ライフサイエンスコーパス: subsequence

1 ofiling method to identify F(420)-correlated subsequences.

2 ence in these regions for intermediate sized subsequences.

3 ded to reveal groups of conserved functional subsequences.

4 ce into all of its possible contiguous 25 nt subsequences.

5 short fixed- or variable-length high-scoring subsequences.

6 s that are composed of repeated and shuffled subsequences.

7 omizable in how it views and exports genomic subsequences.

8 rather than any structural similarity in the subsequences.

9 e example of one sequence segmented into two subsequences.

10 sking repetitive elements and low complexity subsequences.

11 and characterized a small 10-amino acid CAV subsequence (90-99) that accounted for the majority of e

12 e build, genomic copy number of the 3 nested subsequence and influence of polymorphisms including a p

13 each DNA sequence into multiple overlapping subsequences and models each subsequence separately, the

14 tedly selecting the highest scoring pairs of subsequences and using them to construct small portions

15 on, concatenation, and recycling of specific subsequences; and (iii) enabling the biologically plausi

16 gned to find matches when query and database subsequences are highly similar.

17 Extended subsequences are then post-processed to refine repeats t

18 GBA finds short subsequences as LCR candidates by traversing this graph.

19 Within a defined subsequence, base composition and homodimerization value

20 this model, the determination of non-called subsequences between any gene and its nearest neighbors

21 presentation of position-specific nucleotide subsequences, both within and adjacent to the aligned re

22 quence having the fewest mismatches with the subsequence, but that did not match the subsequence exac

23 imilar correlations both for small and large subsequences, but there is a difference in these regions

24 end' approach, in which occurrences of short subsequences called 'seeds' are used to search for poten

25 Protein subsequences can be Basic Local Alignment Search Tool (B

26 ved from global alignment of locally-aligned subsequences compared to global alignment of the full-le

27 tes due to the presence of errors within the subsequence containing the oligo tag intended to define

28 sults obtained from analyses with homologous subsequence detection programs.

29 includes the ability to extract features and subsequences, display sequences and features graphically

30 synthetically prepared DNA and RNA oligomer subsequences: DNA, 5'd-T-T-T-T-T-T-A-A-T-A-A-T-T-A-A-A-A

31 e homologs) and local homologies (homologous subsequences embedded in nonhomologous sequence).

32 asured and the fluctuation spectrum of local subsequence entropies calculated to quantify the degree

33 the subsequence, but that did not match the subsequence exactly.

34 ree Markov models of order k associated with subsequences extracted from a given genome.

35 or scrolling full sequences or user-dictated subsequences for comparative viewing for organisms of in

36 sing paired KH-domains defined the preferred subsequences for each KH domain.

37 sualize the resulting ABA graphs and extract subsequences from ABA graphs.

38 nnection between the intrinsic complexity of subsequences in a genome and the intrinsic, i.e. DNA enc

39 tterns and then identifying over-represented subsequences in the promoter regions of those genes.

40 lly, complete domains are aligned to protein subsequences, in a 'semi-global alignment'.

41 It consists of symbols representing DNA subsequences, including regulatory elements and DNA asse

42 alignment, which aligns pieces of domains to subsequences, is common in high-throughput annotation ap

43 n successfully applied to the longest common subsequence (LCS) and edit-distance problems, producing

44 he basic idea is to apply the longest common subsequence (LCS) framework to selected pairs of rows in

45 computational algorithm, Longest Increasing Subsequence (LIS) algorithm.

46 ction of specialized data sets and iterative subsequence masking.

47 us or not can be answered by whether the two-subsequence model describes the DNA sequence better than

48 ng-signal was modeled by the distribution of subsequence occurrences (implicit motifs) using self-org

49 A subsequence of CARC1 promotes cohesin binding to neighbo

50 detected point mutations in a 198 base-pair subsequence of the Escherichia coli rpoB gene.

51 of AMI profiles are conserved, even in short subsequences of a species' genome, rendering a pervasive

52 ue array of DNA probes directed against rRNA subsequences of bacteria and fungi for identification.

53 Subsequences of Colias introns match subsequences of oth

54 of the presence/absence of short nucleotide subsequences of different length ('n-mers', n = 5-20) in

55 This paper revisits the question for subsequences of DNA taken at random from the genome.

56 ogram to compare the frequencies of k-length subsequences of nucleotides with the frequencies predict

57 Subsequences of Colias introns match subsequences of other introns, untranslated regions of c

58 ighly perseverative and highly unpredictable subsequences of responses within a test session.

59 records, detailed by gene calls demarcating subsequences of the chromosomes.

60 chored placements to cluster the mappings of subsequences of unanchored ends to identify the size, co

61 e favored than others among fragments (i.e., subsequences) of sequences that encode uniquely, and exa

62 ng an optimal partitioning of non-repetitive subsequences over a prescribed range of tile sizes, on a

63 In each graph, a vertex denotes a similar subsequence pair.

64 A similar analysis was applied to subsequence pairs found by the Smith-Waterman algorithm.

65 ificant short, statistically overrepresented subsequence patterns (motifs) in a set of sequences is a

66 nsemble that place the aggregation-prone tau subsequences, PHF6* and PHF6, in conformations that are

67 to transform the signature into the closest subsequence present in the background.

68 use known algorithms for the longest common subsequence problem as part of our map integration strat

69 Subsequence regions can be selected based on diverse cri

70 am modules that enables precise selection of subsequence regions from records of the RefSeq human gen

71 rogram information about the base, helix, or subsequence selected by the user.

72 ple overlapping subsequences and models each subsequence separately, therefore implicitly takes into

73 for the noncontacted residues between these subsequences, showing that the contact points must be op

74 ds; filtration of reads containing undesired subsequences (such as parts of adapters and PCR primers

75 ferences in the second leg (C) of the repeat subsequence that arise in the first leg (B) because of d

76 strate the algorithm's potential to identify subsequences that are conserved to different degrees.

77 Edges denote pairs of subsequences that can be connected to form higher simila

78 ique sites in DNA sequences by searching for subsequences that closely match the PCR primers and have

79 e that the -12 region core contains specific subsequences that direct the diverse RNA polymerase inte

80 It then extends them to find longer subsequences that may contain full repeats with low comp

81 equence coverage increases with the sizes of subsequence tiles that are to be included in the design.

82 nthetic mini-genes, which include degenerate subsequences totaling over 100 M bases of variation.

83 For small subsequences - up to 1 kb - this correlation is weak but

84 For each of these 25 nt subsequences, we searched a recent human transcript mapp

85 ores generated from the best locally-aligned subsequence were significantly less effective than SSEAR

86 Golem A and B subsequences were only found in primates and squirrel.

87 e homologous to each other and retrieves the subsequences which are conserved between the two DNA seq

88 nded replay is composed of chains of shorter subsequences, which may reflect a strategy for the stora

89 he goal is to find a set of mutually similar subsequences within a collection of input sequences.

90 th problem" and leads to inverted amino acid subsequences within a de novo reconstruction.

91 ization and information-theoretic content of subsequences within a genome are strongly correlated to

92 Conservation of DNA subsequences within amplification origins from the 12 re

93 oups of similar sequences and locally aligns subsequences within them.