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Journal articles on the topic 'Scoring Matrices'

Author: Grafiati

Published: 4 June 2021

Last updated: 6 September 2023

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1

WU, THOMAS D., CRAIG G. NEVILL-MANNING, and DOUGLAS L. BRUTLAG. "Minimal-Risk Scoring Matrices for Sequence Analysis." Journal of Computational Biology 6, no. 2 (1999): 219–35. http://dx.doi.org/10.1089/cmb.1999.6.219.

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2

Mills, L. J., and W. R. Pearson. "Adjusting scoring matrices to correct overextended alignments." Bioinformatics 29, no. 23 (2013): 3007–13. http://dx.doi.org/10.1093/bioinformatics/btt517.

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3

Trivedi, Rakesh, and Hampapathalu Adimurthy Nagarajaram. "Substitution scoring matrices for proteins ‐ An overview." Protein Science 29, no. 11 (2020): 2150–63. http://dx.doi.org/10.1002/pro.3954.

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4

Frommlet, Florian, and Andreas Futschik. "On the Dependence Structure of Sequence Alignment Scores Calculated with Multiple Scoring Matrices." Statistical Applications in Genetics and Molecular Biology 3, no. 1 (2004): 1–12. http://dx.doi.org/10.2202/1544-6115.1073.

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A common practice in protein sequence alignment is to try several scoring matrices until “something interesting" is found. This leads to a multiple testing problem making p- and E-values hard to interpret. We focus on local alignment and propose to use logistic copula functions to model explicitly the dependence structure of scores obtained using different scoring matrices. By doing this, we obtain p-value correction factors when using more than one scoring matrix on the same sequences. Furthermore the parameter of the logistic copula can be interpreted as measure of dependence, providing insight concerning the relatedness of the scores from different matrices.

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5

Smith, Scott F. "Homology search with binary and trinary scoring matrices." International Journal of Bioinformatics Research and Applications 2, no. 2 (2006): 119. http://dx.doi.org/10.1504/ijbra.2006.009763.

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6

SHPAER, EUGENE G. "DNA Scoring Matrices: Application to Detect Divergent Repeats." Microbial & Comparative Genomics 2, no. 1 (1997): 75–87. http://dx.doi.org/10.1089/omi.1.1997.2.75.

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7

Sato, Kengo, Kensuke Morita, and Yasubumi Sakakibara. "PSSMTS: position specific scoring matrices on tree structures." Journal of Mathematical Biology 56, no. 1-2 (2007): 201–14. http://dx.doi.org/10.1007/s00285-007-0108-4.

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8

KACZANOWSKI, Sz, and P. ZIELENKIEWICZ. "LOG-ODDS SCORING MATRICES CALCULATED FROM DESIGNED PROTEIN SEQUENCES." Biochemical Society Transactions 28, no. 5 (2000): A261. http://dx.doi.org/10.1042/bst028a261b.

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9

Crochemore, Maxime, Gad M. Landau, and Michal Ziv-Ukelson. "A Subquadratic Sequence Alignment Algorithm for Unrestricted Scoring Matrices." SIAM Journal on Computing 32, no. 6 (2003): 1654–73. http://dx.doi.org/10.1137/s0097539702402007.

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10

Henikoff, Jorja G., and Steven Henikoff. "Using substitution probabilities to improve position-specific scoring matrices." Bioinformatics 12, no. 2 (1996): 135–43. http://dx.doi.org/10.1093/bioinformatics/12.2.135.

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11

Wu, T. D., C. G. Nevill-Manning, and D. L. Brutlag. "Fast probabilistic analysis of sequence function using scoring matrices." Bioinformatics 16, no. 3 (2000): 233–44. http://dx.doi.org/10.1093/bioinformatics/16.3.233.

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12

Frommlet, F., M. Bogdan, and A. Futschik. "Power analysis of database search using multiple scoring matrices." Computational Statistics & Data Analysis 51, no. 3 (2006): 1656–63. http://dx.doi.org/10.1016/j.csda.2006.06.009.

