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Journal articles on the topic 'X/Motif (Computer program)'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 February 2022

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1

Trush, V. A., N. S. Kariaka, I. S. Konovalova, S. V. Shishkina, and V. M. Amirkhanov. "Synthesis, crystal structure, Hirschfeld surface analysis and biological activity prediction of N-(dimethoxyphosphoryl)-1-methylpyridinium-4-carboximidate." Voprosy Khimii i Khimicheskoi Tekhnologii, no. 3 (May 2021): 137–44. http://dx.doi.org/10.32434/0321-4095-2021-136-3-137-144.

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N-(dimethoxyphosphoryl)-1-methylpyridinium-4-carboximidate, a new carbacylamidophosphate-type compound, was synthesized and characterized by means of IR, 1H and 31P NMR and UV-Vis spectroscopies and X-ray analysis. The molecule of the synthesized compound has triclinic (P-1) symmetry, displays monomeric motif in crystal and crystalizes as solvate containing methanol molecule, which is connected to carbacylamidophosphate molecule through O(2)H(5A)–O(5) hydrogen bond. Through – stacking interactions, the molecules of the synthesized compound are linked in the chain along the a crystallographic axis. Several other intermolecular bonds connect these chains along b and c crystallographic axes. The intermolecular interactions with HH and OH contacts prevail in the crystalline structure of N-(dimethoxyphosphoryl)-1-methylpyridinium-4-carboximidate, the contribution of planar stacking CC contacts being equal to 4.1%. The synthesized compound was found to be well soluble in water. By using computer program PASS, we established that the synthesized substance is likely can exhibit 18 types of biological activity in experiment.

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2

Kingsford, Carl, Elena Zaslavsky, and Mona Singh. "A cost-aggregating integer linear program for motif finding." Journal of Discrete Algorithms 9, no. 4 (December 2011): 326–34. http://dx.doi.org/10.1016/j.jda.2011.04.001.

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3

Negi, Surendra S., and Werner Braun. "Automated Detection of Conformational Epitopes Using Phage Display Peptide Sequences." Bioinformatics and Biology Insights 3 (January 2009): BBI.S2745. http://dx.doi.org/10.4137/bbi.s2745.

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Background Precise determination of conformational epitopes of neutralizing antibodies represents a key step in the rational design of novel vaccines. A powerful experimental method to gain insights on the physical chemical nature of conformational epitopes is the selection of linear peptides that bind with high affinities to a monoclonal antibody of interest by phage display technology. However, the structural characterization of conformational epitopes from these mimotopes is not straightforward, and in the past the interpretation of peptide sequences from phage display experiments focused on linear sequence analysis to find a consensus sequence or common sequence motifs. Results We present a fully automated search method, EpiSearch that predicts the possible location of conformational epitopes on the surface of an antigen. The algorithm uses peptide sequences from phage display experiments as input, and ranks all surface exposed patches according to the frequency distribution of similar residues in the peptides and in the patch. We have tested the performance of the EpiSearch algorithm for six experimental data sets of phage display experiments, the human epidermal growth factor receptor-2 (HER-2/neu), the antibody mAb Bo2C11 targeting the C2 domain of FVIII, antibodies mAb 17b and mAb b12 of the HIV envelope protein gp120, mAb 13b5 targeting HIV-1 capsid protein and 80R of the SARS coronavirus spike protein. In all these examples the conformational epitopes as determined by the X-ray crystal structures of the antibody-antigen complexes, were found within the highest scoring patches of EpiSearch, covering in most cases more than 50% residues of experimental observed conformational epitopes. Input options of the program include mapping of a single peptide or a set of peptides on the antigen structure, and the results of the calculation can be visualized on our interactive web server. Availability Users can access the EpiSearch from our web server http://curie.utmb.edu/episearch.html Contact webraun@utmb.edu

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4

LAMBKIN, C. L. "Computer Program Review." Australian Journal of Entomology 34, no. 4 (November 1995): 280. http://dx.doi.org/10.1111/j.1440-6055.1995.tb01340.x.

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5

Wood, Reg K. "Computer Process Control Program." Journal of Engineering Education 84, no. 1 (January 1995): 51–57. http://dx.doi.org/10.1002/j.2168-9830.1995.tb00146.x.

