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Journal articles on the topic 'Sequence analysis DNA'

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Published: 4 June 2021

Last updated: 29 January 2023

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1

Karlin, S., and L. R. Cardon. "Computational DNA Sequence Analysis." Annual Review of Microbiology 48, no. 1 (1994): 619–54. http://dx.doi.org/10.1146/annurev.mi.48.100194.003155.

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2

CAO, YINHE, WEN-WEN TUNG, J. B. GAO, and YAN QI. "RECURRENCE TIME STATISTICS: VERSATILE TOOLS FOR GENOMIC DNA SEQUENCE ANALYSIS." Journal of Bioinformatics and Computational Biology 03, no. 03 (2005): 677–96. http://dx.doi.org/10.1142/s0219720005001235.

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With the completion of the human and a few model organisms' genomes, and with the genomes of many other organisms waiting to be sequenced, it has become increasingly important to develop faster computational tools which are capable of easily identifying the structures and extracting features from DNA sequences. One of the more important structures in a DNA sequence is repeat-related. Often they have to be masked before protein coding regions along a DNA sequence are to be identified or redundant expressed sequence tags (ESTs) are to be sequenced. Here we report a novel recurrence time-based me

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3

Barna, J. "DNA and Protein Sequence Analysis." Journal of Medical Genetics 34, no. 11 (1997): 959–60. http://dx.doi.org/10.1136/jmg.34.11.959-a.

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4

Zu-Guo, Yu, Vo Anh, Gong Zhi-Min, and Long Shun-Chao. "Fractals in DNA sequence analysis." Chinese Physics 11, no. 12 (2002): 1313–18. http://dx.doi.org/10.1088/1009-1963/11/12/318.

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5

Sass, Philip M. "DNA AND PROTEIN SEQUENCE ANALYSIS." Shock 8, no. 2 (1997): 156. http://dx.doi.org/10.1097/00024382-199708000-00021.

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6

Chen, Fei, and Yuan-Ting Zhang. "A DNA Structure-Based Bionic Wavelet Transform and Its Application to DNA Sequence Analysis." Applied Bionics and Biomechanics 1, no. 1 (2003): 3–9. http://dx.doi.org/10.1155/2003/675645.

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DNA sequence analysis is of great significance for increasing our understanding of genomic functions. An important task facing us is the exploration of hidden structural information stored in the DNA sequence. This paper introduces a DNA structure-based adaptive wavelet transform (WT) – the bionic wavelet transform (BWT) – for DNA sequence analysis. The symbolic DNA sequence can be separated into four channels of indicator sequences. An adaptive symbol-to-number mapping, determined from the structural feature of the DNA sequence, was introduced into WT. It can adjust the weight value of each c

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7

Song, Young-Ohk, and Duk-Jin Chang. "Unification System for Analysis of DNA Sequence." Journal of the Korea Contents Association 11, no. 3 (2011): 65–72. http://dx.doi.org/10.5392/jkca.2011.11.3.065.

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8

Onasanya, A., M. M. Ekperigin, R. O. Onasanya, et al. "DNA Sequencing Analysis of African Xanthomonas oryzae pv. oryzae Virulence Gene (AXaVrg) DNA Marker." Scientia Agriculturae Bohemica 49, no. 2 (2018): 78–86. http://dx.doi.org/10.2478/sab-2018-0012.

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Abstract Global rice production is constrained by bacterial leaf blight (BLB) disease caused by Xanthomonas oryzae pv. oryzae (Xoo). BLB disease incidence in West Africa was between 70–85% and yield loss in farmers’ fields was in the range of 50–90% from 2005 to 2010. In the present study, African Xoo virulence gene OPP-172000 DNA marker was identified and purified using randomly amplified polymorphic DNA polymerase chain reaction (RAPD-PCR) products from 50 Xoo isolates. Genomic DNA of 50 Xoo isolates were analyzed using OPP-17 primer in RAPD-PCR during which African Xoo virulence gene OPP-17

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9

BAKER, ANDREW R., and JOHN SHINE. "Human Kidney Kallikrein: cDNA Cloning and Sequence Analysis." DNA 4, no. 6 (1985): 445–50. http://dx.doi.org/10.1089/dna.1985.4.445.

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10

KIM, MYOUNG HEE, HWA-HYOUNG CHANG, CHUOG SHIN, MYUNGSUN CHO, DALKEUN PARK, and HYOUNG WOO PARK. "Genomic Structure and Sequence Analysis of HumanHOXA-9." DNA and Cell Biology 17, no. 5 (1998): 407–14. http://dx.doi.org/10.1089/dna.1998.17.407.