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13

Coronado, Juan E., Oliver Attie, Susan L. Epstein, Wei-Gang Qiu, and Peter N. Lipke. "Composition-Modified Matrices Improve Identification of Homologs of Saccharomyces cerevisiae Low-Complexity Glycoproteins." Eukaryotic Cell 5, no. 4 (2006): 628–37. http://dx.doi.org/10.1128/ec.5.4.628-637.2006.

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ABSTRACT Yeast glycoproteins are representative of low-complexity sequences, those sequences rich in a few types of amino acids. Low-complexity protein sequences comprise more than 10% of the proteome but are poorly aligned by existing methods. Under default conditions, BLAST and FASTA use the scoring matrix BLOSUM62, which is optimized for sequences with diverse amino acid compositions. Because low-complexity sequences are rich in a few amino acids, these tools tend to align the most common residues in nonhomologous positions, thereby generating anomalously high scores, deviations from the expected extreme value distribution, and small e values. This anomalous scoring prevents BLOSUM62-based BLAST and FASTA from identifying correct homologs for proteins with low-complexity sequences, including Saccharomyces cerevisiae wall proteins. We have devised and empirically tested scoring matrices that compensate for the overrepresentation of some amino acids in any query sequence in different ways. These matrices were tested for sensitivity in finding true homologs, discrimination against nonhomologous and random sequences, conformance to the extreme value distribution, and accuracy of e values. Of the tested matrices, the two best matrices (called E and gtQ) gave reliable alignments in BLAST and FASTA searches, identified a consistent set of paralogs of the yeast cell wall test set proteins, and improved the consistency of secondary structure predictions for cell wall proteins.

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14

May, Alex C. W. "Towards more meaningful hierarchical classification of amino acid scoring matrices." Protein Engineering, Design and Selection 12, no. 9 (1999): 707–12. http://dx.doi.org/10.1093/protein/12.9.707.

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15

Campagne, Carole Sylvie, Philip Roche, Frédéric Gosselin, Léïta Tschanz, and Thierry Tatoni. "Expert-based ecosystem services capacity matrices: Dealing with scoring variability." Ecological Indicators 79 (August 2017): 63–72. http://dx.doi.org/10.1016/j.ecolind.2017.03.043.

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16

Malherbe, Hanlie, Stephan Pauleit, and Carsten Lorz. "Mapping the Loss of Ecosystem Services in a Region Under Intensive Land Use Along the Southern Coast of South Africa." Land 8, no. 3 (2019): 51. http://dx.doi.org/10.3390/land8030051.

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Intensive land use activities worldwide have caused considerable loss to many ecosystem services. The dynamics of these threats must be quickly investigated to ensure timely update of management strategies and policies. Compared with complex models, mapping approaches that use scoring matrices to link land use/land cover and landscape properties with ecosystem services are relatively efficient and easier to apply. In this study, scoring matrices are developed and spatially explicit assessments of five ecosystem services, such as erosion control, water flow regulation, water quality maintenance, soil quality maintenance, and biodiversity maintenance, are conducted for a region under intense land use along the southern coast of South Africa. The complex interaction of land use/land cover and ecosystem services within a particular landscape is further elucidated by performing a spatial overview of the high-risk areas that contribute to the loss of ecosystem services. Results indicate that both agricultural activities and urban development contribute to the loss of ecosystem services. This study reveals that with sufficient knowledge from previous literature and inputs from experts, the use of scoring matrices can be adapted to different regional characteristics. This approach can be improved by adding additional landscape properties and/or adapting the matrix values as new data become available.

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17

Kerpedjiev, Peter, Jes Frellsen, Stinus Lindgreen, and Anders Krogh. "Adaptable probabilistic mapping of short reads using position specific scoring matrices." BMC Bioinformatics 15, no. 1 (2014): 100. http://dx.doi.org/10.1186/1471-2105-15-100.