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6

Feroz, Khan, Sharma Richa, Shukla Rakesh Kumar, Meena Abha, Shasany Ajit Kumar, and Sharma Ashok. "Genomic Identification of SinR Transcription Factor Binding Sites in Nitrogen Fixing Bacterium Bradyrhizobium japonicum." Open Bioinformatics Journal 3, no. 1 (May 5, 2009): 8–17. http://dx.doi.org/10.2174/1875036200903010008.

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SinR is a transcription factor which controls expression of stress tolerance sin genes related to alternate development processes under stress condition. Identification of genome wide SinR-box motif and their regulated genes has not been worked out yet in Bradyrhizobium japonicum. For this, a weight matrix of 9 bp was developed from the known promoter sequences of Bacillus subtilis, which was then used for genome wide identification of co-regulated genes. The methodology first involves phylogenetic footprinting of SinR regulated genes and then construction of scoring matrix through ‘Consensus’ and confirmation through MEME & D-Matrix tools. Genomic prediction was done through ‘Patser’ program and confirmation through ‘PossumSearch’ program in Linux system. Results showed that all the 371 predicted genes belongs to 9 different functional classes, in which 221 found in operons with more than 80% Sin-box motif similarity. Similar approach can be used in other bacteria to explore hidden genomic regulatory network.

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7

ROSE, M. B., P. A. GEORGHIADES, and W. B. DOWSLAND. "A Computer Program for Urology." British Journal of Urology 57, no. 3 (June 1985): 257–60. http://dx.doi.org/10.1111/j.1464-410x.1985.tb06338.x.

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8

Findlay, A. "Review: The Shell Hacker's Guide to X and MOTIF." Computer Bulletin 37, no. 6 (December 1, 1995): 20. http://dx.doi.org/10.1093/combul/37.6.20-a.

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9

Glynn, John. "Exegetical and Bible Study Computer Program." Conversations in Religion & Theology 5, no. 1 (May 2007): 116–28. http://dx.doi.org/10.1111/j.1479-2214.2007.00109.x.

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10

Ngo, Vu, Mengchi Wang, and Wei Wang. "Finding de novo methylated DNA motifs." Bioinformatics 35, no. 18 (February 6, 2019): 3287–93. http://dx.doi.org/10.1093/bioinformatics/btz079.

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Abstract Motivation Increasing evidence has shown that nucleotide modifications such as methylation and hydroxymethylation on cytosine would greatly impact the binding of transcription factors (TFs). However, there is a lack of motif finding algorithms with the function to search for motifs with modified bases. In this study, we expand on our previous motif finding pipeline Epigram to provide systematic de novo motif discovery and performance evaluation on methylated DNA motifs. Results mEpigram outperforms both MEME and DREME on finding modified motifs in simulated data that mimics various motif enrichment scenarios. Furthermore we were able to identify methylated motifs in Arabidopsis DNA affinity purification sequencing (DAP-seq) data that were previously demonstrated to contain such motifs. When applied to TF ChIP-seq and DNA methylome data in H1 and GM12878, our method successfully identified novel methylated motifs that can be recognized by the TFs or their co-factors. We also observed spacing constraint between the canonical motif of the TF and the newly discovered methylated motifs, which suggests operative recognition of these cis-elements by collaborative proteins. Availability and implementation The mEpigram program is available at http://wanglab.ucsd.edu/star/mEpigram. Supplementary information Supplementary data are available at Bioinformatics online.

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11

Goff, Kathy J., and Rachel A. Fouts. "A Computer-Assisted Nursing QA Program." Journal For Healthcare Quality 11, no. 5 (October 1989): 26–29. http://dx.doi.org/10.1111/j.1945-1474.1989.tb00458.x.

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12

Maslia, Morris L. "Modifications to the Computer Program TENSOR2D." Ground Water 32, no. 3 (May 1994): 501–2. http://dx.doi.org/10.1111/j.1745-6584.1994.tb00668.x.

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13

Martins Costa, M. T. C., D. Rinaldi, and J. L. Rivail. "CHIMISTE: A quantum chemistry computer program." Journal of Molecular Structure: THEOCHEM 166 (June 1988): 125–28. http://dx.doi.org/10.1016/0166-1280(88)80424-x.

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14

Shrivastava, Falguni, Renuka Kendurkar, B. D. Shrivastava, and Ramji Yadav. "Computer Program for obtaining theoretical X-ray Satellite Spectrum." International Journal of Scientific Research in Physics and Applied Sciences 6, no. 3 (June 30, 2018): 9–17. http://dx.doi.org/10.26438/ijsrpas/v6i3.917.

