ライフサイエンスコーパス: NMF

1 NMF appears to have advantages over other methods such a

2 NMF distinguished all three mutagens and in the pooled a

3 NMF levels are highly correlated with corneocyte morphol

4 NMF levels were ascertained using confocal Raman spectro

5 NMF values were also inversely correlated with skin surf

6 We have developed a NMF analysis plug-in in BRB-ArrayTools for unsupervised

7 r evaluation of the safety and efficacy of a NMF remains a challenge.

8 products of filaggrin-derived amino acids ("NMF") but also endogenous glycerol from circulation into

9 on with alternating least-squares algorithm (NMF-ALS) to solve spectral overlaps.

10 ork for any stochastic clustering algorithm, NMF is an efficient method for identification of distinc

11 or the non-negative coefficient matrix in an NMF needs to be controlled in approximating high-dimensi

12 nal distance between sites, and find that an NMF-filtered measure of functional distance is more stro

13 induction of apoptosis by both etoposide and NMF was associated with a reduction in the cellular leve

14 atients with AD stratified by FLG status and NMF level.

15 the manual pipeline can be replaced with any NMF algorithm, for further generalization of the softwar

16 orithm is described, which works by applying NMF to the envelope matrix (envelopogram) of 22 frequenc

17 APS), the first robust whole genome Bayesian NMF using the sparse, MCMC algorithm, CoGAPS.

18 We found a strong correlation between NMF levels and Dermal Texture Index scores in both acute

19 s of structural covariance (PSCs) derived by NMF were highly reproducible over a range of resolutions

20 isomerase II induced by etoposide but not by NMF.

21 In most cases, NMF accurately decomposed the images into contributions

22 ntly described variant of NMF, namely Convex-NMF, as an unsupervised method of source extraction from

23 The application of Convex-NMF in computer assisted decision support systems is exp

24 The unsupervised properties of Convex-NMF place this approach one step ahead of classical labe

25 in fully unsupervised mode and using Convex-NMF as a DR step previous to standard supervised classif

26 However, ICRF-193 had no effect on either NMF- or camptothecin-induced DNA fragmentation.

27 ying any peak aggregation method (especially NMF and PCA) improves the statistical prediction power o

28 er computing time compared to other existing NMF algorithms.

29 isfactory results in such cases, we extended NMF to incorporate preexisting qualitative knowledge abo

30 lvent systems: water, 6 M urea in water, FA, NMF, and DMF.

31 um corneum (SC) natural moisturizing factor (NMF) components and consequent increased SC pH.

32 e components of natural moisturizing factor (NMF) showed the distribution of water to be higher and h

33 constituents of natural moisturizing factor (NMF), important in maintaining SC hydration.

34 kdown products (natural moisturizing factor [NMF]), and corneocyte morphology in patients with AD.

35 find that non-negative matrix factorisation (NMF) clearly outperforms principal components analysis.

36 range of Non-negative Matrix Factorisation (NMF) methods in two respects: first, to derive sources c

37 by using non-negative matrix factorisation (NMF) techniques.

38 eveloped a nonnegative matrix factorization (NMF) algorithm to detect and separate spectrally distinc

39 Non-negative Matrix Factorization (NMF) algorithms associate gene expression with biologica

40 is method non-negative matrix factorization (NMF) has been applied to the analysis of gene array expe

41 ved using non-negative matrix factorization (NMF) into discrete trinucleotide-based mutational signat

42 Non-negative matrix factorization (NMF) is an increasingly used algorithm for the analysis

43 then use non-negative matrix factorization (NMF) to approximate these protein family profiles as lin

44 s, we used nonnegative matrix factorization (NMF) to uncover coordinated patterns of cortical develop

45 chniques: non-negative matrix factorization (NMF) using additional sparse conditioning (SC), and the

46 ntation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criteri

47 the use of nonnegative matrix factorization (NMF), an algorithm based on decomposition by parts that

48 is (PCA), non-negative matrix factorization (NMF), maximum autocorrelation factor (MAF), and probabil

49 s, such as nonnegative matrix factorization (NMF).

