ライフサイエンスコーパス: data visualization

1 assembly, polymorphism detection, as well as data visualization.

2 n used in functional inference as well as in data visualization.

3 ssary for further statistical processing and data visualization.

4 in some cases, human manual inspection using data visualization.

5 anizing map-based (SOM) cluster analysis and data visualization.

6 he analytical calculations and provides easy data visualization.

7 ting multilevel replication, and interactive data visualization.

8 the lower-dimensional space, which enhances data visualization.

9 erform automated spatiotemporal analysis and data visualization.

10 nts for different protein states, along with data visualization.

11 nted in C++ for data processing and in R for data visualization.

12 ays, and the value of co-design in producing data visualization.

13 e workstation integrated with smartphone for data visualization.

14 uch as condition modification on the fly and data visualization.

15 mbedding methods are crucial for single-cell data visualization.

16 r real-time interactive single-cell genomics data visualization.

17 designed to meet this need for comprehensive data visualization.

18 that integrates bioinformatics analysis and data visualization.

19 sitional information into their analysis and data visualization.

20 ts, requiring development of novel tools for data visualization.

21 ong with time-gated filtering and innovative data visualization.

22 ace to improve usability, responsiveness and data visualization.

23 from bulk sequence processing to interactive data visualization.

24 and provides integrated tools for expressive data visualization.

25 us statistical analysis and state of the art data visualization.

26 nalysis with the browse-based technology for data visualization.

27 nment, annotation, statistical analysis, and data visualization.

28 rences inaugurated a symposium on Biological Data Visualization.

29 ice and suggesting new strategies for robust data visualization.

30 esigned for ultra high-throughput sequencing data visualization.

31 , statistical modeling, machine learning and data visualization.

32 to serve as a flexible component for genomic data visualization.

33 arameters in addition to publication-quality data visualizations.

34 alize, and enable the sharing of interactive data visualizations.

35 networks for alt text generation of genomics data visualizations.

36 t inferences and generating information-rich data visualizations.

37 romotes both the reading and construction of data visualizations, a pairing analogous to that of both

38 ctive performance, statistical analysis, and data visualization; all without programming.

39 ecological, earth observations sciences and data visualization, among others.

40 e resolution introduces unique challenges in data visualization and analyses.

41 This novel software platform for multimodal data visualization and analysis bears translational pote

42 o support RNA structure research by offering data visualization and analysis capabilities for a varie

43 an open-source software tool for multimodal data visualization and analysis during DBS surgery.

44 The Omics Viewer, a user data visualization and analysis tool, allows a list of g

45 New data visualization and analysis tools include SeqViewer,

46 The combination of multiresolution data visualization and analysis, combined with the phylo

47 Our data visualization and analysis, incorporating statistic

48 igence (AI) algorithms was developed for the data visualization and analysis.

49 seminating models of biological pathways for data visualization and analysis.

50 QPACA supports data visualization and both fine- and coarse-grained spe

51 DELiVR features a comprehensive toolkit for data visualization and can be customized to other cell t

52 tent space that is amenable to interpretable data visualization and clustering.

53 xpanded both in content and in the tools for data visualization and comparison.

54 publicly accessible website that integrates data visualization and curation of current gene annotati

55 lymorphism prediction, PCR primer selection, data visualization and data download in a variety of for

56 ed to include advanced statistical analysis, data visualization and data integration.

57 We examine current practices in data visualization and discuss improvements, advocating

58 hembench provides a broad range of tools for data visualization and embeds a rigorous workflow for cr

59 and is optimized to provide high-performance data visualization and exploration on standard desktop s

60 In this article, we present LocusExplorer, a data visualization and exploration tool for genetic asso

61 ved tables that enable efficient access from data visualization and exploration tools.

62 browsing tool was successfully developed for data visualization and filtering data by several linked

63 al vignette describing common tasks, such as data visualization and gene set enrichment analysis.

64 database has provided high-quality genomics data visualization and genome annotations to the researc

65 The current GlyMDB provides data visualization and glycan-binding motif discovery fo

66 top of the real-world scene, offering unique data visualization and interaction opportunities.

67 tionally, this update offers improvements to data visualization and interpretation, including an occu

68 nhancements and new tools to further improve data visualization and interpretation.

69 en-source data science toolbox that combines data visualization and machine learning, and that is tai

70 gnment tools, such as GMAP, with easy-to-use data visualization and mining tools.

71 package, with a user-friendly interface for data visualization and pathway exploration.

72 s of PathVisio are pathway drawing, advanced data visualization and pathway statistics.

73 Gene expression data visualization and quality control were assessed usi

74 We present a new data visualization and quantification tool developed to

75 sor data onto the Google Glass for on-demand data visualization and real-time analysis.

76 informatics tasks, including classification, data visualization and removal of biases, such as batch

77 ous prototype version by providing versatile data visualization and sophisticated statistical analyse

78 -by-pathway matrix that can be used for both data visualization and statistical enrichment analysis.