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11

Karlin, S., and G. Ghandour. "Comparative statistics for DNA and protein sequences: single sequence analysis." Proceedings of the National Academy of Sciences 82, no. 17 (1985): 5800–5804. http://dx.doi.org/10.1073/pnas.82.17.5800.

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12

Karlin, S., and G. Ghandour. "Comparative statistics for DNA and protein sequences: multiple sequence analysis." Proceedings of the National Academy of Sciences 82, no. 18 (1985): 6186–90. http://dx.doi.org/10.1073/pnas.82.18.6186.

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13

Wu, Paula, Ngai Fong Law, and Wan Chi Siu. "Analysis of cross sequence similarities for multiple DNA sequences compression." International Journal of Computer Aided Engineering and Technology 1, no. 4 (2009): 437. http://dx.doi.org/10.1504/ijcaet.2009.028551.

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14

Graham, Duncan, and Karen Faulds. "Quantitative SERRS for DNA sequence analysis." Chemical Society Reviews 37, no. 5 (2008): 1042. http://dx.doi.org/10.1039/b707941a.

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15

Ludwig, Michael, and Robert J. Hartzman. "Video analysis of DNA sequence homologs." Analytical Chemistry 64, no. 22 (1992): 2678–81. http://dx.doi.org/10.1021/ac00046a005.

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16

Chatterjee, Samprit, and B. S. Weir. "Statistical Analysis of DNA Sequence Data." Journal of the American Statistical Association 80, no. 390 (1985): 495. http://dx.doi.org/10.2307/2287952.

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17

Vona, G., M. E. Ghiani, C. M. Calò, L. Vacca, M. Memmì, and L. Varesi. "Mitochondrial DNA sequence analysis in Sicily." American Journal of Human Biology 13, no. 5 (2001): 576–89. http://dx.doi.org/10.1002/ajhb.1096.

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18

Mallon, Ann-Marie, and Mark Strivens. "DNA Sequence Analysis and Comparative Sequencing." Methods 14, no. 2 (1998): 160–78. http://dx.doi.org/10.1006/meth.1997.0575.

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19

Szopa, J. "Expression analysis of a Cucurbita cDNA encoding endonuclease." Acta Biochimica Polonica 42, no. 2 (1995): 183–89. http://dx.doi.org/10.18388/abp.1995_4643.

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The nuclear matrices of plant cell nuclei display intrinsic nuclease activity which consists in nicking supercoiled DNA. A cDNA encoding a 32 kDa endonuclease has been cloned and sequenced. The nucleotide and deduced amino-acid sequences show high homology to known 14-3-3 protein sequences from other sources. The amino-acid sequence shows agreement with consensus sequences for potential phosphorylation by protein kinase A and C and for calcium, lipid and membrane-binding sites. The nucleotide-binding site is also present within the conserved part of the sequence. By Northern blot analysis, the

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20

Leung, F. C., M. Welt, R. D. Quesenberry, and X.-Z. Shen. "DNA Fingerprinting and Cloning of Hypervariable Minisatellite Repeats in Salmonids." Canadian Journal of Fisheries and Aquatic Sciences 51, S1 (1994): 258–66. http://dx.doi.org/10.1139/f94-312.

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We used heterologous Jeffreys' 33.6 core sequence and microsatellites (CAC)5 and (CA)12 as probes and compared them with probes based on the minisatellite sequences from tilapia (Oreochromis niloticus) and Atlantic salmon (Salmo salar) in fingerprinting assays. DNA fingerprints generated with the Jeffreys' 33.6 core sequence and the microsatellite (CAC)5 and (CA)12 probes showed complex profiles with high background, but DNA fingerprints using the tilapia and Atlantic salmon probes showed clear, less complex, informative, individual-specific DNA fingerprints suitable for analysis. We cloned an

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21

WABIKO, HIROETSU, KATHLEEN C. RAYMOND, and LEE A. BULLA. "Bacillus thuringiensisEntomocidal Protoxin Gene Sequence and Gene Product Analysis." DNA 5, no. 4 (1986): 305–14. http://dx.doi.org/10.1089/dna.1986.5.305.

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22

MADISEN, LINDA, NANCY R. WEBB, TIMOTHY M. ROSE та ін. "Transforming Growth Factor-β2: cDNA Cloning and Sequence Analysis". DNA 7, № 1 (1988): 1–8. http://dx.doi.org/10.1089/dna.1988.7.1.