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18

O’Leary, Maureen A., Kenzley Alphonse, Arce H. Mariangeles, et al. "Crowds Replicate Performance of Scientific Experts Scoring Phylogenetic Matrices of Phenotypes." Systematic Biology 67, no. 1 (2017): 49–60. http://dx.doi.org/10.1093/sysbio/syx052.

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19

Frommlet, F., A. Futschik, and M. Bogdan. "On the significance of sequence alignments when using multiple scoring matrices." Bioinformatics 20, no. 6 (2004): 881–87. http://dx.doi.org/10.1093/bioinformatics/btg498.

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20

Rozhina, Viktoria D. "CREDIT RISK ASSESSMENT MODELS AT THE BEHAVIOR-SCORING STAGE." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 7/1, no. 127 (2022): 128–40. http://dx.doi.org/10.36871/ek.up.p.r.2022.07.01.013.

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Credit risk management is one of the most important tasks in banking risk management. Credit risk is the possibility of financial losses if the borrower fails to fulfill its obligations in a timely manner and in full, in particular as a result of a delay or non-repayment of a payment on a banking product. This article is devoted to the search for optimal methods for assessing the main component of the credit risk model - the probability of default of the borrower (PD) at the stage of building behavioral models. The paper considers two blocks of mathematical models - quantitative and classification. The object of the study is a portfolio of homogeneous loans of a commercial bank, the subject is the dynamics of the exit of the considered contracts into default. As an effective approach, the author proposes an integrated method for introducing the forecast result obtained using migration matrices as a new variable for the scoring model. Namely, revealing the depth of delinquency, upon reaching which borrowers do not improve the quality of the loan, as a separate predictor that helps to improve the scoring result.

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21

Boytsov, Alexandr, Sergey Abramov, Vsevolod J. Makeev, and Ivan V. Kulakovskiy. "Positional weight matrices have sufficient prediction power for analysis of noncoding variants." F1000Research 11 (January 12, 2022): 33. http://dx.doi.org/10.12688/f1000research.75471.1.

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The commonly accepted model to quantify the specificity of transcription factor binding to DNA is the position weight matrix, also called the position-specific scoring matrix. Position weight matrices are used in thousands of projects and computational tools in regulatory genomics, including prediction of the regulatory potential of single-nucleotide variants. Yet, recently Yan et al. presented new experimental method for analysis of regulatory variants and, based on its results, reported that "the position weight matrices of most transcription factors lack sufficient predictive power". Here, we re-analyze the rich experimental dataset obtained by Yan et al. and show that appropriately selected position weight matrices in fact can successfully quantify transcription factor binding to alternative alleles.

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22

Sanchez-Garcia, Ruben, Carlos Sorzano, Jose Carazo, and Joan Segura. "3DCONS-DB: A Database of Position-Specific Scoring Matrices in Protein Structures." Molecules 22, no. 12 (2017): 2230. http://dx.doi.org/10.3390/molecules22122230.

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23

Maurer-Stroh, Sebastian, Maja Debulpaep, Nico Kuemmerer, et al. "Exploring the sequence determinants of amyloid structure using position-specific scoring matrices." Nature Methods 7, no. 3 (2010): 237–42. http://dx.doi.org/10.1038/nmeth.1432.

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24

Lim, Shen, Joo Tong, Fook Chew, and Martti T. Tammi. "The value of position-specific scoring matrices for assessment of protein allegenicity." BMC Bioinformatics 9, Suppl 12 (2008): S21. http://dx.doi.org/10.1186/1471-2105-9-s12-s21.

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25

STATES, D., W. GISH, and S. ALTSCHUL. "Improved sensitivity of nucleic acid database searches using application-specific scoring matrices." Methods 3, no. 1 (1991): 66–70. http://dx.doi.org/10.1016/s1046-2023(05)80165-3.

