ライフサイエンスコーパス: binning

1 very rate compared with approaches based on "binning".

2 the sample fragments, a procedure known as 'binning'.

3 data preprocessing (i.e., centroiding and/or binning).

4 ias the results against weighted statistical binning.

5 ument does not apply to weighted statistical binning.

6 metagenomic data using differential coverage binning.

7 Our method also has a high accuracy in read binning.

8 formance to manual peak deconvolution and to binning.

9 assembly, and multidimensional phylogenetic binning.

10 on regardless of the downstream smoothing or binning.

11 processing steps, such as peak alignment and binning.

12 cluding reference deconvolution and spectral binning.

13 described here involve torsion matching and binning.

14 es an alternative to the current practice of binning.

15 play to carry out massively parallel epitope binning.

16 a 3D KSHV genomic structural model with 2 kb binning.

17 both Y haplotypes were reconstructed by Trio binning.

18 and isotopes than existing methods based on binning.

19 ared to commonly used methods based on fixed binning.

20 rforms existing methods on normalization and binning.

21 ts using MLE over the more common methods of binning.

22 T vector for improved results in metagenomic binning.

23 age, enabling quick and accurate metagenomic binning.

24 thm that greatly advances over standard trio binning.

25 specifically dedicated to metagenomic viral binning.

26 aired with a camera with built-in electronic binning.

27 methods have been devised for reference-free binning.

28 s favorably with other tools on viral contig binning.

29 w statistical tools, and supports metagenome binning.

30 pproach, normalized cut, for improved contig binning.

31 g in markedly improved performance of contig binning.

32 OTU clustering is also referred to as binning.

33 ing methods to enable more accurate sequence binning.

34 as user-specified PDFs without the need for binning.

35 For example, binning 100k contigs took about 4 h on 10 Intel CPU Core

36 Binning 16S rRNA sequences into operational taxonomic un

37 offset detection concept by computationally binning 2D optical data associated with digital offsets

38 ors in competitive binding assays by epitope binning a panel of antibodies.

39 ecovering more bacterial genomes compared to binning a single sample as well as comparing the microbi

40 proves the state of the art in terms of both binning accuracies and the scope of applicability.

41 proposed approach achieves a higher species binning accuracy and is particularly powerful when seque

42 dies, we demonstrate that MetaBMF has a high binning accuracy.

43 embraces customized knowledge to facilitate binning accuracy.

44 Here, we introduce BASALT (Binning Across a Series of Assemblies Toolkit) for binni

45 program, and consistent peak extraction plus binning across a study set.

46 Binning aims to recover microbial genomes from metagenom

47 Metagenomic binning aims to retrieve microbial genomes directly from

48 Our barcode-based metagenome binning algorithm substantially improves the state of th

49 ture enables the development of a graph trio binning algorithm that greatly advances over standard tr

50 is sequencer and used a variant of the phred binning algorithm to combine them into a single empirica

51 combining a deep-learning based metagenomics binning algorithm with paired metagenome and metavirome

52 duce a new binning method, named JBA ("pJRES Binning Algorithm"), which aims to extend the applicabil

53 Here we present an expanded binning algorithm, MaxBin 2.0, which recovers genomes fr

54 Many binning algorithms have been developed, but their perfor

55 of selected regions of interest and by pixel binning along the spectral direction.

56 platform to perform high-throughput epitope binning analysis on a large number of monoclonal antibod

57 Differential coverage binning analysis revealed significant ARG enrichment in

58 hrough single-contig refinement by iterative-binning and -assembly of reads.

59 combination of morphology-based phylogenetic binning and a multiresponse permutation procedure to tes

60 ring these tools, linking them with advanced binning and annotation tools, and maintaining provenance

61 y on aggregating information through spatial binning and cannot combine information from multiple cel

62 sing state-of-the-art metagenomic population binning and catalyzed reporter deposition fluorescence i

63 The classical binning and counting approach to plotting reliability di

64 produces better results than single-coverage binning and identifies contaminant contigs and chimeric

65 ow the use of statistical constructs such as binning and linear regression to quantify relationships

66 Epitope binning and mapping experiments with LptD-loop-deletion

67 e antigen, and facilitating detailed epitope binning and mapping studies.

