Journal articles: 'Sequence profiles'

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Popovic, Tatjana, Aleksandra Jelusic, Petar Mitrovic, Renata Ilicic, and Sanja Markovic. "Allelic profile of Serbian Xanthomonas campestris pv. campestris isolates from cabbage." Pesticidi i fitomedicina 35, no. 1 (2020): 19–26. http://dx.doi.org/10.2298/pif2001019p.

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Xanthomonas campestris pv. campestris (Xcc), the causal agent of black rot disease of cabbage (Brassica oleracea var. capitata L.), is one of the most important bacteria which affect proper cabbage growth, leading to head weight and quality losses and thereby drastically reducing its marketing value. The pathogen is genetically diverse, which is evident from the presence of eleven races worldwide and more than thirty combinations of allelic profiles. Therefore, this study aimed to determine the allelic profiles of Serbian cabbage Xcc strains obtained in 2014. The analysis was done on three selected Xcc strains whose DNA was first amplified using polymerase chain reaction (PCR) with four housekeeping genes - P-XdnaK, fyuA, gyrB, and rpoD, then sequenced, and the obtained sequences were finally used to determine allelic profiles. Allelic profiles were determined by comparison with 33 Xcc strains obtained from different hosts and regions, whose allelic profiles had been determined previously. A non-redundant database (NRDB) from the pubMLST was used for allelic profile determination and Phyloviz software for constructing a minimum spanning tree. The obtained allelic profile of all Serbian Xcc cabbage strains was 1, 3, 1, 1 for the P-X-dnaK, fyuA, gyrB and rpoD genes, respectively. This profile is assigned as sequence type 2 (ST2) and it coincides with a Portuguese B. oleracea Xcc strain, CPBF 213, originating from B. oleracea var. costata. No connection between sequence type (ST) and the host was detected.

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Kiah, Han Mao, Gregory J. Puleo, and Olgica Milenkovic. "Codes for DNA Sequence Profiles." IEEE Transactions on Information Theory 62, no. 6 (June 2016): 3125–46. http://dx.doi.org/10.1109/tit.2016.2555321.

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Rozemuller, E. H., B. Chadwick, D. Charron, L. A. Baxter-Lowe, J. F. Eliaou, L. Johnston-Dow, and M. G. J. Tilanus. "Sequenase sequence profiles used for HLA-DPB1 sequencing-based typing." Tissue Antigens 47, no. 1 (January 1996): 72–79. http://dx.doi.org/10.1111/j.1399-0039.1996.tb02516.x.

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FREITAS, A. D., and S. COUTINHO. "MULTIFRACTALITY OF GENERALIZED FIBONACCI PROFILES." Fractals 01, no. 03 (September 1993): 694–701. http://dx.doi.org/10.1142/s0218348x93000721.

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The multifractal properties of a class of one parameter generalized Fibonacci sequences are studied. This class of recursion relations, which is defined by an infinite set of sequences similar to the original Fibonacci’s one, appears for the first time in the study of the Ising model by the real space Migdal-Kadanoff renormalization group approach. The whole set of numbers generated by these equations, when properly arranged over the interval [0,1], gives the exact local magnetization profile of the Ising model on generalized hierarchical lattices at the critical temperature. This profile has a multifractal structure showing that an infinite set of exponents is required to describe how its singularities are distributed. The F(α)-function for the measure defined by the normalized profile is numerically obtained and analyzed. Each value of α characterizes the set of numbers generated by one sequence with arbitrary initial conditions. The exact lower (αmin) and upper (αmax) bounds of the spectra are analytically calculated. For a particular value of the parameter, the original Fibonacci sequence appears, generating a set of numbers diverging with the αmin exponent.

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Hirons, Linda, Eleanor J. Gardiner, Christopher A. Hunter, and Peter Willett. "Structural DNA Profiles: Single Sequence Queries." Journal of Chemical Information and Modeling 46, no. 2 (March 2006): 743–52. http://dx.doi.org/10.1021/ci050385a.

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Gil, Nelson, and Andras Fiser. "Identifying functionally informative evolutionary sequence profiles." Bioinformatics 34, no. 8 (December 1, 2017): 1278–86. http://dx.doi.org/10.1093/bioinformatics/btx779.

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Gardiner, Don L., Alison M. Goodfellow, Diana R. Martin, and Kadaba S. Sriprakash. "Group A Streptococcal Vir Types Are M-Protein Gene (emm) Sequence Type Specific." Journal of Clinical Microbiology 36, no. 4 (1998): 902–7. http://dx.doi.org/10.1128/jcm.36.4.902-907.1998.

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The M-protein genes (emm genes) of 103 separate impetiginous Streptococcus pyogenes isolates were sequenced and the sequence types were compared to the types obtained by Vir typing. Vir typing is based on restriction fragment length polymorphism (RFLP) analysis of a 4- to 7-kb pathogenicity island encodingemm and other virulence genes. By using bothHaeIII and HinfI to generate RFLP profiles, complete concordance between Vir type and emm sequence type was found. Comparison of the emm sequences with those in GenBank revealed new sequence types sharing less than 90% identity with known types. Diversity in the emm sequence was generated by corrected frameshift mutations, point mutations, and small in-frame mutations.

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Rychlewski, Leszek, Weizhong Li, Lukasz Jaroszewski, and Adam Godzik. "Comparison of sequence profiles. Strategies for structural predictions using sequence information." Protein Science 9, no. 2 (December 31, 2008): 232–41. http://dx.doi.org/10.1110/ps.9.2.232.

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Kim, Byoung-Jun, Jae-Myung Kim, Bo-Ram Kim, So-Young Lee, GaNa Kim, Yun-Ho Jang, Soyoon Ryoo, et al. "Mycobacterium anyangense sp. nov., a rapidly growing species isolated from blood of Korean native cattle, Hanwoo (Bos taurus coreanae)." International Journal of Systematic and Evolutionary Microbiology 65, Pt_7 (July 1, 2015): 2277–85. http://dx.doi.org/10.1099/ijs.0.000255.