50 based on non-negative matrix factorization (NMF).

51 s in the mean-field (MF) and non-mean-field (NMF) regions corresponding to d >/= 4 and d < 4 for the

52 The algorithms used for NMF and Semi-NMF are available at ftp://linus.nci.nih.go

53 The development of new medical formulations (NMF) for reconstructive therapies has considerably impro

54 led with nanoporous material functionalized (NMF) liquid.

55 We conclude by discussing how NMF, and other dimension reduction methods, can help ena

56 Due to the nanoscale infiltration in NMF liquid and its interaction with cell walls, the cell

57 n of the so-called peak aggregation methods (NMF Reduction, PCA Decomposition, Maximum Peak, and Spec

58 icroM etoposide or 300 mM N-methylformamide (NMF), a nongenotoxic agent.

59 solvents, formamide (FA), N-methylformamide (NMF), and N,N-dimethylformamide (DMF) were compared to t

60 Use of N-methylformamide (NMF), which has not previously been a solvent known for

61 onses to the DA uptake blocker, nomifensine (NMF), were assessed in these preparations.

62 We demonstrate the ability of NMF to recover meaningful biological information from ca

63 ng has contributed to the recent approval of NMF such as GEM 21S and INFUSE bone grafts for periodont

64 significant decrease in the concentration of NMF was observed for corneocytes isolated from superfici

65 infants than in adults; the concentration of NMF was significantly lower in infants.

66 te pre-clinical models for the evaluation of NMF in situations requiring periodontal or oral reconstr

67 The stability of NMF-generated mutational signatures depends upon the num

68 mples of screening and functional studies of NMF that can be translated into clinical use.

69 and molecular structure in the treatment of NMF-related diseases is discussed.

70 age of using a recently described variant of NMF, namely Convex-NMF, as an unsupervised method of sou

71 cal validation and enhanced visualization of NMF results.

72 ariate associations, the relative weights of NMF solutions can obscure biomarkers.

73 Treatment with etoposide or NMF induced the morphology of apoptosis within 4 hr.

74 ze of the factor model and outperforms other NMF models in predicting RBP interaction sites on RNA.

75 cale similarity between expression patterns, NMF is a recently developed machine learning technique c

76 tissue); second, taking the best performing NMF method for source separation, we compare its accurac

77 are available at ftp://linus.nci.nih.gov/pub/NMF.

78 An IR parameter that measures the relative NMF concentration in corneocytes is introduced.

79 tly used in the literature and with the same NMF parametrization as the one considered here.

80 The algorithms used for NMF and Semi-NMF are available at ftp://linus.nci.nih.gov/pub/NMF.

81 tool also incorporates an algorithm for Semi-NMF which can handle both positive and negative elements

82 new formulation leads to a convergent sparse NMF algorithm via alternating non-negativity-constrained

83 , we introduce a novel formulation of sparse NMF and show how the new formulation leads to a converge

84 We apply our sparse NMF algorithm to cancer-class discovery and gene express

85 results illustrate that the proposed sparse NMF algorithm often achieves better clustering performan

86 ion encoder to 80% to 100% for the suggested NMF coding strategy was observed.

87 n artificially generated sequences show that NMF can faithfully reproduce both positioning and conten

88 The NMF analysis plug-in is freely available in BRB-ArrayToo

89 the two approaches markedly disagree in the NMF case, where the MC data indicates a transition, whil

90 estimate of the critical exponent nu in the NMF region is about twice as large as its classical valu

91 results indicate that the transition in the NMF region is governed by strong non-perturbative effect

92 Finally, we demonstrate the use of the NMF approach through characterization of biologically in

93 ed on an empirical Bayesian treatment of the NMF model.

94 high dimensionality and nonconvexity of the NMF paradigm.

95 r large-scale DNA methylation studies, while NMF does well in the unsupervised context.

96 these levels were inversely correlated with NMF levels.