68 Metagenomic binning and metaproteomic analysis of this deep subsurfa

69 ction of recombinant chromosomes useful as a binning and ordering resource for YAC-based physical map

70 Metagenomic binning and phylogenetic analysis revealed that two anam

71 n metrics for assessing metagenome assembly, binning and profiling results, and provide step-by-step

72 , such as MySQL multi-column indexing, MySQL binning and R-Tree indexing.

73 ing with an adjustable field-of-view, ad-hoc binning and re-binning of data based on the requirements

74 g Across a Series of Assemblies Toolkit) for binning and refinement of short- and long-read sequencin

75 nfirmed the accuracy of the on-yeast epitope binning and structures of both individual nanobodies, an

76 We demonstrate the measurement, binning and transfer of 119 PhCCs in a single session, p

77 ds were classified taxonomically (by genomic binning) and functionally (using Kyoto Encyclopedia of G

78 thods: (1) background subtraction, (2) pixel binning, and (3) CMOS color channel selection.

79 pipeline incorporating iterative subtractive binning, and apply it to a time series of 100 metagenomi

80 via metagenomic, metatranscriptomic, genomic binning, and geochemical analyses from Axial Seamount, a

81 thod constitutes a powerful tool for epitope binning, and in our case allowed development of a sandwi

82 and viral genomes using iterative assembly, binning, and read mapping.

83 ve used a combination of metagenomic, genome binning, and stimulus-induced metatranscriptomic approac

84 free parameters nor require arbitrary trait binning, and weigh species by their abundances rather th

85 opulation in lupus-prone NZBxW mice with our binning approach "pattern recognition of immune cells (P

86 We previously developed MaxBin, an automated binning approach for high-throughput recovery of microbi

87 We present a novel binning approach for large scale joint variant calling a

88 As an alternative binning approach, Hi-C-based binning employs metagenomic

89 Here, using a trio-binning approach, we present a high-quality, diploid ref

90 only permanent pasture lands using a climate binning approach.

91 eal datasets in comparison with state-of-art binning approaches such as CONCOCT, GroopM, MaxBin and M

92 Adaptive smoothing and binning approaches were found to compensate for low posi

93 er textural features by applying 5 different binning approaches.

94 ethods for assembly, taxonomic profiling and binning are key to interpreting metagenome data, but a l

95 ut any distribution assumption, corrects for binning artifacts, and provides improved statistical pow

96 ing for assembly and genome recovery through binning, as was assembly quality for the latter.

97 community structure and function, automated binning, as well as genomic signature-based visualizatio

98 To investigate their taxonomic structure, binning assembled contigs into discrete clusters is crit

99 reconstructed using metagenomic assembly and binning) associated with the marine dinoflagellates Gamb

100 and AFITBin, a novel method for metagenomic binning based on AFIT and a matrix factorization method.

101 ndependent approach called MBBC (Metagenomic Binning Based on Clustering) to cluster environmental sh

102 A number of binning-based methods have been proposed to reduce the d

103 ads (Supernova), and is comparable to a trio-binning-based third generation long-read-based assembly

104 e have not applied a crude approach based on binning but a sophisticated machine learning method capa

105 g using long (HiFi) reads combined with Hi-C binning can address this challenge even for complex micr

106 Thus, naive binning can improve phylogenomic analysis in the presenc

107 Conversely, alignment and binning can introduce artefacts and limit immediate biol

108 non-overlapping groups; unfortunately, such binning can miss remote relationships.

109 Unlike classical clustering problem, contig binning can utilize known relationships among some of th

110 Binning cells according to total ERK expression revealed

111 By binning cells into groups with finite genetic bottleneck

112 proaches have inherent limitations including binning clearly continuous distributions, poor trait-gro

113 or determining features using variant length binning, clustering and density estimation; (ii) a progr

114 Here we present a method, based on binning co-abundant genes across a series of metagenomic

115 re used to establish 3 predictive models per binning configuration: one model based on a combination

116 However, in the related field of metagenomic binning, contigs are routinely clustered using informati

117 y investigating the application of different binning criteria.

118 Binning cutoffs for each sample type are chosen automati

119 We compiled epitope-binning data for seventeen hmAbs and structures of nine

120 Pairwise epitope binning data from the ProteOn 36-ligand array format and

121 The binning data were further integrated with affinity infor

122 an alternative binning approach, Hi-C-based binning employs metagenomic Hi-C technique to measure th

123 Binning environmental shotgun reads is one of the most f

124 pitopes as determined by ELISA based epitope binning experiments and mass photometry.