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26

Pu, Xian, Jian Guo, Howard Leung, and Yuanlie Lin. "Prediction of membrane protein types from sequences and position-specific scoring matrices." Journal of Theoretical Biology 247, no. 2 (2007): 259–65. http://dx.doi.org/10.1016/j.jtbi.2007.01.016.

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27

G., Renganayaki, and Achuthsankar S. Nair. "Hubsm: A Novel Amino Acid Substitution Matrix for Comparing Hub Proteins." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 8 (2017): 212. http://dx.doi.org/10.23956/ijarcsse.v7i8.53.

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Sequence alignment algorithms and database search methods use BLOSUM and PAM substitution matrices constructed from general proteins. These de facto matrices are not optimal to align sequences accurately, for the proteins with markedly different compositional bias in the amino acid. In this work, a new amino acid substitution matrix is calculated for the disorder and low complexity rich region of Hub proteins, based on residue characteristics. Insights into the amino acid background frequencies and the substitution scores obtained from the Hubsm unveils the residue substitution patterns which differs from commonly used scoring matrices .When comparing the Hub protein sequences for detecting homologs, the use of this Hubsm matrix yields better results than PAM and BLOSUM matrices. Usage of Hubsm matrix can be optimal in database search and for the construction of more accurate sequence alignments of Hub proteins.

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28

Boytsov, Alexandr, Sergey Abramov, Vsevolod J. Makeev, and Ivan V. Kulakovskiy. "Positional weight matrices have sufficient prediction power for analysis of noncoding variants." F1000Research 11 (June 23, 2022): 33. http://dx.doi.org/10.12688/f1000research.75471.2.

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The position weight matrix, also called the position-specific scoring matrix, is the commonly accepted model to quantify the specificity of transcription factor binding to DNA. Position weight matrices are used in thousands of projects and software tools in regulatory genomics, including computational prediction of the regulatory impact of single-nucleotide variants. Yet, recently Yan et al. reported that "the position weight matrices of most transcription factors lack sufficient predictive power" if applied to the analysis of regulatory variants studied with a newly developed experimental method, SNP-SELEX. Here, we re-analyze the rich experimental dataset obtained by Yan et al. and show that appropriately selected position weight matrices in fact can adequately quantify transcription factor binding to alternative alleles.

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29

Boytsov, Alexandr, Sergey Abramov, Vsevolod J. Makeev, and Ivan V. Kulakovskiy. "Positional weight matrices have sufficient prediction power for analysis of noncoding variants." F1000Research 11 (July 4, 2022): 33. http://dx.doi.org/10.12688/f1000research.75471.3.

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The position weight matrix, also called the position-specific scoring matrix, is the commonly accepted model to quantify the specificity of transcription factor binding to DNA. Position weight matrices are used in thousands of projects and software tools in regulatory genomics, including computational prediction of the regulatory impact of single-nucleotide variants. Yet, recently Yan et al. reported that "the position weight matrices of most transcription factors lack sufficient predictive power" if applied to the analysis of regulatory variants studied with a newly developed experimental method, SNP-SELEX. Here, we re-analyze the rich experimental dataset obtained by Yan et al. and show that appropriately selected position weight matrices in fact can adequately quantify transcription factor binding to alternative alleles.

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30

Maurer-Stroh, Sebastian, Maja Debulpaep, Nico Kuemmerer, et al. "Addendum: Exploring the sequence determinants of amyloid structure using position-specific scoring matrices." Nature Methods 7, no. 10 (2010): 855–57. http://dx.doi.org/10.1038/nmeth1010-855b.

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31

Gowri, V. S. "MulPSSM: a database of multiple position-specific scoring matrices of protein domain families." Nucleic Acids Research 34, no. 90001 (2006): D243—D246. http://dx.doi.org/10.1093/nar/gkj043.

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32

Dombrowski, Stefan C., A. Alexander Beaujean, Ryan J. McGill, and Nicholas F. Benson. "The Woodcock-Johnson IV Tests of Achievement Provides Too Many Scores for Clinical Interpretation." Journal of Psychoeducational Assessment 37, no. 7 (2018): 819–36. http://dx.doi.org/10.1177/0734282918800745.