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From the whole blood of Korean native cattle, Hanwoo (Bos taurus coreanae), a previously undescribed, rapidly growing, scotochromogenic isolate of the genus Mycobacterium is reported. Its 16S rRNA gene sequence, and the sequences of three other genes (hsp65, recA and rpoB) were unique and phylogenetic analysis based on 16S rRNA gene sequence (1420 bp) placed the organism into the rapidly growing Mycobacterium group close to Mycobacterium smegmatis (98.5 % sequence similarity). However, phylogenetic analyses based on three different gene sequences (hsp65, recA and rpoB) revealed its location to be distinct from the branch of rapidly growing species. Culture and biochemical characteristics were generally similar to those of Mycobacterium fortuitum. Unique matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) MS profiles of lipids, unique fatty acid profile, unique mycolic acids profiles and a low DNA–DNA relatedness to M. fortuitum (23.6 %) and M. smegmatis (39.7 %) strongly supported the taxonomic status of this strain as a representative of a novel species of rapidly growing mycobacteria named Mycobacterium anyangense. The type strain is strain QIA-38T ( = JCM 30275T = KCTC 29443T).

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Xiong, Yi, Juan Liu, Wen Zhang, and Tao Zeng. "Prediction of heme binding residues from protein sequences with integrative sequence profiles." Proteome Science 10, Suppl 1 (2012): S20. http://dx.doi.org/10.1186/1477-5956-10-s1-s20.

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Bartonek, Lukas, Daniel Braun, and Bojan Zagrovic. "Frameshifting preserves key physicochemical properties of proteins." Proceedings of the National Academy of Sciences 117, no. 11 (March 3, 2020): 5907–12. http://dx.doi.org/10.1073/pnas.1911203117.

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Frameshifts in protein coding sequences are widely perceived as resulting in either nonfunctional or even deleterious protein products. Indeed, frameshifts typically lead to markedly altered protein sequences and premature stop codons. By analyzing complete proteomes from all three domains of life, we demonstrate that, in contrast, several key physicochemical properties of protein sequences exhibit significant robustness against +1 and −1 frameshifts. In particular, we show that hydrophobicity profiles of many protein sequences remain largely invariant upon frameshifting. For example, over 2,900 human proteins exhibit a Pearson’s correlation coefficient R between the hydrophobicity profiles of the original and the +1-frameshifted variants greater than 0.7, despite an average sequence identity between the two of only 6.5% in this group. We observe a similar effect for protein sequence profiles of affinity for certain nucleobases as well as protein sequence profiles of intrinsic disorder. Finally, analysis of significance and optimality demonstrates that frameshift stability is embedded in the structure of the universal genetic code and may have contributed to shaping it. Our results suggest that frameshifting may be a powerful evolutionary mechanism for creating new proteins with vastly different sequences, yet similar physicochemical properties to the proteins from which they originate.

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Elofsson, Arne, Daniel Fischer, Danny W. Rice, Scott M. Le Grand, and David Eisenberg. "A study of combined structure/sequence profiles." Folding and Design 1, no. 6 (December 1996): 451–61. http://dx.doi.org/10.1016/s1359-0278(96)00061-2.

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13

Biegert, A., and J. Soding. "Sequence context-specific profiles for homology searching." Proceedings of the National Academy of Sciences 106, no. 10 (February 20, 2009): 3770–75. http://dx.doi.org/10.1073/pnas.0810767106.

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Poleksic, A., and M. Fienup. "Optimizing the size of the sequence profiles to increase the accuracy of protein sequence alignments generated by profile-profile algorithms." Bioinformatics 24, no. 9 (March 12, 2008): 1145–53. http://dx.doi.org/10.1093/bioinformatics/btn097.

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15

KUANG, RUI, EUGENE IE, KE WANG, KAI WANG, MAHIRA SIDDIQI, YOAV FREUND, and CHRISTINA LESLIE. "PROFILE-BASED STRING KERNELS FOR REMOTE HOMOLOGY DETECTION AND MOTIF EXTRACTION." Journal of Bioinformatics and Computational Biology 03, no. 03 (June 2005): 527–50. http://dx.doi.org/10.1142/s021972000500120x.

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We introduce novel profile-based string kernels for use with support vector machines (SVMs) for the problems of protein classification and remote homology detection. These kernels use probabilistic profiles, such as those produced by the PSI-BLAST algorithm, to define position-dependent mutation neighborhoods along protein sequences for inexact matching of k-length subsequences ("k-mers") in the data. By use of an efficient data structure, the kernels are fast to compute once the profiles have been obtained. For example, the time needed to run PSI-BLAST in order to build the profiles is significantly longer than both the kernel computation time and the SVM training time. We present remote homology detection experiments based on the SCOP database where we show that profile-based string kernels used with SVM classifiers strongly outperform all recently presented supervised SVM methods. We further examine how to incorporate predicted secondary structure information into the profile kernel to obtain a small but significant performance improvement. We also show how we can use the learned SVM classifier to extract "discriminative sequence motifs" — short regions of the original profile that contribute almost all the weight of the SVM classification score — and show that these discriminative motifs correspond to meaningful structural features in the protein data. The use of PSI-BLAST profiles can be seen as a semi-supervised learning technique, since PSI-BLAST leverages unlabeled data from a large sequence database to build more informative profiles. Recently presented "cluster kernels" give general semi-supervised methods for improving SVM protein classification performance. We show that our profile kernel results also outperform cluster kernels while providing much better scalability to large datasets. Supplementary website:.

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Zhou, Jiaji, Mark C. Enright, and Brian G. Spratt. "Identification of the Major Spanish Clones of Penicillin-Resistant Pneumococci via the Internet Using Multilocus Sequence Typing." Journal of Clinical Microbiology 38, no. 3 (2000): 977–86. http://dx.doi.org/10.1128/jcm.38.3.977-986.2000.

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Multilocus sequence typing was used to characterize isolates of the major Spanish clones of penicillin-resistant and multiple-antibiotic-resistant Streptococcus pneumoniae. Isolates of the multidrug-resistant Spanish serotype 23F clone and serotype variants of this clone either had identical allelic profiles or their allelic profiles differed from this typical allelic profile at only one of the seven housekeeping loci. Similarly, isolates of the Spanish serotype 6B and 14 clones and the penicillin-resistant serotype 9V clone (and serotype variants of this clone) each had the same allelic profiles or profiles that differed at a single locus. Multilocus sequence typing therefore allows resistant pneumococci to be assigned to the Spanish clones if they have the typical allelic profile of the clone or if their profiles differ from that profile at a single locus. A few resistant isolates that had allelic profiles typical of that of a Spanish clone or whose profiles differed from that of the typical profile at only a single locus possessed penicillin-binding protein pbp1a, pbp2b, or pbp2xgenes that differed from those that are characteristic of the clone. In most cases these isolates could be assigned as variant members of the clone. Since almost all serotype 9V isolates have very similar genotypes, independently emerging penicillin-resistant clones of this serotype will inevitably appear to be similar by molecular typing procedures. Analysis of the pbp genes, in addition to multilocus sequence typing (or any other molecular typing procedure), is therefore required to assign isolates unambiguously to the penicillin-resistant Spanish serotype 9V clone.