125 Epitope binning experiments identified five major antigenic site

126 of analysis, enabling differential coverage binning for recovery of genomes and estimation of microb

127 e the utility of miBF in two use cases: read-binning for targeted assembly, and taxonomic read assign

128 ensitivity and precision of VirBin in contig binning for viral haplotype reconstruction.

129 Time-series binning generates 21,536 high-quality metagenome-assembl

130 Genome binning has been essential for characterization of bacte

131 Metagenomic binning has revolutionized the study of uncultured micro

132 In metagenomic contig binning, Hetero-RP automatically weighs abundance and co

133 Complemented with a reference-free genome binning heuristics based on dimension reduction, the pro

134 Binning, however, does have several advantages.

135 Genomic binning identified key populations of SUP05, Aquificales

136 d to (i) fundamental advances in metagenomic binning, (ii) development and refinement of technology f

137 Statistical binning improves the accuracy of MP-EST, a popular coale

138 comparable to the state-of-the-art Bayesian Binning in Quantiles (BBQ) method when the SVM models ar

139 ment and linkage information further improve binning in the majority of cases.

140 In addition, a binning-independent model based on ex vivo and patient i

141 STRONG performs coassembly, and binning into metagenome assembled genomes (MAGs), and st

142 correspondence between torsion matching and binning is 99% (per residue).

143 Binning is a classification technique based on distribut

144 Further plasmid analyses reveal that MetaCC binning is able to capture multi-copy plasmids.

145 Metagenomic binning is an essential technique for genome-resolved ch

146 Metagenomic contig binning is an important computational problem in metagen

147 e improvement over traditional nonparametric binning is twofold and associated with enhanced resoluti

148 each allele in the sample (allele calling or binning) is therefore an absolute requirement.

149 conductance measurements and demonstrate how binning measurements according to smear can significantl

150 demonstrated the use of DNA methylation for binning metagenomic contigs, associating mobile genetic

151 We have developed a novel method for binning metagenomic reads based on clustering.

152 Here, we introduce COMEBin, a binning method based on contrastive multi-view represent

153 eloped a dynamic programming algorithm based binning method for ARISA data analysis which minimizes t

154 In addition, the binning method lends itself to a natural graphical repre

155 IGD uses a novel linear binning method that allows us to scale analysis to billi

156 We present a binning method that incorporates bacterial DNA methylati

157 we propose a simple yet powerful metagenomic binning method, MetaBMF.

158 Here, we introduce a new binning method, named JBA ("pJRES Binning Algorithm"), w

159 We developed a novel contig binning method, Semi-supervised Spectral Normalized Cut

160 ubspecies from contigs generated by the trio binning method.

161 ion to compare the ability of two normalised binning methods (equal logarithmic and log(2) bins) and

162 he existing binning results of both types of binning methods and achieves better performance in const

163 While dozens of binning methods are available, there is still room for i

164 mplex metagenomic communities, the available binning methods are far from satisfactory, which usually

165 iated with non-model hosts, robust automated binning methods are required.

166 Computational binning methods are used to mitigate fragmentation by pa

167 that ViralCC outperforms existing Hi-C-based binning methods as well as state-of-the-art tools specif

168 The error induced by binning methods can be of similar magnitudes as the vari

169 Traditional shotgun-based binning methods depend on the contigs' composition and a

170 However, the current state-of-the-art contig binning methods do not make full use of the additional b

171 However, existing binning methods face challenges in practical application

172 s not output whole genomes, so computational binning methods have been developed to cluster sequences

173 Existing binning methods have been principally tuned for bacteria

174 o overcome the shortcomings of both types of binning methods on a single sample.

175 t CoCoNet substantially outperforms existing binning methods on viral datasets.

176 COMEBin outperforms other binning methods remarkably when integrated into metageno

177 However, current binning methods struggle with identifying unknown specie

178 l datasets in comparison to state-of-the-art binning methods such as MetaBAT 2, MaxBin 2.0, CONCOT, M

179 Furthermore, existing binning methods usually require a priori decisions regar

180 us research, for both conditions logarithmic binning methods were consistent with Levy flights and ra

181 ssembler, SPAdes, in combination with contig binning methods, allowed the reconstruction of genomes f

182 Existing binning methods, based on nucleotide composition or alig

183 te that COMEBin outperforms state-of-the-art binning methods, particularly in recovering near-complet

184 erived from the Hi-C-based and shotgun-based binning methods, which considerably increases the purity

185 methods always performed better than common binning methods, which demonstrated consistent bias depe

186 d (PhyloPythia, oligonucleotide frequencies) binning methods.

