ライフサイエンスコーパス: computational

1 ovel research methods that take advantage of computational advances and multiscale modeling for the a

2 endent regulation while still retaining many computational advantages of FBA.

3 the development of programmes for performing computational alanine-scanning mutagenesis (CASM) to gui

4 We present EPISCORE, a computational algorithm that performs virtual microdisse

5 tors to their target promoters using a novel computational algorithm, target inference via physical c

6 al properties of the functional circuits and computational algorithms for motion vision.

7 Computational analyses of pathogen genomes are increasin

8 Our computational analyses reveal that the receptive fields

9 Results from thermodynamic, kinetic, and computational analyses suggested that this 12-mer is hig

10 Previous computational analysis indicated that the oxygen (O(2))

11 y information in biological research and the computational analysis of high-throughput biochemical da

12 facilitate the inclusion of exposure data in computational analysis of human disease.

13 Here, using computational analysis of published data, we have identi

14 tro DNA binding assays coupled with unbiased computational analysis provide unprecedented insight int

15 Computational analysis revealed that reward led to both

16 mass spectrometry data acquisition types and computational analysis tools.

17 A density functional theory (DFT) computational analysis, using the omegaB97X-D functional

18 Using multiple length scale imaging and computational analysis, we discovered unique spatial des

19 ities of traumatic brain injury, we combined computational, analytical, and experimental approaches t

20 Altogether, these computational and experimental approaches allow assessme

21 Here we used computational and experimental approaches to examine the

22 Herein we describe a combination of computational and experimental design of cobaltocene met

23 Furthermore, we provide computational and experimental evidence that GAT1508 is

24 Here we report on a combined computational and experimental study about ultrafast dif

25 Structural analysis together with computational and mutagenesis studies reveal the molecul

26 Together, our work provides a computational and neural account of why people learn les

27 to articulate the need to train students in computational and systems biology using research-grade t

28 The combined experimental, computational, and dynamic trajectory study here suggest

29 molyte synthesis and transport, but the main computational approach for predicting metabolic network

30 s of clinical trial drug confirming that our computational approach is an efficient and cost-effectiv

31 n this study, we present a rapid, predictive computational approach that combines a popular, sequence

32 hese results provide an initial example of a computational approach to design bicyclic peptides to ta

33 e used stability selection as an alternative computational approach to identify an optimal signature

34 We use a computational approach to propose a proof of concept mod

35 atility to cerebral vasculature, employing a computational approach using a one-dimensional model of

36 terized in detail by a combined experimental/computational approach using X-ray diffraction; UV/vis,

37 ucing agent using a synergistic experimental-computational approach.

38 Computational approaches for analysis of allosteric coup

39 e strengths and limitations of commonly used computational approaches for exploring cell biological q

40 To date, many computational approaches have been developed to solve th

41 The "litmus test" will be whether computational approaches that are successfully identifyi

42 this deficiency, we have previously employed computational approaches to deduce global dynamics of th

43 In this study, we used computational approaches to develop a structural model o

44 Integrating multiple computational approaches, UPF3B-dependent NMD target tra

45 Using live imaging and computational approaches, we found that the transcriptio

46 actions was investigated by experimental and computational approaches.

47 ual hypotheses and thereby shed light on the computational architecture of cortex.

48 lluminate both their pathophysiology and the computational architecture of the cognitive processes th

49 In order to understand the computational architecture of the cortex, we need to inv

50 ral systems biology enables a proteome-wide, computational assessment of changes to atomic-level phys

51 uming biological experiments and allowed for computational assessment of MeONP inflammatory potential

52 ange of virus host prediction tasks enabling computational assignment of host taxonomic information.

53 To ease this computational barrier, we have created a dynamic web-bas

54 kelihood of complex models in fields such as computational biology and neuroscience is often intracta

55 sobering statistics, most bioinformatics and computational biology research and funding to date has b

56 he analysis of complex data in areas such as computational biology, ecology and econometrics.

57 parameters of networks is ubiquitous across computational biology.

58 provided several insights, they face several computational challenges.

