ライフサイエンスコーパス: biological model

1 lation of Hif1a and Vegfa expression in this biological model.

2 ethods to tease out imperfections in a given biological model.

3 for the scientific community to generate new biological models.

4 ificance and in providing more interpretable biological models.

5 rts using synthetic H2 S donors in different biological models.

6 ion integration environment for quantitative biological models.

7 ry environment, they become less relevant as biological models.

8 the elucidation of gene function in numerous biological models.

9 both effectors and regulators of disease in biological models.

10 pproach will have much wider applications in biological modeling.

11 the olfactory system an important system for biological modelling.

12 xt statements to create, import, and combine biological models, allowing complex models to be built f

13 can create a meta-model of a simulation of a biological model and link that meta-model to experiment

14 is often argued that this is not a realistic biological model and that epistasis (that is, the statis

15 his review, we discuss the theory underlying biological modeling and the process of producing a valua

16 ood glucose levels have been demonstrated in biological models and in clinical trials.

17 It serves to aid the construction of cell biological models and the generation of simulations from

18 New biological models are being developed which explain caus

19 New biological models are incorporating the realistic proces

20 ygen radical absorbance capacity (ORAC), and biological model as 2,2'-azobis (2-aminopropane) dihydro

21 es can modulate tau aggregation in the slice biological model at concentrations well below those asso

22 Our results indicate that, when building biological models based on published experimental data,

23 We chose TRAIL as a biological model because it inhibits activated lymphocyt

24 The structure and dynamics of a biological model bilayer are reported with atomic-scale

25 ubstrates of proteolytic enzymes in relevant biological models, both historical and focusing on state

26 d SMLM imaging to a broad range of available biological models, but also present unique insights into

27 ents and trace metals at basal levels in two biological models, cells of Chlamydomonas reinhardtii an

28 This biological model closely mimics the human setting and pe

29 erefore, developing an accurate and powerful biological model for bipolar disorder has been a challen

30 Here, we outline a viable cell-biological model for generating synaptic specificity tha

31 Here we identify a biological model for polaro-crypsis.

32 olution of early cells and provide an extant biological model for studying this problem.

33 low the development of a proper physical and biological model for telomere subdynamics.

34 aken together, these findings provide a cell biological model for the role of this metallochaperone u

35 Thus, a biological model for toxicity and animal disease can be

36 e association studies and exploration of new biological models for allelic exclusion in the human gen

37 uently, CPGs have been suggested as valuable biological models for understanding of microcircuit dyna

38 Evidence from multiple biological models, from stem cells to ex vivo biophysica

39 The concurrent revival of the biological model has led to postmodernist counter-reacti

40 igenic) stimulation in a multistate leukemia biological model (i.e., chronic lymphocytic leukemia).

41 Here we use a biological model in which HOXB6 represses alpha- and gam

42 her, the exploration of OncoPPi led to a new biological model in which MKK3 operates by two distinct

43 els with few free parameters to more complex biological models in humans lies in constraining the mor

44 time and its activity was studied in several biological models including transiently or stably transf

45 g of nanotopological changes in a variety of biological models, including extracellular matrix (ECM)

46 Various other biological models, including human keratinocytes (HaCaT)

47 Among a wide range of biological models involving the independent ancestry of

48 Parameter estimation in biological models is a common yet challenging problem.

49 anism of action and potential for testing in biological models is fragmentary.

50 climate-driven statistical, and mechanistic biological models, little work has been done to understa

51 review, we distinguish between two types of biological models--mathematical and computational--which

52 ogically realistic stochastic models to test biological models more stringently and make predictions

53 ed with the surface, supporting a conceptual biological model of depth-dependent physiology.

54 Taken together, these data provide a cell biological model of SOD1 biosynthesis that is consistent

55 iew, we first briefly review theoretical and biological models of addiction and then describe existin

56 This paper examines two biological models of anticancer activity, cytotoxicity a

57 sted using the FRAP and DPPH assays, and two biological models of lipid oxidation (activity in preven

58 tially present an overview, which focuses on biological models of lymphatic networks within the breas

59 Biological models of obsessive-compulsive disorder propo

60 interpretation of pharmacological studies in biological models of tau aggregation.

61 Current chronological, behavioral, and biological models of this transitional period hinge on t

62 esearchers to quickly develop and simulate a biological model on a desktop or laptop, which can then

63 the effects of changing various physical and biological model parameters on the developing vascular a

64 d to exploratory data- and hypothesis-driven biological modeling problems.

65 After, frozen cryo-sections from a biological model system were measured by exploiting the

66 typic cortical cultures from rat brains as a biological model system, in which spontaneous neuronal a

67 Using this powerful biological model system, we have discovered key pathways

68 age in the nucleus, has provided very useful biological model systems for the study of the function o

69 tions encompassed chemical, biochemical, and biological model systems generating C-centered radicals.

70 nt and regeneration is hampered by a lack of biological model systems that recapitulate key aspects o

71 the key functional capabilities of important biological model systems while abstracting away from the

72 are readily applicable to a wide spectrum of biological model systems.

73 odel is translated directly into a plausible biological model testable by single-particle tracking.

74 Our results suggest the biological model that high-affinity DNA binding by Teb1A

75 Development of simplified biological models that would allow us to better understa

76 Using a biological model (the mudskipper), a physical robot mode

77 hology, consistent with other MDRS-deficient biological models, thus providing a framework for the en

78 It provides an important biological model to investigate mechanisms underlying th

79 simple procedure (called varphi ) to reduce biological models to functional submodules, using statis

80 stituted an accessible, easily usable set of biological models to investigate cancer biology and expl

81 ntrolling signal transduction; (ii) evolving biological modeling tools describing cellular circuits a

82 Moreover, biological models underpin each category uniquely and wi

83 A popular biological model used to study arrhythmogenesis is the c

84 city based on the assay results from all the biological models used in this study, whereas S-TiO2 was

85 riation in methods of exhaust generation and biological models used to assess responses.

86 tion with experimental data and diagrammatic biological models via the common underlying ALFA represe

87 Relative absorption, in chickens as the biological model, was determined by evaluating growth an

88 Using surrogate genetics in a powerful biological model, we dissect a poorly understood hypoxia

89 els to cooperatively drive computational and biological modeling, which together could eventually lea

90 The zebrafish embryo is a highly interesting biological model with applications in different scientif

91 MVS set-point adaptation is a biological model with applications to basic neurophysiol

92 This approach combining biological modeling with high-content imaging provides a