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17

Scaiewicz, Andrea, and Michael Levitt. "Unique function words characterize genomic proteins." Proceedings of the National Academy of Sciences 115, no. 26 (June 12, 2018): 6703–8. http://dx.doi.org/10.1073/pnas.1801182115.

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Between 2009 and 2016 the number of protein sequences from known species increased 10-fold from 8 million to 85 million. About 80% of these sequences contain at least one region recognized by the conserved domain architecture retrieval tool (CDART) as a sequence motif. Motifs provide clues to biological function but CDART often matches the same region of a protein by two or more profiles. Such synonyms complicate estimates of functional complexity. We do full-linkage clustering of redundant profiles by finding maximum disjoint cliques: Each cluster is replaced by a single representative profile to give what we term a unique function word (UFW). From 2009 to 2016, the number of sequence profiles used by CDART increased by 80%; the number of UFWs increased more slowly by 30%, indicating that the number of UFWs may be saturating. The number of sequences matched by a single UFW (sequences with single domain architectures) increased as slowly as the number of different words, whereas the number of sequences matched by a combination of two or more UFWs in sequences with multiple domain architectures (MDAs) increased at the same rate as the total number of sequences. This combinatorial arrangement of a limited number of UFWs in MDAs accounts for the genomic diversity of protein sequences. Although eukaryotes and prokaryotes use very similar sets of “words” or UFWs (57% shared), the “sentences” (MDAs) are different (1.3% shared).

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Zhou, H., and Y. Zhou. "SPEM: improving multiple sequence alignment with sequence profiles and predicted secondary structures." Bioinformatics 21, no. 18 (July 14, 2005): 3615–21. http://dx.doi.org/10.1093/bioinformatics/bti582.

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Merrill, Lori, Jennifer Richardson, Cheryl R. Kuske, and John Dunbar. "Fluorescent Heteroduplex Assay for Monitoring Bacillus anthracis and Close Relatives in Environmental Samples." Applied and Environmental Microbiology 69, no. 6 (June 2003): 3317–26. http://dx.doi.org/10.1128/aem.69.6.3317-3326.2003.

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ABSTRACT A fluorescent heteroduplex method was developed to assess the presence of 16S rRNA gene (rDNA) sequences from Bacillus anthracis and close relatives in PCR-amplified 16S rDNA sequence mixtures from environmental samples. The method uses a single-stranded, fluorescent DNA probe, 464 nucleotides in length, derived from a B. anthracis 16S rRNA gene. The probe contains a unique, engineered deletion such that all probe-target duplexes are heteroduplexes with an unpaired G at position 343 (ΔG343). Heteroduplex profiles of sequences ≥85% similar to the probe were produced using an ABI 377 sequencer in less than 3 h. The method divides strains of the Bacillus cereus-Bacillus thuringiensis-B. anthracis group into two subgroups. Each subgroup is defined by a specific 16S rRNA gene sequence type. Sequence type A, containing one mismatch with the probe, occurs in B. anthracis and a small number of closely related clonal lineages represented mostly by food-borne pathogenic isolates of B. cereus and B. thuringiensis. Sequence type B, containing two mismatches with the probe, is found in the majority of B. cereus and B. thuringiensis strains examined to date. Sequence types A and B, when hybridized to the probe, generate two easily differentiated heteroduplexes. Thus, from heteroduplex profiles, the presence of B. cereus-B. thuringiensis-B. anthracis subgroups in environmental samples can be inferred unambiguously. The results show that fluorescent heteroduplex analysis is an effective profiling technique for detection and differentiation of sequences representing small phylogenetic or functional groups in environmental samples.

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20

Krabbe, Paul F. M., and Gouke J. Bonsel. "Sequence Effects, Health Profiles, and the QALY Model." Medical Decision Making 18, no. 2 (January 1998): 178–86. http://dx.doi.org/10.1177/0272989x9801800207.

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The authors conducted an experiment to determine whether the sequence of presentation of states in a health profile would affect the valuations assigned to them. The empirical task was part of a large standardized experiment involving 104 students. Thirteen health states were valued using two variations of the time-tradeoff method. At the group level, a small but distinct overall effect of the sequence of the tradeoffs was detected after accounting for discounting effects. The respondents were not preference-indifferent concerning the sequence of health states presented. Detailed analysis at the individual level indicated that the overall sequence effect was attributable to two groups of respondents who were sensitive to the sequence of events. One small group, referred to as “best-things-first” respondents, preferred the best years first; the other group, classified as “happy-end” respondents, preferred the reverse sequence. The majority of the respondents, however, were indifferent to the sequence. These results suggest that 1) in valuation experiments involving the time-tradeoff method and 2) in applying valuation results to the evaluation of real-life health consequences, a varying lifetime health profile may not be regarded as simply a chain of independent separately valued and discounted QALY periods. Even elementary valuation tasks cannot safely assume ignorance of prognosis, as the additive utility independence assumption of the QALY model does not hold. The sequence effect at least supplements the conventional general time-preference concept, and specific strategies are suggested to disentangle quantitatively the sequence effect and the time-preference effect.

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Rouillard, Vincent. "Decomposing pavement surface profiles into a Gaussian sequence." International Journal of Vehicle Systems Modelling and Testing 4, no. 4 (2009): 288. http://dx.doi.org/10.1504/ijvsmt.2009.032021.

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Smith, David K., and Hong Xue. "Sequence profiles of immunoglobulin and immunoglobulin-like domains." Journal of Molecular Biology 274, no. 4 (December 1997): 530–45. http://dx.doi.org/10.1006/jmbi.1997.1432.

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Pizzi, Cinzia, Mattia Ornamenti, Simone Spangaro, Simona E. Rombo, and Laxmi Parida. "Efficient Algorithms for Sequence Analysis with Entropic Profiles." IEEE/ACM Transactions on Computational Biology and Bioinformatics 15, no. 1 (January 1, 2018): 117–28. http://dx.doi.org/10.1109/tcbb.2016.2620143.