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23

XIN, XIAONAN, ROBERT DAY, WEIJIA DONG, YINGHONG LEI, and LLOYD D. FRICKER. "Cloning, Sequence Analysis, and Distribution of Rat Metallocarboxypeptidase z." DNA and Cell Biology 17, no. 4 (1998): 311–19. http://dx.doi.org/10.1089/dna.1998.17.311.

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24

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 (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 t

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25

Burt, D. W., I. R. Paton та B. R. Dey. "Comparative analysis of human and chicken transforming growth factor-β2 and -β3 promoters". Journal of Molecular Endocrinology 7, № 3 (1991): 175–83. http://dx.doi.org/10.1677/jme.0.0070175.

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ABSTRACT The promoters for chicken transforming growth factor-β2 (TGF-β2) and TGF-β3 were cloned and sequenced to study the regulation of these genes. The promoters are GC-rich and lie within CpG islands. Several putative DNA regulatory sequence motifs were identified in the 5′-flanking regions, including matches to particular recognition sequences for several nuclear factors found in other genes. A comparison of chicken and human TGF-β2 promoters revealed a 111 bp conserved sequence surrounding the major transcription start site. Two regions of sequence homology were detected in the 5′-flanki

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26

Begum, RA, MT Alam, H. Jahan, and MS Alam. "Partial sequence analysis of mitochondrial cytochrome B gene of Labeo calbasu of Bangladesh." Journal of Biodiversity Conservation and Bioresource Management 5, no. 1 (2019): 25–30. http://dx.doi.org/10.3329/jbcbm.v5i1.42182.

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Labeo calbasu (Family Cyprinidae) was studied at DNA level to know genetic diversity within and between species. The mitochondrial cytochrome b (cyt-b) gene of L. calbasu was sequenced and compared to the corresponding sequences of other Labeo species. DNA was isolated from the tissue sample of L. calbasu using phenol: chloroform extraction method. Forward and reverse primers were designed to amplify the target region of cytochrome b gene. A standard PCR protocol was used for the amplification of the desired region. Then, the forward and reverse sequences obtained were aligned and edited to fi

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27

Hsu, Tai-Hsin, and Su-Long Nyeo. "Simple Deviation Analysis of Two-Dimensional Viral DNA Walks." Journal of Biological Systems 11, no. 03 (2003): 221–43. http://dx.doi.org/10.1142/s0218339003000841.

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We consider the method of two-dimensional DNA walks based on three independent groups of mapping rules for 21 DNA sequences of animal and plant viruses, and for the sequences of irrational and random numbers. This method provides a visualization tool for the determination of the regional abundance of nucleotides in DNA sequences. By defining a statistical deviation and a maximum-deviation ratio for a DNA walk, we find that the maximum-deviation ratios for the 21 viral DNA sequences are generally larger than those of the random-number sequences of same lengths. It is shown that the viral DNA se

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28

Nhung, Pham Hong, Hiroyuki Hata, Kiyofumi Ohkusu, et al. "Use of the novel phylogenetic marker dnaJ and DNA–DNA hybridization to clarify interrelationships within the genus Aeromonas." International Journal of Systematic and Evolutionary Microbiology 57, no. 6 (2007): 1232–37. http://dx.doi.org/10.1099/ijs.0.64957-0.

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The interrelationships of 27 Aeromonas strains were investigated using dnaJ sequences and DNA–DNA hybridization. dnaJ sequence similarities showed a stronger relationship with DNA–DNA relatedness values than did 16S rRNA gene sequence similarities. Additionally, dnaJ sequence analysis, with interspecies divergence over 5.2 % in most cases, gave better resolution than 16S rRNA gene sequences for the differentiation of strains at the species level. Relationships among Aeromonas species were therefore elucidated on the basis of dnaJ sequences and DNA–DNA reassociation. Strains of Aeromonas enchel

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29

Wei, Dan, Qingshan Jiang, and Sheng Li. "A New Approach for DNA Sequence Similarity Analysis based on Triplets of Nucleic Acid Bases." International Journal of Nanotechnology and Molecular Computation 2, no. 4 (2010): 1–11. http://dx.doi.org/10.4018/978-1-60960-064-8.ch006.

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Similarity analysis of DNA sequences is a fundamental research area in Bioinformatics. The characteristic distribution of L-tuple, which is the tuple of length L, reflects the valuable information contained in a biological sequence and thus may be used in DNA sequence similarity analysis. However, similarity analysis based on characteristic distribution of L-tuple is not effective for the comparison of highly conservative sequences. In this paper, a new similarity measurement approach based on Triplets of Nucleic Acid Bases (TNAB) is introduced for DNA sequence similarity analysis. The new app

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30

Krishnan, Gopal, Rajinder K. Kaul, and Pudur Jagadeeswaran. "DNA sequence analysis: a procedure to find homologies among many sequences." Nucleic Acids Research 14, no. 1 (1986): 543–50. http://dx.doi.org/10.1093/nar/14.1.543.