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15

Nguyen, Jeffrey H., and Raymond Jeanloz. "A computer program to analyze x‐ray diffraction films." Review of Scientific Instruments 64, no. 12 (December 1993): 3456–61. http://dx.doi.org/10.1063/1.1144267.

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16

Cockwell, Kerri Y., and Ian G. Giles. "Software tools for motif and pattern scanning: program descriptions including a universal sequence reading algorithm." Bioinformatics 5, no. 3 (1989): 227–32. http://dx.doi.org/10.1093/bioinformatics/5.3.227.

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17

Burger, Andrew J. "Abstracts of original contributions: Computer application program." Journal of the American College of Cardiology 19, no. 3 (March 1992): 3A—17A. http://dx.doi.org/10.1016/s0735-1097(10)80302-x.

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18

Dzombak, David A., Sujoy B. Roy, and Hung-Jung Fang. "Air-Stripper Design and Costing Computer Program." Journal - American Water Works Association 85, no. 10 (October 1993): 63–72. http://dx.doi.org/10.1002/j.1551-8833.1993.tb06080.x.

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19

Reynolds, W. T. "THE ANAESTHETIC MACHINE, A COMPUTER TUTORIAL PROGRAM." Journal of Veterinary Anaesthesia 18 (August 1991): 137. http://dx.doi.org/10.1111/j.1467-2995.1991.tb00531.x.

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20

Bedewy, M. K., A. O. Sherif, and A. Y. Abdallah. "An interactive computer program for maintenance systems." Reliability Engineering & System Safety 25, no. 4 (January 1989): 349–64. http://dx.doi.org/10.1016/0951-8320(89)90063-x.

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21

ASHLEY, M. V., I. C. CABALLERO, W. CHAOVALITWONGSE, B. DASGUPTA, P. GOVINDAN, S. I. SHEIKH, and T. Y. BERGER-WOLF. "KINALYZER, a computer program for reconstructing sibling groups." Molecular Ecology Resources 9, no. 4 (July 2009): 1127–31. http://dx.doi.org/10.1111/j.1755-0998.2009.02562.x.

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22

Badger, John, R. Ajay Kumar, Ping Yip, and S�ndor Szalma. "New features and enhancements in the X-PLOR computer program." Proteins: Structure, Function, and Genetics 35, no. 1 (April 1, 1999): 25–33. http://dx.doi.org/10.1002/(sici)1097-0134(19990401)35:1<25::aid-prot3>3.0.co;2-v.

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23

Maris, Ingka, Kosala Dwidja Purnomo, and Bagus Juliyanto. "PEMANFAATAN ITERATED FUNCTION SYSTEM (IFS) UNTUK MEMBANGKITKAN MOTIF ANYAMAN UKURAN n x n." Majalah Ilmiah Matematika dan Statistika 21, no. 1 (March 26, 2021): 25. http://dx.doi.org/10.19184/mims.v21i1.23120.

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Woven is one of art thats very close to life. Woven has a pattern consisting of two-dimensional (2D) and has a basic pattern. Along with the development times, technology is also growing including computer technology. Computer can be used for mathematical calculation process, one of them is fractal. Fractal Sierpinski carpet is formed from a square that use Iterated Function System (IFS) method. This method is exact self-similar resulting in the same fractal with the original constituent object. The writer want to get woven pattern using computer technology, that is GUI application in Matlab that utilizes the IFS method on fractal. Woven patterns formed from woven that have a grid size of n x n and are given a few iterations. So, that it can make it easier for craftsmen to make woven pattern that are interesting and varied.

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24

Burling, Thomas A., Andrea L. Seidner, and David E. Gaither. "A computer-directed program for smoking cessation treatment." Journal of Substance Abuse 6, no. 4 (January 1994): 427–31. http://dx.doi.org/10.1016/s0899-3289(94)90362-x.

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25

Fenger, Kirsten, and S. A. Sørensen. "PEDIGREE-PLOT: a computer program for plotting pedigrees." Clinical Genetics 32, no. 4 (June 28, 2008): 284–86. http://dx.doi.org/10.1111/j.1399-0004.1987.tb03313.x.

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26

Urban-Lurain, Mark, and Donald J. Weinshank. "Do Non-Computer Science Students Need to Program?*." Journal of Engineering Education 90, no. 4 (October 2001): 535–41. http://dx.doi.org/10.1002/j.2168-9830.2001.tb00636.x.