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Gront, D., M. Blaszczyk, P. Wojciechowski, and A. Kolinski. "BioShell Threader: protein homology detection based on sequence profiles and secondary structure profiles." Nucleic Acids Research 40, W1 (June 12, 2012): W257—W262. http://dx.doi.org/10.1093/nar/gks555.

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GUO, JIAN, XIAN PU, YUANLIE LIN, and HOWARD LEUNG. "PROTEIN SUBCELLULAR LOCALIZATION BASED ON PSI-BLAST AND MACHINE LEARNING." Journal of Bioinformatics and Computational Biology 04, no. 06 (December 2006): 1181–95. http://dx.doi.org/10.1142/s0219720006002405.

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Subcellular location is an important functional annotation of proteins. An automatic, reliable and efficient prediction system for protein subcellular localization is necessary for large-scale genome analysis. This paper describes a protein subcellular localization method which extracts features from protein profiles rather than from amino acid sequences. The protein profile represents a protein family, discards part of the sequence information that is not conserved throughout the family and therefore is more sensitive than the amino acid sequence. The amino acid compositions of whole profile and the N-terminus of the profile are extracted, respectively, to train and test the probabilistic neural network classifiers. On two benchmark datasets, the overall accuracies of the proposed method reach 89.1% and 68.9%, respectively. The prediction results show that the proposed method perform better than those methods based on amino acid sequences. The prediction results of the proposed method are also compared with Subloc on two redundance-reduced datasets.

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Rojas-Cartagena, Carmencita, Pablo Ortíz-Pineda, Francisco Ramírez-Gómez, Edna C. Suárez-Castillo, Vanessa Matos-Cruz, Carlos Rodríguez, Humberto Ortíz-Zuazaga, and José E. García-Arrarás. "Distinct profiles of expressed sequence tags during intestinal regeneration in the sea cucumberHolothuria glaberrima." Physiological Genomics 31, no. 2 (October 2007): 203–15. http://dx.doi.org/10.1152/physiolgenomics.00228.2006.

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Repair and regeneration are key processes for tissue maintenance, and their disruption may lead to disease states. Little is known about the molecular mechanisms that underline the repair and regeneration of the digestive tract. The sea cucumber Holothuria glaberrima represents an excellent model to dissect and characterize the molecular events during intestinal regeneration. To study the gene expression profile, cDNA libraries were constructed from normal, 3-day, and 7-day regenerating intestines of H. glaberrima. Clones were randomly sequenced and queried against the nonredundant protein database at the National Center for Biotechnology Information. RT-PCR analyses were made of several genes to determine their expression profile during intestinal regeneration. A total of 5,173 sequences from three cDNA libraries were obtained. About 46.2, 35.6, and 26.2% of the sequences for the normal, 3-days, and 7-days cDNA libraries, respectively, shared significant similarity with known sequences in the protein database of GenBank but only present 10% of similarity among them. Analysis of the libraries in terms of functional processes, protein domains, and most common sequences suggests that a differential expression profile is taking place during the regeneration process. Further examination of the expressed sequence tag dataset revealed that 12 putative genes are differentially expressed at significant level ( R > 6). Experimental validation by RT-PCR analysis reveals that at least three genes (unknown C-4677-1, melanotransferrin, and centaurin) present a differential expression during regeneration. These findings strongly suggest that the gene expression profile varies among regeneration stages and provide evidence for the existence of differential gene expression.

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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 (December 19, 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 and sequenced homologous repetitive sequences using a novel approach of creating a chinook salmon (Oncorhynchus tshawytscha) genomic DNA library with enriched low Cot DNA repeats for the development of DNA probes. The four types of repeats identified and sequenced were (CT)n and three Alu-like sequences. We generated DNA fingerprints using one of the minisatellite sequences as a probe. This minisatellite sequence was shown to be species specific because it is abundant in chinook and coho salmon (Oncorhynchus kisutch) genomes, but not in Atlantic salmon. These probes will provide us with the tools to study pedigree and linkage analysis, paternity testing, breeding programs, and the analysis of genetic structure within populations for aquaculture and fisheries research.

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Troyanskaya, O. G., O. Arbell, Y. Koren, G. M. Landau, and A. Bolshoy. "Sequence complexity profiles of prokaryotic genomic sequences: A fast algorithm for calculating linguistic complexity." Bioinformatics 18, no. 5 (May 1, 2002): 679–88. http://dx.doi.org/10.1093/bioinformatics/18.5.679.

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YU, GONG-XIN. "RULEMINER: A KNOWLEDGE SYSTEM FOR SUPPORTING HIGH-THROUGHPUT PROTEIN FUNCTION ANNOTATIONS." Journal of Bioinformatics and Computational Biology 02, no. 04 (December 2004): 595–617. http://dx.doi.org/10.1142/s0219720004000752.

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In this paper, we present RuleMiner, a knowledge system to facilitate a seamless integration of multi-sequence analysis tools and define profile-based rules for supporting high-throughput protein function annotations. This system consists of three essential components, Protein Function Groups (PFGs), PFG profiles and rules. The PFGs, established from an integrated analysis of current knowledge of protein functions from Swiss-Prot database and protein family-based sequence classifications, cover all possible cellular functions available in the database. The PFG profiles illustrate detailed protein features in the PFGs as in sequence conservations, the occurrences of sequence-based motifs, domains and species distributions. The rules, extracted from the PFG profiles, describe the clear relationships between these PFGs and all possible features. As a result, the RuleMiner is able to provide an enhanced capability for protein function analysis, such as results from the integrated sequence analysis tools for given proteins can be comparatively analyzed due to the clear feature-PFG relationships. Also, much needed guidance is readily available for such analysis. If the rules describe one-to-one (unique) relationships between the protein features and the PFGs, then these features can be utilized as unique functional identifiers and cellular functions of unknown proteins can be reliably determined. Otherwise, additional information has to be provided.

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Randriambelo, T., J. L. Baray, S. Baldy, A. M. Thompson, S. Oltmans, and P. Keckhut. "Investigation of the short-time variability of tropical tropospheric ozone." Annales Geophysicae 21, no. 10 (October 31, 2003): 2095–106. http://dx.doi.org/10.5194/angeo-21-2095-2003.