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The Woodcock-Johnson Tests of Achievement, Fourth Edition (WJ IV ACH) is purported to align with Cattell–Horn–Carroll (CHC) theory and offers upward of 20 scores within its interpretive and scoring system. The Technical Manual does not furnish validity evidence for the scores reported by the scoring system, suggesting that evidentiary support may be incomplete. Exploratory bifactor analysis (EBFA; maximum likelihood extraction with a bigeomin [orthogonal] rotation) was applied to the two school-aged correlation matrices at ages 9 to 19. Results indicated nonalignment with CHC theory and do not support the interpretation of most of the scores suggested by the scoring system. Instead, the results of this study suggest that the loading patterns diverge significantly from the interpretive system produced by the WJ IV ACH. Only the academic fluency and academic knowledge clusters emerged following the use of EBFA. Implications for clinical interpretation of the WJ IV ACH are offered.

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33

Maurer-Stroh, Sebastian, Maja Debulpaep, Nico Kuemmerer, et al. "Erratum: Corrigendum: Exploring the sequence determinants of amyloid structure using position-specific scoring matrices." Nature Methods 7, no. 10 (2010): 855. http://dx.doi.org/10.1038/nmeth1010-855a.

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34

Teddy, Trimurni Abidin, and Listiani Nurul Huda. "MICROLEAKAGE OF SAUCER-SHAPED CLASS II COMPOSITE RESIN RESTORATION." Dentika Dental Journal 18, no. 3 (2015): 251–56. http://dx.doi.org/10.32734/dentika.v18i3.1962.

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Filling techniques influence in reducing polymerization shrinkage which cause microleakage. Besides, the use of matricesalso contributes to achieve good marginal ridge. This study was aimed to examine the effect of filling techniques and theuse of matrices on microleakage of saucer-shaped Class II restorations. Mandibular premolar specimens were prepared insaucer-shaped cavity design, then they were divided into eight groups according to filling techniques (bulk orincremental), the use of matrices (circumferential or sectional), and whether load was provided or not. Specimens wereimmersed in saline for 24 hours, then thermocycled, later immersed in 2% methylene blue for 24 hours. Micro gap wasmeasured by scoring dye penetration in specimens that were sectioned mesio-distally under a stereomicroscope with 20xmagnification. Furthermore, visual analysis was performed under Scanning Electron Microscope to examine themicroleakage in details. Statistical analysis with Kruskal-Wallis test and Mann-Whitney test demonstrated that bulk andincremental filling techniques were not significantly different in microleakage (p> 0.05). This study also demonstratedthat the use of matrices was significantly different in microleakage in different filling techniques (p< 0.05), whether loadwas provided or not. This study showed that the use of matrices was important in reducing the microleakage in saucershapedClass II restorations.

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35

Campagne, C. Sylvie, and Philip Roche. "May the matrix be with you! Guidelines for the application of expert-based matrix approach for ecosystem services assessment and mapping." One Ecosystem 3 (May 3, 2018): e24134. http://dx.doi.org/10.3897/oneeco.3.e24134.