187 methods is markedly reduced when compared to binning methods.

188 shown to outperform the existing Hi-C-based binning methods.

189 times more novel taxa than state-of-the-art binning methods.

190 ome, MGIIa_P, was recovered using metagenome binning methods.

191 ted using median-anchored generalized linear binning (mGLB).

192 n the switching more accurately than typical binning model.

193 dily separated morphologically, the combined binning/multiresponse permutation procedure showed that

194 We show that all forms of binning-naive, statistical, and weighted statistical-dis

195 netic anchors can improve assembly-dependent binning needed for more accurate taxonomic and functiona

196 This binning of cosmids facilitated the subsequent fingerprin

197 ustable field-of-view, ad-hoc binning and re-binning of data based on the requirements of the experim

198 llection times, resulting in strong temporal binning of dynamic processes.

199 s of the receptor-ligand complex facilitates binning of ER modulators into distinct groups based on s

200 it can potentially facilitate the downstream binning of genomic fragments into uniform clusters refle

201 at metagenomic-SIP improves the assembly and binning of isotopically labeled genomes relative to a co

202 o integrate different types of tools for the binning of metagenomic contigs.

203 ply this feature space to the alignment-free binning of metagenomic data.

204 posure levels using two techniques: quantile binning of the exposure and a semiparametric model for t

205 detail by arbitrarily controlling the pixel-binning of the masks.

206 ific functions and improves the assembly and binning of these targeted genomes.

207 Binning (PHAMB), an approach that allows the binning of thousands of viral genomes directly from bulk

208 is of organism-specific metabolic networks, 'binning' of metagenomes and other biological problems ar

209 Pooling ('binning') of related haplotypes did not increase differe

210 Equal-width binning on the cut variable was performed to handle clas

211 Here we compare single- and multi-coverage binning on the same set of samples, and demonstrate that

212 previously described methods of metagenomic binning or metagenomic assembly and represents a fundame

213 PCA, in combination with data binning or other reduction algorithms, has been widely u

214 We term this approach "binning" or "tiling" depending on the type of m/z window

215 low-coverage sequencing (<0.1x), performing 'binning' or 'windowing' on mapped short sequences ('read

216 e trains on a millisecond time scale without binning over time or space.

217 PCR-ME genetic profiles were analyzed using binning palettes generated from two sets of allelic ladd

218 Using these binning palettes, no allele calling errors were detected

219 usually require a priori decisions regarding binning parameters such as a distance level for defining

220 th PIME machine-learning de-noising and taxa binning/parsing of prevalent ASVs at the single nucleoti

221 and Index), [Formula: see text] improves the binning performance in 28 out of 30 testing experiments

222 atasets, we develop Phages from Metagenomics Binning (PHAMB), an approach that allows the binning of

223 Therefore, it is imperative to develop a binning pipeline to overcome the shortcomings of both ty

224 We develop HiFine, a novel binning pipeline to refine the binning results of metage

225 We therefore developed an automated binning pipeline, termed 'Autometa', to address these is

226 includes the spurious contact detection into binning pipelines for the first time.

227 Contig binning plays a crucial role in metagenomic data analysi

228 ressing two challenging problems: metagenome binning problem and identification of horizontally trans

229 VEBA implements a novel iterative binning procedure and hybrid sample-specific/multi-sampl

230 However, recent work has shown that binning procedures return biased estimates of lambda com

231 mbda was estimated using MLE compared to the binning procedures.

232 le approximations based on the nature of the binning process and the transformation rules for probabi

233 samples, and demonstrate that multi-coverage binning produces better results than single-coverage bin

234 Assembly and genome binning programs performed well for species represented

235 Taxonomic profiling and binning programs were proficient at high taxonomic ranks

236 does not follow the recommended statistical binning protocol and has data of unknown origin that bia

237 Current encoding mechanisms (e.g., binning, rate-based encoding, and time-based encoding) h

238 However, downstream analysis relies on binning reads into microbial groups by either considerin

239 Metagenomic binning reconstructed 29 high-quality metagenome-assembl

240 egy as opposed to default absolute intensity binning reduces correlation between gray-level co-occurr

241 Rand index cluster analyses predicted best binning results between 97% and 94% sequence similarity

242 t HiFine significantly improves the existing binning results of both types of binning methods and ach

243 Fine, a novel binning pipeline to refine the binning results of metagenomic contigs by integrating bo

244 The epitope binning results were analyzed in unique ways using vario

245 ervariable regions of 16S rRNA were used and binning results were compared.