59 rected mutagenesis, and crystallographic and computational chemical studies to show that (i) the Out

60 s of machine learning models in the field of computational chemistry by considering selected studies

61 thod of using a neural network to reduce the computational complexity of an intracellular signaling m

62 n a trade-off among power consumption, cost, computational complexity, and accuracy.

63 nd Glu balance on the prediction of specific computational components of motivated performance.

64 s of SCMs are identified, and then proven by computational construction.

65 e boundary noise and reduces drastically the computational cost allowing for large data volume annota

66 lightweight approaches without incurring the computational cost of traditional alignment.

67 search algorithms, statistical analysis, and computational cost to achieve coverage of 1 unique cross

68 on of the paths for large networks with less computational cost.

69 The latter significantly reduces the computational cost.

70 s the state of the art, at comparably little computational cost.

71 We combine state-of-the-art computational crystal structure prediction (CSP) techniq

72 Structural and computational data suggest the nature of the 5-R substit

73 Specifically, we conducted three computational decoding experiments that investigated dec

74 tools in fluorescence microscopy is that of computational deconvolution.

75 sed the FLE and functioned to compensate for computational delays was hotly debated in the years that

76 chanistic rationale is supported by detailed computational density functional theory studies, which f

77 A key step of an automated computational design algorithm is molecule generation, w

78 We present a computational design method, loop-helix-loop unit combin

79 nimal synthetic plant promoters enabling the computational design of a suite of synthetic promoters o

80 To enable computational design of binders, we developed a unit of

81 Our study demonstrates that refined computational docking and simulation studies combined wi

82 mophoresis measurements, NMR titrations, and computational docking calculations, as well as biologica

83 We apply our methods and existing computational doublet identification approaches to four

84 tical information for structure-assisted and computational drug design, allowing precise tailoring of

85 principles for small-molecule combinations, computational drug-combination design has not seen gener

86 gs provide a framework for understanding the computational effects of chloride dynamics on dendritica

87 ivity, positive predictive value or PPV, and computational efficiency) of different metagenome analys

88 y the underlying FE foundation, such as high computational efficiency, parallelizability, low numeric

89 The analysis of our extensive computational efforts reveals that social distancing and

90 Computational error correction promises to eliminate seq

91 We provide computational evidence that late transition metals adopt

92 ormed multistep biochemical, structural, and computational experiments to define a spherical 24-monom

93 Our non-invasive approach, a combination of computational fluid dynamics and high-resolution micro-C

94 the droplet motion in the channel flow using computational fluid dynamics simulations and a previousl

95 We used computational fluid dynamics simulations of low-altitude

96 Using computational fluid dynamics, we show that osteostracan

97 To address this, we propose a general computational framework for adapting to novel tasks base

98 We developed a computational framework for identifying putative deleter

99 The reconstructive computational framework for model and data discovery dev

100 ytics (BUAN) is a fast, robust, and flexible computational framework for real-world tractometric stud

101 rallel residual projection (PRP), a parallel computational framework involving the decomposition of a

102 A computational framework is developed to identify biomark

103 Although the computational framework presented here is developed for

104 Here, we present a computational framework that aligns ChIP-exo crosslinkin

105 Checking Engine (SMCE), a probability-based computational framework that considers a set of paramete

106 Overall, our work provides a computational framework that explains changes-of-mind in

107 predictive linkage to expression (MAPLE), a computational framework that learns the association betw

108 As a whole, this study presents a new computational framework that serves as a high throughput

109 Behind this application, SMCE remains a computational framework that supports the projection of

110 A computational framework was used to elucidate the reinfo

111 of the efficient implementation of the same computational function-fast sampling-based inference-and

112 Our method combines computational geometry and graph theory to measure the d

113 A custom computational imaging algorithm we call SARA-COIL is use

114 hed protocols for experimental detection and computational inference of CNVs from SNP array and next-

115 isotope effect studies, in combination with computational investigations, reveal that two different

116 story-dependent programs by distributing the computational labor across a cellular population.

117 isciplinary approach has been a focus on the computational level of analysis, leading to the developm

118 es the value of enzyme stabilization through computational library design.