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Matrices or look-up tables are increasingly popular flexible tools for ecosystem services mapping and assessment. The matrix approach links ecosystem types or land cover types to ecosystem services by providing a score for ecosystem service (ES) capacity, supply, use, demand or other concepts. Using expert elicitation enables quick and integrative ES scoring that can meet general demand for validated ES mapping and assessment at different scales. Nevertheless, guidance is needed on how to collect and integrate expert knowledge to address some of the biases and limits of the expert elicitation method. This paper aims to propose a set of guidelines to produce ES matrices based on expert knowledge. It builds on existing literature and experience acquired through the production of several ES matrices in several ES assessments carried out in France. We propose a 7-steps methodology for the expert-based matrix approach that aims to promote cogency in the method and coherency in the matrices produced. The aim here is to use collective knowledge to produce semi-quantitative estimates of ES quantities and not to analyse individual or societal preferences or importance of ES. The definition of the objectives and the preparation phase is particularly important in order to define the components of capacity to demand ES chain to be addressed. The objectives and the ES components addressed will influence the composition of the expert panel. We recommend an individual filling of an empty matrix in order to strengthen the statistical analysis of the scores' variability and the analysis of congruency between experts. Expert scoring should follow a process of discussion, information-sharing and collective appropriation of a list of ecosystem types and ES to be assessed. We suggest that the ES matrix should not only focus on ES central scores but also address the variabilities and uncertainties as part of the ES assessment. The analysis of these sources of variability allows the documentation of variations in the ES quantity but also an exploration into the lack of consensus or knowledge gaps that needs to be addressed.

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36

Yao, Shuang, Donghua Yu, Yan Song, Hao Yao, Yuzhen Hu, and Benhai Guo. "Dry Bulk Carrier Investment Selection through a Dual Group Decision Fusing Mechanism in the Green Supply Chain." Sustainability 10, no. 12 (2018): 4528. http://dx.doi.org/10.3390/su10124528.

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Uncertain linguistic variables and scoring evaluations are two important evaluation mechanisms in the decision making field. Sustainability requirements for ship investment lead to the complexity of influence factors and the decision making process. The uncertain linguistic assessment features a large amount of ambiguity and subjectivity, while the scoring evaluation features high precision and distinct gradations. This paper constructs a criteria system in the green supply chain and proposes a dual group decision fusing mechanism for integrating the linguistic variable and scoring evaluation into a unified evaluation term. A hierarchical cloud of linguistic variable terms is constructed based on scoring via a reverse cloud generator, and then, the ship investment linguistic terms are transformed into prospect values. In addition, the consistency and investment selection performance are measured after aggregating the individual decision matrices for group decision making. The empirical research results on the selection of dry bulk carriers for investment show that dual group decision fusing mechanisms could effectively improve the consistency, decision making efficiency, and accuracy of dry bulk ship investment choices and reduce the cost of feedback adjustment for group decisions. In comparison with the trapezoidal fuzzy and fuzzy TOPSIS methods of group decision making, the proposed method performs better when there are a large number of alternatives.

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37

Joiţa, Dan-Marian, Mihaela Aurelia Tomescu, Donatella Bàlint, and Lorentz Jäntschi. "An Application of the Eigenproblem for Biochemical Similarity." Symmetry 13, no. 10 (2021): 1849. http://dx.doi.org/10.3390/sym13101849.

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Protein alignment finds its application in refining results of sequence alignment and understanding protein function. A previous study aligned single molecules, making use of the minimization of sums of the squares of eigenvalues, obtained for the antisymmetric Cartesian coordinate distance matrices Dx and Dy. This is used in our program to search for similarities between amino acids by comparing the sums of the squares of eigenvalues associated with the Dx, Dy, and Dz distance matrices. These matrices are obtained by removing atoms that could lead to low similarity. Candidates are aligned, and trilateration is used to attach all previously striped atoms. A TM-score is the scoring function that chooses the best alignment from supplied candidates. Twenty essential amino acids that take many forms in nature are selected for comparison. The correct alignment is taken into account most of the time by the alignment algorithm. It was numerically detected by the TM-score 70% of the time, on average, and 15% more cases with close scores can be easily distinguished by human observation.

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38

Frith, M. C. "Statistical significance of clusters of motifs represented by position specific scoring matrices in nucleotide sequences." Nucleic Acids Research 30, no. 14 (2002): 3214–24. http://dx.doi.org/10.1093/nar/gkf438.

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39

Kinjo, Akira R., and Haruki Nakamura. "Nature of Protein Family Signatures: Insights from Singular Value Analysis of Position-Specific Scoring Matrices." PLoS ONE 3, no. 4 (2008): e1963. http://dx.doi.org/10.1371/journal.pone.0001963.

