led to the development of Tissue Culture propagation methods that generate a large number of homogenous plants, have no seasonal effect on plant source and provide tools to fight the expansion of date pests and diseases. The disadvantage of this procedure is the occurrence of off-type trees which differ from the original cultivar. In the present project we focused on two of the most common date palm off-types: (1) trees with reduced fruit setting, in which most of the flowers turn into three-carpel parthenocarpic fruits. In a severe form, multi-carpel flowers and fruitlets (with up to six or eight carpels instead of the normal three-carpel flowers) are also formed. (2) dwarf trees, having fewer and shorter leaves, very short trunk and are not bearing fruits at their expected age, compared to the normal trees. Similar off-types occur in other crop species propagated by tissue culture, like banana (mainly dwarf plants) or oil palm (with a common 'Mantled' phenotype with reduced fruit setting and occurrence of supernumerary carpels). Some off-types can only be detected several years after planting in the fields. Therefore, efficient methods for prevention of the generation of off-types, as well as methods for their detection and early removal, are required for date palms, as well as for other tissue culture propagated crops. This research is aimed at the understanding of the mechanisms by which off-types are generated, and developing markers for their early identification. Several molecular and genomic approaches were applied. Using Methylation Sensitive AFLP and bisulfite sequencing, we detected changes in DNA methylation patterns occurring in off-types. We isolated and compared the sequence and expression of candidate genes, genes related to vegetative growth and dwarfism and genes related to flower development. While no sequence variation were detected, changes in gene expression, associated with the severity of the "fruit set" phenotype were detected in two genes - PdDEF (Ortholog of rice SPW1, and AP3 B type MADS box gene), and PdDIF (a defensin gene, highly homologous to the oil palm gene EGAD). We applied transcriptomic analyses, using high throughput sequencing, to identify genes differentially expressed in the "palm heart" (the apical meristem and the region of embryonic leaves) of dwarf vs. normal trees. Among the differentially expressed genes we identified genes related to hormonal biosynthesis, perception and regulation, genes related to cell expansion, and genes related to DNA methylation. Using Representation Difference Analyses, we detected changes in the genomes of off-type trees, mainly chloroplast-derived sequences that were incorporated in the nuclear genome and sequences of transposable elements. Sequences previously identified as differing between normal and off-type trees of oil palms or banana, successfully identified variation among date palm off-types, suggesting that these represent highly labile regions of monocot genomes. The data indicate that the date palm genome, similarly to genomes of other monocot crops as oil palm and banana, is quite unstable when cells pass through a cycle of tissue culture and regeneration. Changes in DNA sequences, translocation of DNA fragments and alteration of methylation patterns occur. Consequently, patterns of gene expression are changed, resulting in abnormal phenotypes. The data can be useful for future development of tools for early identification of off-type as well as for better understanding the phenomenon of somaclonal variation during propagation in vitro.
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Barefoot, Susan F., Bonita A. Glatz, Nathan Gollop, and Thomas A. Hughes. Bacteriocin Markers for Propionibacteria Gene Transfer Systems. United States Department of Agriculture, June 2000. http://dx.doi.org/10.32747/2000.7573993.bard.