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Abstract. Since 1998, a ground-based tropospheric ozone lidar has been running at Reunion Island and has been involved with a daily measurement campaign that was performed in the latter part of the biomass burning season, during November–December 1999. The averaged ozone profile obtained during November–December 1999 agrees well with the averaged ozone profile obtained from the ozonesondes launch at Reunion during November–December (1992– 2001). Comparing weekly sonde launches (part of the Southern Hemisphere Additional Ozonesondes: SHADOZ program) with the daily ground-based lidar observations shows that some striking features of the day-to-day variability profiles are not observed in the sonde measurements. Ozone profiles respond to the nature of disturbances which vary from one day to the next. The vertical ozone distribution at Reunion is examined as a function of prevailing atmospheric circulation. Back trajectories show that most of the enhanced ozone crossed over biomass burning and convectively active regions in Madagascar and the southern African continent. The analyses of the meteorological data show that ozone stratification profiles are in agreement with the movement of the synoptic situations in November–December 1999. Three different sequences of transport are explained using wind fields. The first sequence from 23 to 25 November is characterized by northerly transport; during the second sequence from 26 to 30 November, the air masses are influenced by meridional transport. The third sequence from 2 to 6 December is characterized by westerly transport associated with the sub-tropical jet stream. The large, standard deviations of lidar profiles in the middle and upper troposphere are in agreement with the upper wind variabilities which evidence passing ridge and trough disturbances. During the transition period between the dry season and the wet season, multiple ozone sources including stratosphere-troposphere exchanges, convection and biomass burning contribute to tropospheric ozone at Reunion Island through sporadic events characterized by a large spatial and temporal variability.Key words. Atmospheric composition and structure (troposphere-composition and chemistry) – Meteorology and atmospheric dynamics (climatology; tropical meteorology)

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Tress, Michael L., David Jones, and Alfonso Valencia. "Predicting Reliable Regions in Protein Alignments from Sequence Profiles." Journal of Molecular Biology 330, no. 4 (July 2003): 705–18. http://dx.doi.org/10.1016/s0022-2836(03)00622-3.

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Yang, A. S., and L. y. Wang. "Local structure prediction with local structure-based sequence profiles." Bioinformatics 19, no. 10 (July 1, 2003): 1267–74. http://dx.doi.org/10.1093/bioinformatics/btg151.

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Hamp, Tobias, and Burkhard Rost. "Evolutionary profiles improve protein–protein interaction prediction from sequence." Bioinformatics 31, no. 12 (February 4, 2015): 1945–50. http://dx.doi.org/10.1093/bioinformatics/btv077.

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Eisenberg, David, James U. Bowie, Roland Lüthy, and Seunghyon Choe. "Three-dimensional profiles for analysing protein sequence–structure relationships." Faraday Discuss. 93 (1992): 25–34. http://dx.doi.org/10.1039/fd9929300025.

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Harrison, Robert L., and Bryony C. Bonning. "The nucleopolyhedroviruses of Rachiplusia ou and Anagrapha falcifera are isolates of the same virus." Journal of General Virology 80, no. 10 (October 1, 1999): 2793–98. http://dx.doi.org/10.1099/0022-1317-80-10-2793.

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The 7·8 kb EcoRI-G fragment of Rachiplusia ou multicapsid nucleopolyhedrovirus (RoMNPV), containing the polyhedrin gene, was cloned and sequenced. The sequence of the fragment was 92·3% identical to the sequence of the corresponding region in the Autographa californica (Ac)MNPV genome. A comparison of the EcoRI-G sequence with other MNPV sequences revealed that RoMNPV was most closely related to AcMNPV. However, the predicted amino acid sequence of RoMNPV polyhedrin shared more sequence identity with the polyhedrin of Orygia pseudotsugata MNPV. In addition, the RoMNPV sequence was almost completely identical (99·9%) to a previously published 6·3 kb sequence of Anagrapha falcifera MNPV (AfMNPV). The Eco RI and HindIII restriction fragment profiles of RoMNPV and AfMNPV also were nearly identical, with an additional EcoRI band detected in RoMNPV DNA. Bioassays of these viruses with three different hosts (the European corn borer, Ostrinia nubilalis H übner, the corn earworm, Helicoverpa zea Boddie, and the tobacco budworm, Heliothis virescens Fabricius) failed to detect any differences in the biological activities of RoMNPV and AfMNPV. These results indicate that RoMNPV and AfMNPV are different isolates of the same virus. The taxonomic relationship of Ro/AfMNPV and AcMNPV is discussed.

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Hunter, Paul J., Geoff M. Petch, Leo A. Calvo-Bado, Tim R. Pettitt, Nick R. Parsons, J. Alun W. Morgan, and John M. Whipps. "Differences in Microbial Activity and Microbial Populations of Peat Associated with Suppression of Damping-Off Disease Caused by Pythium sylvaticum." Applied and Environmental Microbiology 72, no. 10 (October 2006): 6452–60. http://dx.doi.org/10.1128/aem.00313-06.

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ABSTRACT The microbiological characteristics associated with disease-suppressive peats are unclear. We used a bioassay for Pythium sylvaticum-induced damping-off of cress seedlings to identify conducive and suppressive peats. Microbial activity in unconditioned peats was negatively correlated with the counts of P. sylvaticum at the end of the bioassay. Denaturing gradient gel electrophoresis (DGGE) profiling and clone library analyses of small-subunit rRNA gene sequences from two suppressive and two conducive peats differed in the bacterial profiles generated and the diversity of sequence populations. There were also significant differences between bacterial sequence populations from suppressive and conducive peats. The frequencies of a number of microbial groups, including the Rhizobium-Agrobacterium group (specifically sequences similar to those for the genera Ochrobactrum and Zoogloea) and the Acidobacteria, increased specifically in the suppressive peats, although no single bacterial group was associated with disease suppression. Fungal DGGE profiles varied little over the course of the bioassay; however, two bands associated specifically with suppressive samples were detected. Sequences from these bands corresponded to Basidiomycete yeast genera. Although the DGGE profiles were similar, fungal sequence diversity also increased during the bioassay. Sequences highly similar to those of Cryptococcus increased in relative abundance during the bioassay, particularly in the suppressive samples. This study highlights the importance of using complementary approaches to molecular profiling of complex populations and provides the first report that basidiomycetous yeasts may be associated with the suppression of Pythium-induced diseases in peats.