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27

Fouad, AF, and JA Burleson. "Effectiveness of an endodontic diagnosis computer simulation program." Journal of Dental Education 61, no. 3 (March 1997): 289–95. http://dx.doi.org/10.1002/j.0022-0337.1997.61.3.tb03119.x.

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28

PROCTOR, TONY. "Brain, A Computer Program to Aid Creative Thinking." Journal of Creative Behavior 25, no. 1 (March 1991): 61–68. http://dx.doi.org/10.1002/j.2162-6057.1991.tb01354.x.

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29

Berger, Stephen A., and Uri Blackman. "Computer Program for Diagnosing and Teaching Geographic Medicine." Journal of Travel Medicine 2, no. 3 (September 1, 1995): 199–203. http://dx.doi.org/10.1111/j.1708-8305.1995.tb00655.x.

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30

GLYNIAS, MANUEL J., and ALAN G. GOODRIDGE. "A Sequence Analysis Program for the Macintosh Computer." Annals of the New York Academy of Sciences 478, no. 1 Metabolic Reg (October 1986): 281–82. http://dx.doi.org/10.1111/j.1749-6632.1986.tb15541.x.

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31

Clement, M., D. Posada, and K. A. Crandall. "TCS: a computer program to estimate gene genealogies." Molecular Ecology 9, no. 10 (October 2000): 1657–59. http://dx.doi.org/10.1046/j.1365-294x.2000.01020.x.

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32

Burns, Edward. "Autoscan: An adaptive multiple-choice basic computer program." Journal of School Psychology 26, no. 3 (September 1988): 311–15. http://dx.doi.org/10.1016/0022-4405(88)90012-x.

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33

Hakulinen, Timo, and Kamal H. Abeywickrama. "A computer program package for relative survival analysis." Computer Programs in Biomedicine 19, no. 2-3 (January 1985): 197–207. http://dx.doi.org/10.1016/0010-468x(85)90011-x.

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34

PHILIPPOU, PHILIP. "Using the GRASS program." Journal of Computer Assisted Learning 4, no. 3 (September 1988): 179–81. http://dx.doi.org/10.1111/j.1365-2729.1988.tb00176.x.

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35

ZHANG, AI-BING, SHENGJIANG TAN, and TEIJI SOTA. "autoinfer1.0: a computer program to infer biogeographical events automatically." Molecular Ecology Notes 6, no. 3 (September 2006): 597–99. http://dx.doi.org/10.1111/j.1471-8286.2006.01376.x.

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36

Canfora, Gerardo, Aniello Cimitile, and Andrea De Lucia. "Conditioned program slicing." Information and Software Technology 40, no. 11-12 (December 1998): 595–607. http://dx.doi.org/10.1016/s0950-5849(98)00086-x.

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37

HAMERSLAG, RUDI. "Teacher-Friendly Transportation Program." Computer-Aided Civil and Infrastructure Engineering 3, no. 1 (November 6, 2008): 81–89. http://dx.doi.org/10.1111/j.1467-8667.1988.tb00158.x.

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38

Maier, Vincent B., Joseph M. Sherry, Joseph Kaminski, Paul Mashack, and John J. Kirias. "A Comprehensive X-Ray Machine Inspection Program." Biomedical Instrumentation & Technology 43, no. 6 (November 1, 2009): 468–71. http://dx.doi.org/10.2345/0899-8205-43.6.468.

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39

Burian, Max, and Heinz Amenitsch. "Dummy-atom modelling of stacked and helical nanostructures from solution scattering data." IUCrJ 5, no. 4 (May 11, 2018): 390–401. http://dx.doi.org/10.1107/s2052252518005493.

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The availability of dummy-atom modelling programs to determine the shape of monodisperse globular particles from small-angle solution scattering data has led to outstanding scientific advances. However, there is no equivalent procedure that allows modelling of stacked, seemingly endless structures, such as helical systems. This work presents a bead-modelling algorithm that reconstructs the structural motif of helical and rod-like systems. The algorithm is based on a `projection scheme': by exploiting the recurrent nature of stacked systems, such as helices, the full structure is reduced to a single building-block motif. This building block is fitted by allowing random dummy-atom movements without an underlying grid. The proposed method is verified using a variety of analytical models, and examples are presented of successful shape reconstruction from experimental data sets. To make the algorithm available to the scientific community, it is implemented in a graphical computer program that encourages user interaction during the fitting process and also includes an option for shape reconstruction of globular particles.