119 plex interactions are analyzed, the space of computational mechanisms must be constrained based on wh

120 tervention, though the precise cognitive and computational mechanisms that explain treatment response

121 nonlinear equations, which are solved via a computational method called the step-by-step linearizati

122 Our objective is to develop and use a computational method for multi-modal analysis of changes

123 Here, we describe a computational method HiNT (Hi-C for copy Number variatio

124 Here we provide a computational method named "BCREval" to estimate the unc

125 To address this, we propose DiNeR, a computational method to directly construct a differentia

126 Here, we present a computational methodology and mathematical formalism to

127 Here, we present an experimental and computational methodology that uses scRNA-seq to charact

128 The currently available computational methods are only considered features in pr

129 Our findings demonstrate that unbiased computational methods are particularly valuable for stud

130 erest has spurred the refinement of existing computational methods as well as the designof new ones,

131 Our results demonstrate the promise of computational methods based on autoencoding and optimal

132 more accessible, it could ultimately enable computational methods for chemical assessment that can t

133 advances and future research directions for computational methods for CNA detection from scDNAseq da

134 Many scientific disciplines rely on computational methods for data analysis, model generatio

135 Most studies of computational methods for gene expression analysis use s

136 We find that the proposed computational methods frequently provide useful real-tim

137 Currently, several computational methods have been developed to facilitate

138 tion in those genomes has been measured with computational methods often developed specifically for t

139 zation of 2 using combined spectroscopic and computational methods revealed that 2 is a low-spin (S =

140 s often do not corroborate with results from computational methods that are primarily designed for no

141 nscriptional noise on the ability of leading computational methods to assemble and quantify the genes

142 t years, transcriptome-wide experimental and computational methods to study RBPs and their interactio

143 Lacking appropriate computational methods, information hidden inside the iso

144 t based format of ped files is efficient for computational methods, it is not immediately intuitive t

145 a modulator/promoter of LLPS in cells using computational methods.

146 A computational model attributes effects of pEMT mainly to

147 Here, we introduce a computational model in which hippocampus subserves place

148 A computational model of a chain of lymphatic contractile

149 sed the discrete element method to develop a computational model of a deformable cell that includes s

150 ble rate, the dream of a fully comprehensive computational model of a living cell may be drawing clos

151 Our computational model of BD hippocampal neurons that was b

152 s ago, David Marr and James Albus proposed a computational model of cerebellar cortical function base

153 isional accounts of confidence and propose a computational model of confidence in which metacognitive

154 y assemble a bipolar spindle, we developed a computational model of fission-yeast mitosis.

155 Here, we have developed a novel computational model of human mitotic cell cycle, integra

156 We then applied our method to a simple computational model of microtubule dynamic instability.

157 To simulate MS and HB, an existing computational model of polarization-dependent properties

158 ther explore these effects, we implemented a computational model of the hippocampus, performing the s

159 We consider the impact of the computational model on computed linear free-energy relat

160 This dilemma necessitates a computational model that can predict NN thermodynamics w

161 nt as a search process and use a mechanistic computational model that combines polarity protein bioch

162 munity-driven data-reporting standards and a computational model that will facilitate the inclusion o

163 We sought to fill this gap by fitting a computational model to data (n = 1754) from a modified s

164 hypotheses often relies on the ability of a computational model to explain the data, quantified in m

165 We created a computational model using sparse maximum likelihood to e

166 subsequent investigation using a hippocampal computational model, revealing increased representationa

167 learning, as measured using a probabilistic computational model, while trait cognitive anxiety sympt

168 l approach to PSC that can be applied to any computational model.

169 Combined approaches of computational modeling and quantitative measurement reve

170 o biochemical reconstitution, and supporting computational modeling and simulation, to demonstrate th

171 ination with multivoxel pattern analysis and computational modeling based on inverted encoding model

172 c and spectroscopic experiments coupled with computational modeling demonstrate that the compelling p

173 Unbiased computational modeling further predicted an interaction

174 nt innervation in gerbils of both sexes with computational modeling of a single cell.