79 a website which supports browsing, querying, data visualization and the ability to download raw and c

80 a graphical user interface (GUI) to support data visualization and user interaction.

81 In it, scientists use interactive data visualizations and read deeply in the research lite

82 experimentally manipulate different dynamic data visualizations and show that presenting data highli

83 scriptome sequencing reads, an R library for data visualization, and a Julia script for PofO testing.

84 V) was one of the first tools to provide NGS data visualization, and it currently provides a rich set

85 Furthermore, through feature selection, data visualization, and model discrimination, the most i

86 ps, including read alignment, read counting, data visualization, and statistical testing-this complex

87 tive gene selection, supervised/unsupervised data visualization, and user/prior knowledge guidance, t

88 vailable for browsing through an interactive data visualization app hosted at

89 Lastly, we created an interactive data visualization application for the scientific commun

90 ty modulation of such materials, display and data visualization applications that go beyond data stor

91 emble-based simulations together with unique data visualization approaches establish the foundation o

92 disciplinary utility in conjunction with new data visualization approaches opens up new vistas in ima

93 In this study, we used analytical and data visualization approaches to untangle effects on con

94 ere we use mass spectrometry informatics and data visualization approaches(11-13) to provide an asses

95 Combined with custom data visualization at the group and individual levels, S

96 This i3 is a data visualization based on the Cell Stem Cell tenth ann

97 ation age, the ability to read and construct data visualizations becomes as important as the ability

98 nation of non-trivial steps from statistics, data visualization, bioinformatics and machine learning.

99 offers tools for peptide library generation, data visualization, built-in and public database peptide

100 logy recently acknowledged the importance of data visualization by inaugurating an award for the "Fig

101 us component analysis (ASCA) and exploratory data visualization by principal component analysis (PCA)

102 Data visualization can play a key role in comparative ge

103 Increasing the visual saliency of such data visualizations can help viewers more accurately ide

104 Finally, memes provides data visualization capabilities to facilitate communicat

105 existing imputation methods in reference to data visualization, cell subpopulation identification an

106 We further extended scGAE for scRNA-seq data visualization, clustering, and trajectory inference

107 rom a reusable toolkit of user interface and data visualization components.

108 articipating PX resources, now with enhanced data visualization components.We describe the updated su

109 ibuted stochastic neighbor embedding (t-SNE) data visualization demonstrated that cells cluster based

110 ots from chaotic systems theory as a dynamic data visualization device and show how these plots captu

111 tter pie plots are one type of commonly used data visualization for such data but present perceptual

112 analyses and (iii) introducing a new set of data visualizations for expressed region analysis.

113 Reactome pathways using PathVisio's advanced data visualization functionalities.

114 used in genomics and omics research, but the data visualization has been highly limited in function,

115 Data visualization has developed in several directions:

116 methylation data and single-cell methylation data visualization have been added, and we continue to u

117 y easy-to-use interfaces nor well suited for data visualization in general data formats.

118 Data visualization in reduced-parameter frameworks (e.g.

119 oth an R package and a Shiny app, to improve data visualization in this context, enabling enhanced pr

120 reasing need for rich and dynamic biological data visualizations in bioinformatic web applications.

121 ology research allowing for complex queries, data visualization, integration, and formatting.

122 chromatin interaction maps enables effective data visualization, integration, and mining.

123 Data visualization is a crucial tool for data exploratio

124 Data visualization is a pivotal component of a structura

125 Data visualization is an essential component of genomic

126 Data visualization is an important tool that epidemiolog

127 Data visualization is critical for interpreting biologic

128 Interactive data visualization is imperative in the biological scien

129 A crucial component of intuitive data visualization is presenting a hierarchical tree str

130 nd interactive visualizations, like genomics data visualizations, is even more challenging.

131 ematical, and visual literacy exist, current data visualization literacy (DVL) definitions and framew

132 This paper introduces a data visualization literacy framework (DVL-FW) that was

133 of phylogenetic placement of new samples and data visualization, making it possible to complete the p

134 s quality control, data bias correction, and data visualization methods with a mass-aware gridding al

135 Nonlinear data visualization methods, such as t-distributed stocha

136 ds offers a fully integrated environment for data visualization, motif finding, and comparative analy

137 hon Dash as a web-based toolbox designed for data visualization of zonal gene expression patterns in

138 ption generation tool focused on interactive data visualizations of genome-mapped data, created with

139 Furthermore, we have implemented extensive data visualizations, on-the-fly data filtering, and a ba

140 ent plotgardener, a coordinate-based genomic data visualization package that offers a new paradigm fo

141 Data were geocoded and analyzed in a data visualization platform from March 1 to December 1,

142 We additionally develop a data visualization platform, named ApplE Turnover, that

143 interactive data query or as part of genomic data visualization platforms such as genome browsers.