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40

Andie, Andie, and Hasanuddin Hasanuddin. "THE IMPLEMENTATION OF ACCREDITATION SCORING CALCULATIONS IN ALL WEB-BASED ACCREDITATION AGENCIES." AL ULUM: JURNAL SAINS DAN TEKNOLOGI 9, no. 2 (2023): 76. http://dx.doi.org/10.31602/jst.v9i2.11768.

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Accreditation is an assessment activity to determine the eligibility of a department and higher education. Accreditation aims to determine the eligibility of departments and universities based on criteria that refer to the national higher education standards and guarantee the quality of departments and universities externally in both academic and non-academic fields to protect the interests of students and the community. All accreditation agencies have different accreditation instruments. The scoring calculation can be done automatically through the application of the respective accreditation agency and can only be seen by the assessment team, while departments and universities cannot see it. so far, universities and departments can only calculate accreditation scores manually using the excell application based on accreditation assessment instruments and matrices. Therefore, the research team wants to create a web-based application that can calculate accreditation scores independently to calculate accreditation assessment scores quickly and accurately.

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41

Myers, Richard, Caroline Clark, Arshad Khan, Paul Kellam, and Richard Tedder. "Genotyping Hepatitis B virus from whole- and sub-genomic fragments using position-specific scoring matrices in hbv star." Journal of General Virology 87, no. 6 (2006): 1459–64. http://dx.doi.org/10.1099/vir.0.81734-0.

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Hepatitis B virus (HBV) genomes have been classified into eight genotypes based on phylogenetic analysis of sequence variation. Identifying and tracking the movement of HBV genotypes is important in terms of both monitoring infection rates and predicting disease and treatment. An HBV genotyping tool has been developed that compares query sequences with position-specific scoring matrices representing the eight HBV genotypes. This tool (hbv star) is rapid, robust and accurate and assigns genotype based on a statistically defined scoring model. hbv star confidently assigned 90 % of 590 full-length HBV genomes to an HBV genotype (Z score >2.0). Thirty-two of the residual 48 sequences were identified as non-human primate viruses and 16 sequences were identified as recombinant or putative recombinants. Receiver-Operated Characteristic (ROC) analysis was used to compare the accuracy of genotype prediction using basal core promoter sequences and surface and core genes with the accuracy achieved by using full-length sequences. A web interface to hbv star is available at http://www.vgb.ucl.ac.uk/starn.shtml.

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42

MALDE, KETIL, and ROBERT GIEGERICH. "Calculating PSSM probabilities with lazy dynamic programming." Journal of Functional Programming 16, no. 1 (2005): 75–81. http://dx.doi.org/10.1017/s0956796805005708.

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Position-specific scoring matrices are one way to represent approximate string patterns, which are commonly encountered in the field of bioinformatics. An important problem that arises with their application is calculating the statistical significance of matches. We review the currently most efficient algorithm for this task, and show how it can be implemented in Haskell, taking advantage of the built-in non-strictness of the language. The resulting program turns out to be an instance of dynamic programming, using lists rather the typical dynamic programming matrix.

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43

Satria, Dhimas, Dovan Pujangga Asmara Lanank Esiswitoyo, Ni Ketut Caturwati, Erny Listijorini, and Rina Lusiani. "Body Design Concept of Remotely Operated Vehicle (ROV) of Observation Class with the Method of Concept Screening and Concept Scoring." MATEC Web of Conferences 218 (2018): 02009. http://dx.doi.org/10.1051/matecconf/201821802009.

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The Remotely Operated Vehicle (ROV) underwater observation equipment has previously been developed, but it had restriction for not being hydrodynamic still due to the unique conditions of the Sunda Strait waters. This study aims to further develop the previously developed ROV by improving the design structure of the ROV body. The method of design concept selection used was concept screening and concept scoring. In concept screening, the initial concept was evaluated relatively to the same preferences using screening matrices. On the other hand the Concept Scoring was conducted by determining the relative performance value which was the assessment used to evaluate how the comparison between concepts and number as the comparison. The result of the study obtained the selected design concept, which was small ROV with streamlined / half-streamlined body geometry which had rear-middle rotor configuration as motion component of hydrodynamic 3 DOF (surge, heave, and yaw).