175 Emerging studies in computational modeling of decision making, caregiver-rel

176 solution structure of the aptamer and enable computational modeling of the docked complex with RT.

177 operties, we compared experimental data with computational modeling results.

178 Computational modeling revealed that dominant learning m

179 Here, we use computational modeling to assess whether known GTPase dy

180 ne microfluidics, time-lapse microscopy, and computational modeling to investigate how the type I int

181 ution assay and egg extract experiments with computational modeling to show that differences in intri

182 Here, we use high-resolution microscopy, computational modeling, and in vitro and in vivo cell in

183 Using computational modeling, we find that the early pathologi

184 On the neural level, computational modeling-based fMRI analyses revealed that

185 hput screening (HTS) in vitro approaches and computational modeling.

186 Computational modelling and multivariate analyses identi

187 ,([1]) single-crystal X-ray diffraction and computational modelling indicate that the isostructural

188 Behavioural computational modelling indicated that precision weighti

189 In both types of judgment, computational modelling revealed that reward information

190 We applied single-cell RNA sequencing and computational modelling to track memory development duri

191 ed, high-resolution environmental layers and computational modelling.

192 Thus, computational models are learning tools that help direct

193 Computational models for SHM targeting often model the t

194 our findings, we developed configural-based computational models involving vector addition, the seco

195 n this Perspective we explain how executable computational models meet this need.

196 Computational models of ARDM will help to establish a qu

197 ional magnetic resonance imaging informed by computational models of sign- and goal-tracking.

198 es governing gene silencing, and a series of computational models of the biological mechanism of the

199 ine learning is a powerful tool for creating computational models relating brain function to behavior

200 Computational models show that the inactive and active s

201 es and the incipient use of mathematical and computational models to characterize these interactions

202 ed for methods facilitating the expansion of computational models to incorporate these newly-discover

203 provides a new way to evaluate and constrain computational models with brain activity and pushes our

204 Here, using structure-based computational models, we demonstrate that the SARS-CoV-2

205 hat predicted -Fe-induced gene expression in computational models.

206 But increasingly, stories are told using computational molecular physics (CMP).

207 ng field attempting to translate advances in computational neuroscience and machine learning into imp

208 the most enduring and influential models in computational neuroscience, despite apparent falsificati

209 Here we propose a novel method for computational optimization of associative learning exper

210 framework across a wide variety of tasks and computational paradigms, ranging from regression to imag

211 A computational pathology pipeline (CRImage) was used to c

212 We evaluate computational performance using simulated data, and show

213 psychological assessments to develop a novel computational phenotyping method that groups brain regio

214 We used the same computational pipeline to analyze publicly available exp

215 Here, we present an open-source computational pipeline to produce 3D consistent histolog

216 We developed a computational pipeline, where the inputs of a cryo-EM ma

217 Here we employed an innovative computational platform, Mining of Synthetic Lethals (MiS

218 The experimental and computational platforms developed here provide a framewo

219 As computational power and speed continue to increase at a

220 AB, ABC | ABC), the latter requiring greater computational power to be processed.

221 ause of the lack of enough training data and computational power.

222 In agreement with the computational prediction, LNZTO demonstrates the best sy

223 oscopy (cryo-EM), x-ray crystallography, and computational predictions were used to build molecular m

224 gap can be reduced with the help of accurate computational predictors.

225 s interact during visual processing and what computational principles underlie these history dependen

226 imulation is a distinct and more challenging computational problem-this is what the brain must actual

227 Current state-of-the-art approaches to computational protein design (CPD) aim to capture the de

228 Computational protein design (CPD) can address the inver

229 Here, computational protein-protein docking was used to deline

230 Computational psychiatry is a rapidly growing field atte

231 ms across 14,611 genes, without the need for computational reconstruction of gene models.

232 We now describe a computational rendering of our methodology that creates

233 Computational reproducibility means providing software s

234 genome, but the method required substantial computational resources and did not scale to gigabase-si

235 actually "optimal" relative to the limits on computational resources available may have some value, b

236 cal unfolding while minimizing the amount of computational resources required by the large water box

237 due to the sheer volume of data, inadequate computational resources to handle an oversized problem,

238 gnment, to best fit their analysis needs and computational resources.