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The antibotulinal baceriocins, propionicin PLG-1 and jenseniin G., were the first to be identified, purified and characterized for the dairy propionibaceria and are produced by Propionibacterium thoenii P127 and P. thoenii/jensenii P126, respectively. Objectives of this project were to (a) produce polyclonal antibodies for detection, comparison and monitoring of propionicin PLG-1; (b) identify, clone and characterize the propionicin PLG-1 (plg-1) and jenseniin G (jnG) genes; and (3) develop gene transfer systems for dairy propionibacteria using them as models. Polyclonal antibodies for detection, comparison and monitoring of propionicin PLG-1 were produced in rabbits. Anti-PLG-1 antiserum had high titers (256,000 to 512,000), neutralized PLG-1 activity, and detected purified PLG-1 at 0.10 mg/ml (indirect ELISA) and 0.033 mg/ml (competitive indirect ELISA). Thirty-nine of 158 strains (most P. thoenii or P. jensenii) yielded cross-reacting material; four strains of P. thoenii, including two previously unidentified bacteriocin producers, showed biological activity. Eight propionicin-negative P127 mutants produced neither ELISA response nor biological activity. Western blot analyses of supernates detected a PLG-1 band at 9.1 kDa and two additional protein bands with apparent molecular weights of 16.2 and 27.5 kDa. PLG-1 polyclonal antibodies were used for detection of jenseniin G. PLG-1 antibodies neutralized jenseniin G activity and detected a jenseniin G-sized, 3.5 kDa peptide. Preliminary immunoprecipitation of crude preparations with PLG-1 antibodies yielded three proteins including an active 3-4 kDa band. Propionicin PLG-1 antibodies were used to screen a P. jensenii/thoenii P126 genomic expression library. Complete sequencing of a cloned insert identified by PLG-1 antibodies revealed a putative response regulator, transport protein, transmembrane protein and an open reading frame (ORF) potentially encoding jenseniin G. PCR cloning of the putative plg-1 gene yielded a 1,100 bp fragment with a 355 bp ORF encoding 118 amino acids; the deduced N-terminus was similar to the known PLG-1 N-terminus. The 118 amino acid sequence deduced from the putative plg-1 gene was larger than PLG-1 possibly due to post-translational processing. The product of the putative plg-1 gene had a calculated molecular weight of 12.8 kDa, a pI of 11.7, 14 negatively charged residues (Asp+Glu) and 24 positively charged residues (Arg+Lys). The putative plg-1 gene was expressed as an inducible fusion protein with a six-histidine residue tag. Metal affinity chromatography of the fused protein yielded a homogeneous product. The fused purified protein sequence matched the deduced putative plg-1 gene sequence. The data preliminarily suggest that both the plg-1 and jnG genes have been identified and cloned. Demonstrating that antibodies can be produced for propionicin PLG-1 and that those antibodies can be used to detect, monitor and compare activity throughout growth and purification was an important step towards monitoring PLG-1 concentrations in food systems. The unexpected but fortunate cross-reactivity of PLG-1 antibodies with jenseniin G led to selective recovery of jenseniin G by immunoprecipitation. Further refinement of this separation technique could lead to powerful affinity methods for rapid, specific separation of the two bacteriocins and thus facilitate their availability for industrial or pharmaceutical uses. Preliminary identification of genes encoding the two dairy propionibacteria bacteriocins must be confirmed; further analysis will provide means for understanding how they work, for increasing their production and for manipulating the peptides to increase their target species. Further development of these systems would contribute to basic knowledge about dairy propionibacteria and has potential for improving other industrially significant characteristics.
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Levisohn, Sharon, Maricarmen Garcia, David Yogev, and Stanley Kleven. Targeted Molecular Typing of Pathogenic Avian Mycoplasmas. United States Department of Agriculture, January 2006. http://dx.doi.org/10.32747/2006.7695853.bard.

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Intraspecies identification (DNA "fingerprinting") of pathogenic avian mycoplasmas is a powerful tool for epidemiological studies and monitoring strain identity. However the only widely method available for Mycoplasma gallisepticum (MG) and M. synoviae (MS)wasrandom amplified polymorphic DNA (RAPD). This project aimed to develop alternative and supplementary typing methods that will overcome the major constraints of RAPD, such as the need for isolation of the organism in pure culture and the lack of reproducibility intrinsic in the method. Our strategy focussed on recognition of molecular markers enabling identification of MG and MS vaccine strains and, by extension, pathogenic potential of field isolates. Our first aim was to develop PCR-based systems which will allow amplification of specific targeted genes directly from clinical material. For this purpose we evaluated the degree of intraspecies heterogeneity in genes encoding variable surface antigens uniquely found in MG all of which are putative pathogenicity factors. Phylogenic analysis of targeted sequences of selected genes (pvpA, gapA, mgc2, and lp) was employed to determine the relationship among MG strains.. This method, designated gene targeted sequencing (GTS), was successfully employed to identify strains and to establish epidemiologically-linked strain clusters. Diagnostic PCR tests were designed and validated for each of the target genes, allowing amplification of specific nucleotide sequences from clinical samples. An mgc2-PCR-RFLP test was designed for rapid differential diagnosis of MG vaccine strains in Israel. Addressing other project goals, we used transposon mutagenesis and in vivo and in vitro models for pathogenicity to correlated specific changes in target genes with biological properties that may impact the course of infection. An innovative method for specific detection and typing of MS strains was based on the hemagglutinin-encoding gene vlhA, uniquely found in this species. In parallel, we evaluated the application of amplified fragment length polymorphism (AFLP) in avian mycoplasmas. AFLP is a highly discriminatory method that scans the entire genome using infrequent restriction site PCR. As a first step the method was found to be highly correlated with other DNA typing methods for MG species and strain differentiation. The method is highly reproducible and relatively rapid, although it is necessary to isolate the strain to be tested. Both AFLP and GTS are readily to amenable to computer-assisted analysis of similarity and construction of a data-base resource. The availability of improved and diverse tools will help realize the full potential of molecular typing of avian mycoplasmas as an integral and essential part of mycoplasma control programs.