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44

Torda, A. E., J. B. Procter, and T. Huber. "Wurst: a protein threading server with a structural scoring function, sequence profiles and optimized substitution matrices." Nucleic Acids Research 32, Web Server (2004): W532—W535. http://dx.doi.org/10.1093/nar/gkh357.

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Henneke, Christina M., Michael J. Danson, David W. Hough, and David J. Osguthorpe. "Sequence alignment of citrate synthase proteins using a multiple sequence alignment algorithm and multiple scoring matrices." "Protein Engineering, Design and Selection" 2, no. 8 (1989): 597–604. http://dx.doi.org/10.1093/protein/2.8.597.

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Eronen, Ville-Pekka, Rolf O. Lindén, Anna Lindroos, Mirella Kanerva, and Tero Aittokallio. "Genome-Wide Scoring of Positive and Negative Epistasis through Decomposition of Quantitative Genetic Interaction Fitness Matrices." PLoS ONE 5, no. 7 (2010): e11611. http://dx.doi.org/10.1371/journal.pone.0011611.

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Leelananda, Sumudu P., and Robert L. Jernigan. "Incorporating Protein Topology Information in Similarity Matrices for Improved Sequence Matching (A Fold-Specific Scoring System)." Biophysical Journal 104, no. 2 (2013): 508a. http://dx.doi.org/10.1016/j.bpj.2012.11.2804.

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Jones, David T. "Protein secondary structure prediction based on position-specific scoring matrices 1 1Edited by G. Von Heijne." Journal of Molecular Biology 292, no. 2 (1999): 195–202. http://dx.doi.org/10.1006/jmbi.1999.3091.

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Gao, Jianzhao, Ning Zhang, and Jishou Ruan. "Prediction of protein modification sites of gamma-carboxylation using position specific scoring matrices based evolutionary information." Computational Biology and Chemistry 47 (December 2013): 215–20. http://dx.doi.org/10.1016/j.compbiolchem.2013.09.002.

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Leiberman, D., D. Myatt, and A. Kausar. "ST3 national selection for surgical specialty training in the UK: a comparative analysis." Bulletin of the Royal College of Surgeons of England 103, no. 7 (2021): 357–61. http://dx.doi.org/10.1308/rcsbull.2021.129.

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Abstract:

Introduction National recruitment at ST3 level is the point for aspiring surgical trainees to obtain a national training number and progress to consultancy. In the 2020 recruitment year, face-to-face interviews were not possible owing to the COVID-19 pandemic. This highlighted wide ranging variability in recruitment processes for different surgical specialties. Methods Person specification details and portfolio scoring matrices were accessed through the Oriel recruitment portal. These were analysed and broken down into common domains for comparison purposes by two authors. Overall scores were totalled. Each domain was assessed in terms of its importance to each specialty by calculating its percentage contribution to overall portfolio marks. Results There was variability in all aspects of portfolio assessment and scoring. This started with how many overall ranking marks were contributed by the portfolio to each specialty. Further analysis and comparison of scoring domains demonstrated heterogeneity in how each specialty assesses and awards candidates marks based on achievements. Large emphasis is placed on certain domains by some specialties but not others. Conclusions The degree of variation in ST3 portfolio assessment and the differences between surgical specialties in how the scoring domains are valued has implications for core surgical trainees and those looking to apply for higher surgical training at ST3 level. Currently, core surgical trainees are assessed using a common process of annual review of competence progression that may not be suited to helping prepare candidates for gaining a national training number. There is no available evidence to account for variability between surgical specialty recruitment processes. Further work is needed to assess whether ST3 selection scoring variation has any impact on trainee progression to higher surgical training.

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