239 demonstrate that NA underpins behavioral and computational responses to uncertainty.

240 The computational results for a realistic scalp EEG database

241 iscrimination, with behavioral responses and computational results indicating variation from single-t

242 eling and molecular dynamics was applied and computational results were analyzed in comparison with a

243 The computational results were validated experimentally (up

244 Our results highlight the computational role of these regions in exploration and s

245 itical aspects of the data while maintaining computational scalability.

246 Computational science has been greatly improved by the u

247 andalone R package to allow experimental and computational scientists to easily navigate the tool.

248 n the nuclear positioning; we therefore used computational screening to reverse-engineer and identify

249 Several computational search algorithms have been developed for

250 We used a sophisticated computational search of thousands of expression datasets

251 Quantitative frameworks involving both the computational simulation and the discretization of data

252 We developed a computational simulation model to quantify the clinical

253 We combine experimental investigations with computational simulation to understand the mechanism of

254 hes-bioinformatics, analytical modelling and computational simulation-to understand the diverse gene

255 Computational simulations suggest that increased tempora

256 Through computational simulations, we investigated fluid mixing

257 organized cortical areas available for later computational specialization.

258 To demonstrate computational spectroscopy, we provide our algorithm wit

259 tly, however, we observe that the utility of computational stability predictors is highly heterogeneo

260 Therefore, computational stability predictors, which assess whether

261 In addition, our computational strategy can be applied to other cancer or

262 In this study, we describe a novel computational strategy named loci2path that takes advant

263 ed to enable users to download the SQL file, computational structural features and PTM sites' data.

264 e experimental observations are supported by computational studies and are rationalized in terms of s

265 Computational studies applying hybrid density functional

266 In drug discovery and development, computational studies can reduce the costs and risks of

267 imination of Ar(F)-H, where experimental and computational studies establish a concerted but highly a

268 Previous NMR and computational studies have indicated that the population

269 Computational studies indicate that the reaction proceed

270 Computational studies into the reaction mechanism and or

271 Computational studies reveal that catalysis proceeds thr

272 Mechanistic and computational studies support initial reduction to the [

273 The experimental and computational studies that have helped to delineate the

274 ere kinetic, thermodynamic, hydrodynamic and computational studies that show that a conformational se

275 chemical, operando/in situ spectroscopic and computational studies, we investigate the influence of a

276 le effort on this topic has been expended in computational studies.

277 This computational study determined changes in IQ [peak IQ, b

278 We herein disclose a computational study on the homo- and heterodimerization

279 ium labeling experiments and a comprehensive computational study suggest that, despite fast double bo

280 We carry out an experimental and computational study that exploits the natural genetic va

281 A computational study was also conducted, supporting the i

282 To rationalise these results, a DFT computational study was performed which corroborated the

283 In this computational study, we investigated offline decoding an

284 We then present an overview of computational techniques for the study of rechargeable a

285 Using an array of biochemical, cellular, and computational techniques, we first demonstrate that the

286 In line with systems consolidation and computational theories of episodic memory, evidence from

287 Computational theories of hippocampal function suggest t

288 understanding of the relevant biological and computational theories.

289 egies in hippocampal subfields, in line with computational theories.SIGNIFICANCE STATEMENT The flexib

290 We use the computational tool DSGRN (Dynamic Signatures Generated b

291 tion of background mutation rates, yet fewer computational tools exist for specific interrogation of

292 Computational tools for Strand-seq analyses must capture

293 Accordingly, these new computational tools should lead to an improved understan

294 2.7%) but are predicted to be deleterious by computational tools.

295 aining researchers to use and understand new computational tools.

296 Computational toxicology scientists from 25 internationa

297 framework that motivates hyperalignment, its computational underpinnings for joint modeling of a comm

298 re almost unequivocally considered to be the computational units and actuators of behavior, a complet

299 Our study combines experimental and computational work to characterize, explain, and make pr

300 experimental data, we present and validate a computational workflow based on kallisto and bustools, t