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Weller, Joel I., Derek M. Bickhart, Micha Ron, Eyal Seroussi, George Liu, and George R. Wiggans. Determination of actual polymorphisms responsible for economic trait variation in dairy cattle. United States Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7600017.bard.

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The project’s general objectives were to determine specific polymorphisms at the DNA level responsible for observed quantitative trait loci (QTLs) and to estimate their effects, frequencies, and selection potential in the Holstein dairy cattle breed. The specific objectives were to (1) localize the causative polymorphisms to small chromosomal segments based on analysis of 52 U.S. Holstein bulls each with at least 100 sons with high-reliability genetic evaluations using the a posteriori granddaughter design; (2) sequence the complete genomes of at least 40 of those bulls to 20 coverage; (3) determine causative polymorphisms based on concordance between the bulls’ genotypes for specific polymorphisms and their status for a QTL; (4) validate putative quantitative trait variants by genotyping a sample of Israeli Holstein cows; and (5) perform gene expression analysis using statistical methodologies, including determination of signatures of selection, based on somatic cells of cows that are homozygous for contrasting quantitative trait variants; and (6) analyze genes with putative quantitative trait variants using data mining techniques. Current methods for genomic evaluation are based on population-wide linkage disequilibrium between markers and actual alleles that affect traits of interest. Those methods have approximately doubled the rate of genetic gain for most traits in the U.S. Holstein population. With determination of causative polymorphisms, increasing the accuracy of genomic evaluations should be possible by including those genotypes as fixed effects in the analysis models. Determination of causative polymorphisms should also yield useful information on gene function and genetic architecture of complex traits. Concordance between QTL genotype as determined by the a posteriori granddaughter design and marker genotype was determined for 30 trait-by-chromosomal segment effects that are segregating in the U.S. Holstein population; a probability of <10²⁰ was used to accept the null hypothesis that no segregating gene within the chromosomal segment was affecting the trait. Genotypes for 83 grandsires and 17,217 sons were determined by either complete sequence or imputation for 3,148,506 polymorphisms across the entire genome. Variant sites were identified from previous studies (such as the 1000 Bull Genomes Project) and from DNA sequencing of bulls unique to this project, which is one of the largest marker variant surveys conducted for the Holstein breed of cattle. Effects for stature on chromosome 11, daughter pregnancy rate on chromosome 18, and protein percentage on chromosome 20 met 3 criteria: (1) complete or nearly complete concordance, (2) nominal significance of the polymorphism effect after correction for all other polymorphisms, and (3) marker coefficient of determination >40% of total multiple-regression coefficient of determination for the 30 polymorphisms with highest concordance. The missense polymorphism Phe279Tyr in GHR at 31,909,478 base pairs on chromosome 20 was confirmed as the causative mutation for fat and protein concentration. For effect on fat percentage, 12 additional missensepolymorphisms on chromosome 14 were found that had nearly complete concordance with the suggested causative polymorphism (missense mutation Ala232Glu in DGAT1). The markers used in routine U.S. genomic evaluations were increased from 60,000 to 80,000 by adding markers for known QTLs and markers detected in BARD and other research projects. Objectives 1 and 2 were completely accomplished, and objective 3 was partially accomplished. Because no new clear-cut causative polymorphisms were discovered, objectives 4 through 6 were not completed.
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