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31

Siegel, Andrew F., Barbara Trask, Jared C. Roach, Gregory G. Mahairas, Leroy Hood, and Ger van den Engh. "Analysis of Sequence-Tagged-Connector Strategies for DNA Sequencing." Genome Research 9, no. 3 (1999): 297–307. http://dx.doi.org/10.1101/gr.9.3.297.

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The BAC-end sequencing, or sequence-tagged-connector (STC), approach to genome sequencing involves sequencing the ends of BAC inserts to scatter sequence tags (STCs) randomly across the genome. Once any BAC or other large segment of DNA is sequenced to completion by conventional shotgun approaches, these STC tags can be used to identify a minimum tiling path of BAC clones overlapping the nucleation sequence for sequence extension. Here, we explore the properties of STC-sequencing strategies within a mathematical model of a random target with homologous repeats and imperfect sequencing technolo

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32

FITZGERALD, MARY C., and MARGARET A. FLANAGAN. "Characterization and Sequence Analysis of the Human Ornithine Decarboxylase Gene." DNA 8, no. 9 (1989): 623–34. http://dx.doi.org/10.1089/dna.1.1989.8.623.

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33

CHEN, H., Y. SUN, T. STARK, W. BEATTIE, and R. E. MOSES. "Nucleotide Sequence and Deletion Analysis of thepolB Gene ofEscherichia coli." DNA and Cell Biology 9, no. 9 (1990): 631–35. http://dx.doi.org/10.1089/dna.1990.9.631.

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34

XIN, XIAONAN, OLEG VARLAMOV, ROBERT DAY, et al. "Cloning and Sequence Analysis of cDNA Encoding Rat Carboxypeptidase D." DNA and Cell Biology 16, no. 7 (1997): 897–909. http://dx.doi.org/10.1089/dna.1997.16.897.

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35

Li, Zhentao, and Mathieu Blanchette. "The Difficulty In Computing Ancestral DNA Sequences: Using Computational Analysis To Reconstruct DNA Sequences." McGill Science Undergraduate Research Journal 1, no. 1 (2006): 24–26. http://dx.doi.org/10.26443/msurj.v1i1.153.

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Intriguing work has been carried out in order to decipher the genetic codes of today’s existing species. However, little is known about the genetic makeup of species that existed long ago. Exciting possibilities have recently been raised in the field of computational analysis (1), proposing that reconstruction of ancestral DNA sequences can be performed if the DNA sequences of the existing species are known. Being able to perform such reconstructions would simplify the study of the evolution of these species, and uncover many mysteries regarding life that once existed on this planet. In

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36

Hanif, Waqar, Hijab Fatima, Muhammad Qasim, Rana Muhammad Atif, and Muhammad Rizwan Javed. "SeqDown: An Efficient Sequence Retrieval Software and Comparative Sequence Retrieval Analysis." Current Trends in OMICS 1, no. 1 (2021): 18–29. http://dx.doi.org/10.32350/cto.11.03.

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For any sequence analysis procedure, a single or multiple sequence must be retrieved, stored, organized. One of the most common public databases used for biological sequence retrieval is GenBank which is a comprehensive public database of nucleotide sequences. However, as the length of the sequence to be retrieved increases such as a chromosome, entire genome, scaffold, etc., the elapsed time to download the file gets even elongated due to slower bandwidth to download/retrieve the sequence.[8] In most cases, during sequence analysis, the researcher requires messenger RNA (mRNA), RNA, DNA, prot

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37

Hansen, Scott G., Lisa I. Strelow, David C. Franchi, David G. Anders, and Scott W. Wong. "Complete Sequence and Genomic Analysis of Rhesus Cytomegalovirus." Journal of Virology 77, no. 12 (2003): 6620–36. http://dx.doi.org/10.1128/jvi.77.12.6620-6636.2003.

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ABSTRACT The complete DNA sequence of rhesus cytomegalovirus (RhCMV) strain 68-1 was determined with the whole-genome shotgun approach on virion DNA. The RhCMV genome is 221,459 bp in length and possesses a 49% G+C base composition. The genome contains 230 potential open reading frames (ORFs) of 100 or more codons that are arranged colinearly with counterparts of previously sequenced betaherpesviruses such as human cytomegalovirus (HCMV). Of the 230 RhCMV ORFs, 138 (60%) are homologous to known HCMV proteins. The conserved ORFs include the structural, replicative, and transcriptional regulator

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38

Wang, Li-Ting, Fwu-Ling Lee, Chun-Ju Tai, and Hiroaki Kasai. "Comparison of gyrB gene sequences, 16S rRNA gene sequences and DNA–DNA hybridization in the Bacillus subtilis group." International Journal of Systematic and Evolutionary Microbiology 57, no. 8 (2007): 1846–50. http://dx.doi.org/10.1099/ijs.0.64685-0.