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Golyshev, Mikhail A., and Eugene V. Korotkov. "Developing of the Computer Method for Annotation of Bacterial Genes." Advances in Bioinformatics 2015 (December 6, 2015): 1–9. http://dx.doi.org/10.1155/2015/635437.

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Over the last years a great number of bacterial genomes were sequenced. Now one of the most important challenges of computational genomics is the functional annotation of nucleic acid sequences. In this study we presented the computational method and the annotation system for predicting biological functions using phylogenetic profiles. The phylogenetic profile of a gene was created by way of searching for similarities between the nucleotide sequence of the gene and 1204 reference genomes, with further estimation of the statistical significance of found similarities. The profiles of the genes with known functions were used for prediction of possible functions and functional groups for the new genes. We conducted the functional annotation for genes from 104 bacterial genomes and compared the functions predicted by our system with the already known functions. For the genes that have already been annotated, the known function matched the function we predicted in 63% of the time, and in 86% of the time the known function was found within the top five predicted functions. Besides, our system increased the share of annotated genes by 19%. The developed system may be used as an alternative or complementary system to the current annotation systems.

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Winberg, B. C., Z. Zhou, J. F. Dallas, C. L. McIntyre, and J. P. Gustafson. "Characterization of minisatellite sequences from Oryza sativa." Genome 36, no. 5 (October 1, 1993): 978–83. http://dx.doi.org/10.1139/g93-128.

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Two DNA sequences were cloned from the genome of cultivated rice (Oryza sativa L.) by cross-hybridization with the human minisatellite sequence 33.6. The rice sequences consisted of tandem direct repeats, which showed significant similarity to the 33.6 concensus sequence. Profiles capable of distinguishing different rice cultivars were detected by cross-hybridization with a DNA probe amplified by the polymerase chain reaction from one of the rice minisatellite sequences.Key words: Oryza sativa, minisatellite, hypervariable, DNA fingerprint.

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Kennedy, Katherine, Michael W. Hall, Michael D. J. Lynch, Gabriel Moreno-Hagelsieb, and Josh D. Neufeld. "Evaluating Bias of Illumina-Based Bacterial 16S rRNA Gene Profiles." Applied and Environmental Microbiology 80, no. 18 (July 7, 2014): 5717–22. http://dx.doi.org/10.1128/aem.01451-14.

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ABSTRACTMassively parallel sequencing of 16S rRNA genes enables the comparison of terrestrial, aquatic, and host-associated microbial communities with sufficient sequencing depth for robust assessments of both alpha and beta diversity. Establishing standardized protocols for the analysis of microbial communities is dependent on increasing the reproducibility of PCR-based molecular surveys by minimizing sources of methodological bias. In this study, we tested the effects of template concentration, pooling of PCR amplicons, and sample preparation/interlane sequencing on the reproducibility associated with paired-end Illumina sequencing of bacterial 16S rRNA genes. Using DNA extracts from soil and fecal samples as templates, we sequenced pooled amplicons and individual reactions for both high (5- to 10-ng) and low (0.1-ng) template concentrations. In addition, all experimental manipulations were repeated on two separate days and sequenced on two different Illumina MiSeq lanes. Although within-sample sequence profiles were highly consistent, template concentration had a significant impact on sample profile variability for most samples. Pooling of multiple PCR amplicons, sample preparation, and interlane variability did not influence sample sequence data significantly. This systematic analysis underlines the importance of optimizing template concentration in order to minimize variability in microbial-community surveys and indicates that the practice of pooling multiple PCR amplicons prior to sequencing contributes proportionally less to reducing bias in 16S rRNA gene surveys with next-generation sequencing.

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Fuster, José, Sergio Pérez-López, Pilar Candelas, and Constanza Rubio. "Design of Binary-Sequence Zone Plates in High Wavelength Domains." Sensors 18, no. 8 (August 9, 2018): 2604. http://dx.doi.org/10.3390/s18082604.

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The design of zone plates is an important topic in many areas of physics, such as optics, X-rays, microwaves or ultrasonics. In this paper, a zone plate design method, which provides high flexibility in the shaping of the focusing profile, is analyzed. This flexibility is achieved through the use of binary sequences that produce zone plates with different properties and applications. It is shown that this binary-sequence method works properly at low wavelengths, but requires a modification term to work accurately in high wavelength domains. This additional term extends this powerful design method to any wavelength. Simulation results show acoustic focusing profiles for Fresnel, Fibonacci and Cantor zone plates operating at a wavelength of 1.5 mm without any distortion.

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Hou, Qingzhen, Paul F. G. De Geest, Christian J. Griffioen, Sanne Abeln, Jaap Heringa, and K. Anton Feenstra. "SeRenDIP: SEquential REmasteriNg to DerIve profiles for fast and accurate predictions of PPI interface positions." Bioinformatics 35, no. 22 (May 22, 2019): 4794–96. http://dx.doi.org/10.1093/bioinformatics/btz428.

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Abstract Motivation Interpretation of ubiquitous protein sequence data has become a bottleneck in biomolecular research, due to a lack of structural and other experimental annotation data for these proteins. Prediction of protein interaction sites from sequence may be a viable substitute. We therefore recently developed a sequence-based random forest method for protein–protein interface prediction, which yielded a significantly increased performance than other methods on both homomeric and heteromeric protein–protein interactions. Here, we present a webserver that implements this method efficiently. Results With the aim of accelerating our previous approach, we obtained sequence conservation profiles by re-mastering the alignment of homologous sequences found by PSI-BLAST. This yielded a more than 10-fold speedup and at least the same accuracy, as reported previously for our method; these results allowed us to offer the method as a webserver. The web-server interface is targeted to the non-expert user. The input is simply a sequence of the protein of interest, and the output a table with scores indicating the likelihood of having an interaction interface at a certain position. As the method is sequence-based and not sensitive to the type of protein interaction, we expect this webserver to be of interest to many biological researchers in academia and in industry. Availability and implementation Webserver, source code and datasets are available at www.ibi.vu.nl/programs/serendipwww/. Supplementary information Supplementary data are available at Bioinformatics online.

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Song, Ruiyang, Baixin Cao, Zhenling Peng, Christopher J. Oldfield, Lukasz Kurgan, Ka-Chun Wong, and Jianyi Yang. "Accurate Sequence-Based Prediction of Deleterious nsSNPs with Multiple Sequence Profiles and Putative Binding Residues." Biomolecules 11, no. 9 (September 9, 2021): 1337. http://dx.doi.org/10.3390/biom11091337.