144 Data visualization plays a critical role in interpreting

145 Data visualization plays critical roles in proteomics st

146 ion, we have developed a public, interactive data visualization portal based on the data generated fr

147 isual Omics Explorer (VOE), a cross-platform data visualization portal that is implemented using only

148 , and to assess the prevalence of suboptimal data visualization practices.

149 ses for functional annotation, and generates data visualizations-providing a streamlined and reproduc

150 eal time and features a powerful interactive data visualization report.

151 ecause of the multidimensional nature of the data, visualization requires interactive multidimensiona

152 Typical data visualizations result from linear pipelines that st

153 In addition to pathway analysis and data visualization, SBGNview provides essential infrastr

154 sive Care Unit pre and postimplementation of data visualization software analyzed within the Pediatri

155 Data visualization software has been used to profile org

156 ods to assess implementation of a commercial data visualization software in our pediatric cardiac int

157 rs, adults 18-64 years) using chi2 tests and data visualization software.

158 Finally, we propose data visualization strategies for the inspection of the

159 organized sharing of multistep analyses and data visualization strategies.

160 ools fall into five major application areas: data visualization, structure comparisons, similarity se

161 Data visualizations such as Manhattan-like plots, region

162 The KGraph is a data visualization system that has been developed to dis

163 d coordinates is a challenging but important data visualization task, particularly for spatially reso

164 s enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) cr

165 s of 3D VizStruct, a novel multi-dimensional data visualization technique for analyzing patterns in S

166 s of 3D VizStruct, a novel multi-dimensional data visualization technique for SNP datasets capable of

167 As data visualization techniques become cumbersome for high

168 Data visualization techniques were used to ascertain (1)

169 statistical procedures with state-of-the-art data visualization techniques, NetworkAnalyst allows res

170 many widely used statistical approaches and data visualization techniques.

171 gh-performance genetics and genomics-related data visualization that enables fast, simultaneous plott

172 accessibility data; demonstrate informative data visualizations that synthesize multiple modalities;

173 ariability for individual patients, improved data visualization, the use of artificial intelligence m

174 Functional Heatmap offers time-series data visualization through a Master Panel page, and Comb

175 However, there is no standard for data visualization to contextualize events of interest,

176 d the coverage of pathway-based analysis and data visualization to essentially all major pathway data

177 that lead to a sex-balanced sample; iii) use data visualization to grasp the effect of sex; iv) imple

178 ynamics (EPD) 'KinoViewer' is an interactive data visualization tool designed for analysis and explor

179 Additionally, our data visualization tool enables efficient exploration of

180 e Browser (DCB), an online interactive HTML5 data visualization tool for interacting with three of th

181 nciple, following up our well-received omics data visualization tool Quickomics, RNASequest automates

182 We present an interactive data visualization tool that allows broad access to our

183 the technology now exists to build a genomic data visualization tool that meets these requirements.

184 und the world, we also present anopen-source data visualization tool that summarizes these studies an

185 We designed an interactive spills data visualization tool to illustrate the value of havin

186 We developed a novel data visualization tool to provide an integrated view of

187 Comparative data visualization tool use by stewards at 8 VA faciliti

188 Comparative data visualization tool use by stewards in a pilot imple

189 ions of pViz using two examples: a proteomic data visualization tool with an embedded viewer for disp

190 ontrol and Prevention U.S. Cancer Statistics Data Visualizations Tool.

191 We developed genome data visualization toolkit (GDVTK) as an application fra

192 d Microsoft's PivotViewer software (iii) new data visualization tools and (iv) the interrelation of F

193 A suite of data visualization tools and comprehensive links with ex

194 e among the most informative high-throughput data visualization tools capturing plate-wise and screen

195 s, semantically annotated API endpoints, and data visualization tools contributed by an ecosystem of

196 rSegger provides a variety of postprocessing data visualization tools for single cell and population

197 Transcript data visualization tools include Quality Screening, Mult

198 to interoperate with other data analysis and data visualization tools such as Cytoscape.

199 e as an R/Bioconductor package that includes data visualization tools useful for bias discovery.

200 The integrated data visualization tools, faceted search infrastructure,

201 s, advanced search capabilities and enhanced data visualization tools, making it easier for users to

202 maps to serve as a scaffold for a variety of data visualization tools.

203 rching, which until now lacked comprehensive data visualization tools.

204 ssing and analysis, the latter consisting of data visualization, track description, path reconstructi

205 licly available databases and gene sets, and data visualization using dimension reduction methods.

206 rsible and multiple-time use of colorimetric data visualization using electrophoretic display (EPD).

207 To improve data visualization, we added a Cytoscape Web view to our

208 All statistical analyses and data visualizations were conducted using R.

209 ct type of clustering tendency, are used for data visualization, which increases the likelihood that

210 s through easily creating interactive online data visualizations, which colleagues can query accordin

211 rovides intuitive user control and real-time data visualization, with support for multiple devices.

212 t both structural representation and dynamic data visualization within the SBML model.