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The Bacillus subtilis group comprises eight closely related species that are indistinguishable from one another by 16S rRNA gene sequence analysis. Therefore, the gyrB gene, which encodes the subunit B protein of DNA gyrase, was selected as an alternative phylogenetic marker. To determine whether gyrB gene sequence analysis could be used for phylogenetic analysis and species identification of members of the B. subtilis group, the congruence of gyrB grouping with both 16S rRNA gene sequencing and DNA–DNA hybridization data was evaluated. Ranges of gyrB nucleotide and translated amino acid seque

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39

Kinsner, Witold, and Hong Zhang. "Multi-Fractal Analysis for Feature Extraction from DNA Sequences." International Journal of Software Science and Computational Intelligence 2, no. 2 (2010): 1–18. http://dx.doi.org/10.4018/jssci.2010040101.

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This paper presents estimations of multi-scale (multi-fractal) measures for feature extraction from deoxyribonucleic acid (DNA) sequences, and demonstrates the intriguing possibility of identifying biological functionality using information contained within the DNA sequence. We have developed a technique that seeks patterns or correlations in the DNA sequence at a higher level than the local base-pair structure. The technique has three main steps: (i) transforms the DNA sequence symbols into a modified Lévy walk, (ii) transforms the Lévy walk into a signal spectrum, and (iii) breaks the spectr

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40

Degani, G. "Mitochondrial DNA sequence analysis in Anabantoidei fish." Advances in Biological Chemistry 03, no. 03 (2013): 347–55. http://dx.doi.org/10.4236/abc.2013.33039.

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41

Yang, Ziheng, and Tianlin Wang. "Mixed Model Analysis of DNA Sequence Evolution." Biometrics 51, no. 2 (1995): 552. http://dx.doi.org/10.2307/2532943.

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42

GELFAND, M. S. "Prediction of Function in DNA Sequence Analysis." Journal of Computational Biology 2, no. 1 (1995): 87–115. http://dx.doi.org/10.1089/cmb.1995.2.87.

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43

Gingeras, Thomas R. "Nucleic Acid Sequence Analysis Using DNA Chips." Diagnostic Molecular Pathology 3, no. 3 (1994): 216. http://dx.doi.org/10.1097/00019606-199409000-00033.

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44

LiMin Fu. "An expert network for DNA sequence analysis." IEEE Intelligent Systems 14, no. 1 (1999): 65–71. http://dx.doi.org/10.1109/5254.747907.

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45

Smith, Lloyd M., Jane Z. Sanders, Robert J. Kaiser, et al. "Fluorescence detection in automated DNA sequence analysis." Nature 321, no. 6071 (1986): 674–79. http://dx.doi.org/10.1038/321674a0.

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46

Kirpekar, F. "DNA sequence analysis by MALDI mass spectrometry." Nucleic Acids Research 26, no. 11 (1998): 2554–59. http://dx.doi.org/10.1093/nar/26.11.2554.

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47

Jeong, Byeong-Soo, A. T. M. Golam Bari, Mst Rokeya Reaz, Seokhee Jeon, Chae-Gyun Lim, and Ho-Jin Choi. "Codon-based encoding for DNA sequence analysis." Methods 67, no. 3 (2014): 373–79. http://dx.doi.org/10.1016/j.ymeth.2014.01.016.

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48

Joshi, Yadnyesh, and Sathish Vadhiyar. "Analysis of DNA sequence transformations on grids." Journal of Parallel and Distributed Computing 69, no. 1 (2009): 80–90. http://dx.doi.org/10.1016/j.jpdc.2008.06.012.

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49

Abate, Adam R., Tony Hung, Ralph A. Sperling, et al. "DNA sequence analysis with droplet-based microfluidics." Lab on a Chip 13, no. 24 (2013): 4864. http://dx.doi.org/10.1039/c3lc50905b.

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50

Luo, Liaofu, and Fengmin Ji. "The Preferential Mode Analysis of DNA Sequence." Journal of Theoretical Biology 188, no. 3 (1997): 343–53. http://dx.doi.org/10.1006/jtbi.1997.0485.

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