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Non-synonymous single nucleotide polymorphisms (nsSNPs) may result in pathogenic changes that are associated with human diseases. Accurate prediction of these deleterious nsSNPs is in high demand. The existing predictors of deleterious nsSNPs secure modest levels of predictive performance, leaving room for improvements. We propose a new sequence-based predictor, DMBS, which addresses the need to improve the predictive quality. The design of DMBS relies on the observation that the deleterious mutations are likely to occur at the highly conserved and functionally important positions in the protein sequence. Correspondingly, we introduce two innovative components. First, we improve the estimates of the conservation computed from the multiple sequence profiles based on two complementary databases and two complementary alignment algorithms. Second, we utilize putative annotations of functional/binding residues produced by two state-of-the-art sequence-based methods. These inputs are processed by a random forests model that provides favorable predictive performance when empirically compared against five other machine-learning algorithms. Empirical results on four benchmark datasets reveal that DMBS achieves AUC > 0.94, outperforming current methods, including protein structure-based approaches. In particular, DMBS secures AUC = 0.97 for the SNPdbe and ExoVar datasets, compared to AUC = 0.70 and 0.88, respectively, that were obtained by the best available methods. Further tests on the independent HumVar dataset shows that our method significantly outperforms the state-of-the-art method SNPdryad. We conclude that DMBS provides accurate predictions that can effectively guide wet-lab experiments in a high-throughput manner.

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Radford, A., and N. I. M. Dix. "Comparison of the orotidine 5′-monophosphate decarboxylase sequences of eight species." Genome 30, no. 4 (August 1, 1988): 501–5. http://dx.doi.org/10.1139/g88-084.

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Predicted amino acid sequences of the enzyme orotidine 5′-phosphate decarboxylase (EC 4.1.1.23) from eight different organisms are compared. The comparisons are made on the basis of primary structural differences, primary amino acid sequence, hydropathy profiles, and secondary structure predictions. The organisms compared are Mus musculus, Aspergillus nidulans, Neurospora crassa, Kluyveromyces lactis, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Escherichia coli, and Salmonella typhimurium.Key words: amino acid sequence, decarboxylase-OMP.

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CASTELLANO, GIOVANNA, CIRO CASTIELLO, DANILO DELL'AGNELLO, ANNA MARIA FANELLI, CORRADO MENCAR, and MARIA ALESSANDRA TORSELLO. "LEARNING FUZZY USER PROFILES FOR RESOURCE RECOMMENDATION." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 18, no. 04 (August 2010): 389–410. http://dx.doi.org/10.1142/s0218488510006611.

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Recommender systems are systems capable of assisting users by quickly providing them with relevant resources according to their interests or preferences. The efficacy of a recommender system is strictly connected with the possibility of creating meaningful user profiles, including information about user preferences, interests, goals, usage data and interactive behavior. In particular, analysis of user preferences is important to predict user behaviors and make appropriate recommendations. In this paper, we present a fuzzy framework to represent, learn and update user profiles. The representation of a user profile is based on a structured model of user cognitive states, including a competence profile, a preference profile and an acquaintance profile. The strategy for deriving and updating profiles is to record the sequence of accessed resources by each user, and to update preference profiles accordingly, so as to suggest similar resources at next user accesses. The adaption of the preference profile is performed continuously, but in earlier stages it is more sensitive to updates (plastic phase) while in later stages it is less sensitive (stable phase) to allow resource recommendation. Simulation results are reported to show the effectiveness of the proposed approach.

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Grandadam, Marc, Soraya Tebbal, Mélanie Caron, Mahinda Siriwardana, Bernard Larouze, Jean Louis Koeck, Yves Buisson, Vincent Enouf, and Elisabeth Nicand. "Evidence for hepatitis E virus quasispecies." Journal of General Virology 85, no. 11 (November 1, 2004): 3189–94. http://dx.doi.org/10.1099/vir.0.80248-0.

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The genetic diversity of hepatitis E virus (HEV) has been extensively analysed during the last decade. Most sporadic and epidemic HEV strains are distributed into genotypes or groups. Nevertheless, few studies have looked at the polymorphism of HEV strains isolated from a given outbreak. A serum bank collected in Tanefdour, Algeria, during an acute hepatitis epidemic (1986–1987), retrospectively confirmed as hepatitis E, was analysed. Of the 69 serum samples collected within an 8-week period, 23 were positive for both partial ORF1 (replicase gene) and ORF2 (capsid gene) sequences. Inter- and intra-patient diversities were assessed by RFLP, and by sequencing a 448 bp sequence corresponding to ORF2. RFLP analysis distinguished three profiles: A (18/23), B (3/23) and C (2/23). Most isolates (18/23) shared 99·7–100 % sequence identity and the remainder showed 1–1·3 % divergence. HEV intra-patient diversity was studied using 12 isolates (seven displaying the major RFLP profile and five displaying minor RFLP profiles). For 9 of 12 isolates, additional intra-patient heterogeneity was revealed by RFLP analysis of 100 clones from each isolate and sequence diversity ranging from 0·11 to 3·4 %. These data strongly support the quasispecies organization of HEV during epidemics and could explain the adaptable behaviour of the virus in the host–pathogen interrelations.

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Killer, J., J. Havlík, E. Vlková, V. Rada, R. Pechar, O. Benada, J. Kopečný, O. Kofroňová, and H. Sechovcová. "Lactobacillus rodentium sp. nov., from the digestive tract of wild rodents." International Journal of Systematic and Evolutionary Microbiology 64, Pt_5 (May 1, 2014): 1526–33. http://dx.doi.org/10.1099/ijs.0.054924-0.