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40

Shieh, Kevin R., Christina Kratschmer, Keith E. Maier, John M. Greally, Matthew Levy, and Aaron Golden. "AptCompare: optimized de novo motif discovery of RNA aptamers via HTS-SELEX." Bioinformatics 36, no. 9 (January 30, 2020): 2905–6. http://dx.doi.org/10.1093/bioinformatics/btaa054.

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Abstract Summary High-throughput sequencing can enhance the analysis of aptamer libraries generated by the Systematic Evolution of Ligands by EXponential enrichment. Robust analysis of the resulting sequenced rounds is best implemented by determining a ranked consensus of reads following the processing by multiple aptamer detection algorithms. While several such approaches have been developed to this end, their installation and implementation is problematic. We developed AptCompare, a cross-platform program that combines six of the most widely used analytical approaches for the identification of RNA aptamer motifs and uses a simple weighted ranking to order the candidate aptamers, all driven within the same GUI-enabled environment. We demonstrate AptCompare’s performance by identifying the top-ranked candidate aptamers from a previously published selection experiment in our laboratory, with follow-up bench assays demonstrating good correspondence between the sequences’ rankings and their binding affinities. Availability and implementation The source code and pre-built virtual machine images are freely available at https://bitbucket.org/shiehk/aptcompare. Supplementary information Supplementary data are available at Bioinformatics online.

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41

PIAZZA, A., P. L. MATTIUZ, and P. RICHIARDI. "A Computer Program Library for a Tissue Typing Laboratory." Tissue Antigens 2, no. 3 (October 9, 2008): 156–62. http://dx.doi.org/10.1111/j.1399-0039.1972.tb00131.x.

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42

Gerding, J. J. T. "A FORTRAN IV E AMINO ACID ANALYZER COMPUTER PROGRAM." International Journal of Protein Research 1, no. 1-4 (January 9, 2009): 169–80. http://dx.doi.org/10.1111/j.1399-3011.1969.tb01640.x.

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43

Bishop, Yvonne M. M., Christine C. Katsioules, and Johannes Meienhofer. "COMPUTER PROGRAM FOR LOCALIZATION OF DISULFIDE BONDS IN PROTEINS." International Journal of Peptide and Protein Research 6, no. 4 (January 12, 2009): 231–44. http://dx.doi.org/10.1111/j.1399-3011.1974.tb02382.x.

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44

Macfarlane, H. A. F., and J. A. Ross. "Use of a computer program for contact clinic results." Contact Dermatitis 14, no. 3 (March 1986): 162–64. http://dx.doi.org/10.1111/j.1600-0536.1986.tb01197.x.

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45

Nowell, A. F. "A computer program for repetitive strain gauge rosette analysis." Strain 21, no. 4 (November 1985): 183–85. http://dx.doi.org/10.1111/j.1475-1305.1985.tb00585.x.

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46

Keystone, Jay S. "GIDEON Computer Program for Diagnosing and Teaching Geographic Medicine." Journal of Travel Medicine 6, no. 2 (June 1999): 152–54. http://dx.doi.org/10.1111/j.1708-8305.1999.tb00850.x.

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47

Koča, Jaroslav. "Computer program CICADA — travelling along conformational potential energy hypersurface." Journal of Molecular Structure: THEOCHEM 308 (May 1994): 13–24. http://dx.doi.org/10.1016/0166-1280(94)80091-x.

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48

Brooks, Gordon P., and Holly Raffle. "FISH: A New Computer Program for Friendly Introductory Statistics Help." Teaching Statistics 27, no. 3 (August 2005): 81–88. http://dx.doi.org/10.1111/j.1467-9639.2005.00221.x.

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49

FOLL, MATTHIEU, and OSCAR E. GAGGIOTTI. "colonise: a computer program to study colonization processes in metapopulations." Molecular Ecology Notes 5, no. 3 (September 2005): 705–7. http://dx.doi.org/10.1111/j.1471-8286.2005.01030.x.

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50

Valiere, Nathaniel. "gimlet: a computer program for analysing genetic individual identification data." Molecular Ecology Notes 2, no. 3 (September 2002): 377–79. http://dx.doi.org/10.1046/j.1471-8286.2002.00228.x.

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