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Three strains of regular, long, Gram-stain-positive bacterial rods were isolated using TPY, M.R.S. and Rogosa agar under anaerobic conditions from the digestive tract of wild mice (Mus musculus). All 16S rRNA gene sequences of these isolates were most similar to sequences of Lactobacillus gasseri ATCC 33323T and Lactobacillus johnsonii ATCC 33200T (97.3 % and 97.2 % sequence similarities, respectively). The novel strains shared 99.2–99.6 % 16S rRNA gene sequence similarities. Type strains of L. gasseri and L. johnsonii were also most related to the newly isolated strains according to rpoA (83.9–84.0 % similarities), pheS (84.6–87.8 %), atpA (86.2–87.7 %), hsp60 (89.4–90.4 %) and tuf (92.7–93.6 %) gene sequence similarities. Phylogenetic studies based on 16S rRNA, hsp60, rpoA, atpA and pheS gene sequences, other genotypic and many phenotypic characteristics (results of API 50 CHL, Rapid ID 32A and API ZYM biochemical tests; cellular fatty acid profiles; cellular polar lipid profiles; end products of glucose fermentation) showed that these bacterial strains represent a novel species within the genus Lactobacillus . The name Lactobacillus rodentium sp. nov. is proposed to accommodate this group of new isolates. The type strain is MYMRS/TLU1T ( = DSM 24759T = CCM 7945T).

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Massey, Dashiell J., Dongsung Kim, Kayla E. Brooks, Marcus B. Smolka, and Amnon Koren. "Next-Generation Sequencing Enables Spatiotemporal Resolution of Human Centromere Replication Timing." Genes 10, no. 4 (April 2, 2019): 269. http://dx.doi.org/10.3390/genes10040269.

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Centromeres serve a critical function in preserving genome integrity across sequential cell divisions, by mediating symmetric chromosome segregation. The repetitive, heterochromatic nature of centromeres is thought to be inhibitory to DNA replication, but has also led to their underrepresentation in human reference genome assemblies. Consequently, centromeres have been excluded from genomic replication timing analyses, leaving their time of replication unresolved. However, the most recent human reference genome, hg38, included models of centromere sequences. To establish the experimental requirements for achieving replication timing profiles for centromeres, we sequenced G1- and S-phase cells from five human cell lines, and aligned the sequence reads to hg38. We were able to infer DNA replication timing profiles for the centromeres in each of the five cell lines, which showed that centromere replication occurs in mid-to-late S phase. Furthermore, we found that replication timing was more variable between cell lines in the centromere regions than expected, given the distribution of variation in replication timing genome-wide. These results suggest the potential of these, and future, sequence models to enable high-resolution studies of replication in centromeres and other heterochromatic regions.

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Lanchantin, Jack, and Yanjun Qi. "Graph convolutional networks for epigenetic state prediction using both sequence and 3D genome data." Bioinformatics 36, Supplement_2 (December 2020): i659—i667. http://dx.doi.org/10.1093/bioinformatics/btaa793.

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Abstract Motivation Predictive models of DNA chromatin profile (i.e. epigenetic state), such as transcription factor binding, are essential for understanding regulatory processes and developing gene therapies. It is known that the 3D genome, or spatial structure of DNA, is highly influential in the chromatin profile. Deep neural networks have achieved state of the art performance on chromatin profile prediction by using short windows of DNA sequences independently. These methods, however, ignore the long-range dependencies when predicting the chromatin profiles because modeling the 3D genome is challenging. Results In this work, we introduce ChromeGCN, a graph convolutional network for chromatin profile prediction by fusing both local sequence and long-range 3D genome information. By incorporating the 3D genome, we relax the independent and identically distributed assumption of local windows for a better representation of DNA. ChromeGCN explicitly incorporates known long-range interactions into the modeling, allowing us to identify and interpret those important long-range dependencies in influencing chromatin profiles. We show experimentally that by fusing sequential and 3D genome data using ChromeGCN, we get a significant improvement over the state-of-the-art deep learning methods as indicated by three metrics. Importantly, we show that ChromeGCN is particularly useful for identifying epigenetic effects in those DNA windows that have a high degree of interactions with other DNA windows. Availability and implementation https://github.com/QData/ChromeGCN. Supplementary information Supplementary data are available at Bioinformatics online.

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Kuldová, Jitka, Peter Košovan, Zuzana Limpouchová, Karel Procházka, and Oleg V. Borisov. "Self-association of copolymers with various composition profiles." Collection of Czechoslovak Chemical Communications 75, no. 4 (2010): 493–505. http://dx.doi.org/10.1135/cccc2009539.

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In this paper, we present Monte Carlo study of the self-assembly of linear copolymers consisting of two types of segments (well soluble A and insoluble B segments) in selective solvents. We used simple lattice model: chains were represented by self-avoiding random walks and quality of solvent for both types of segments was controlled by pair interaction parameters. We analyzed how the association behavior depends on the composition profile, i.e., on the sequence of segments A and B along the chain. The size and structure of associates formed by chains with different composition profiles were compared with those of diblock copolymers with the same content of A and B segments. It was shown that even small changes in the sequence of segments within the chains lead to significant differences in the association behavior. In addition to composition profiles, we also shown how the association behavior depends on the quality of solvent and copolymer concentration.

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DUKKA, BAHADUR K. C., ETSUJI TOMITA, JUN'ICHI SUZUKI, KATSUHISA HORIMOTO, and TATSUYA AKUTSU. "PROTEIN THREADING WITH PROFILES AND DISTANCE CONSTRAINTS USING CLIQUE BASED ALGORITHMS." Journal of Bioinformatics and Computational Biology 04, no. 01 (February 2006): 19–42. http://dx.doi.org/10.1142/s0219720006001680.

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With the advent of experimental technologies like chemical cross-linking, it has become possible to obtain distances between specific residues of a newly sequenced protein. These types of experiments usually are less time consuming than X-ray crystallography or NMR. Consequently, it is highly desired to develop a method that incorporates this distance information to improve the performance of protein threading methods. However, protein threading with profiles in which constraints on distances between residues are given is known to be NP-hard. By using the notion of a maximum edge-weight clique finding algorithm, we introduce a more efficient method called FTHREAD for profile threading with distance constraints that is 18 times faster than its predecessor CLIQUETHREAD. Moreover, we also present a novel practical algorithm NTHREAD for profile threading with Non-strict constraints. The overall performance of FTHREAD on a data set shows that although our algorithm uses a simple threading function, our algorithm performs equally well as some of the existing methods. Particularly, when there are some unsatisfied constraints, NTHREAD (Non-strict constraints threading algorithm) performs better than threading with FTHREAD (Strict constraints threading algorithm). We have also analyzed the effects of using a number of distance constraints. This algorithm helps the enhancement of alignment quality between the query sequence and template structure, once the corresponding template structure is determined for the target sequence.

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Journal articles on the topic 'Sequence profiles'

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