246 The combination of epitope binning results with binding kinetics and sequence analy

247 single metagenomic samples to obtain better binning results.

248 Formula: see text] was applied to adjust the binning results.

249 sually >/=10 samples, to get highly accurate binning results.

250 All mAbs are neutralizing, and epitope binning reveals four different epitopes targeted by the

251 sis to 93.9% with smear characterization and binning (SCRIB).

252 nstruction, lesion delineation, and radiomic binning settings.

253 study, a new statistical method, probability binning signature quadratic form (PB-sQF), was developed

254 require arbitrary parameter choices, such as binning size, while more advanced model-based methods re

255 fers a library of operations (normalization, binning, smoothing) to process raw data into visualizabl

256 ere easy to interpret with the aid of allele binning software.

257 Semi-supervised Spectral Normalized Cut for Binning (SolidBin), based on semi-supervised spectral cl

258 n sequencing data together with assembly and binning strategies to reconstruct metagenome-assembled g

259 The use of a relative intensity binning strategy as opposed to default absolute intensit

260 ginating from different modalities through a binning strategy that relies on a common genomic coordin

261 ding domain and employed an on-yeast epitope binning strategy to rapidly map the specificities of the

262 nomic assembly followed by a reference-based binning strategy to screen over 6500 gut metagenomes spa

263 Both a sliding window and a binning strategy were introduced to uncover areas of hig

264 sembly for Synthetic long reads using a Trio-binning strategy, or HAST, which uses parental informati

265 ificial chromosome (YAC)-based isolation and binning strategy.

266 Epitope binning studies showed that MPV364 targets antigenic sit

267 Epitope binning studies showed that the majority of neutralizing

268 single nanocrystals, ranging from intensity "binning" techniques to more sophisticated methods based

269 higher sensitivity and specificity for read-binning than sequence alignment-based methods, also exec

270 ale-invariance was recovered using 'adaptive binning', that is identifying clusters at temporal resol

271 ormation is not significantly compromised by binning the continuous torsional information into a limi

272 for estimating lambda most of which involve binning the data, counting the abundance within bins, an

273 After binning the metagenome data, we assembled and annotated

274 us to study the different timescales through binning the output of the model.

275 Here, we present Opal for metagenomic binning, the task of identifying the origin species of D

276 e level searching rather than hard cutoff or binning, the use of non-parametric methods to fine-tune

277 Here we use trio binning to create a contiguous haplotype DNA sequence of

278 Mirarab et al. introduced statistical binning to improve the signal in phylogenetic methods us

279 SlideCNA uses expression-aware spatial binning to overcome sparsity limitations while maintaini

280 First, FogBank uses histogram binning to quantize pixel intensities which minimizes th

281 genome bin (SGB), which employs co-abundance binning, to investigate subspecies-level microbiome dyna

282 this work, we presented VirBin, a new contig binning tool for distinguishing contigs from different v

283 We developed a contig binning tool, VirBin, which clusters contigs into differ

284 With many binning tools available, we do not try to bin contigs fr

285 The benchmark results with other contig binning tools demonstrated the superior sensitivity and

286 s among bins based on the output of existing binning tools for a single metagenomic sample.

287 text] can be applied to any existing contig-binning tools for single metagenomic samples to obtain b

288 ystems but hampered by the low efficiency of binning tools in adequately recovering metagenome-assemb

289 performance of vRhyme compared to available binning tools in constructing more complete and uncontam

290 nce of [Formula: see text], five widely used binning tools with different strategies of sequence comp

291 of 30 testing experiments (6 datasets with 5 binning tools).

292 achieved notably higher genome accuracy than binning tools.

293 ntegrating both Hi-C-based and shotgun-based binning tools.

294 Linear regression with weighted-age binning was performed to assess for differences between

295 the spectral coding and performing 4-9 frame binning, we achieved a 2-3 fold experimental resolution

296 In addition to genome binning, we show that our method links plasmids and othe

297 olution is only achieved after a process of 'binning' where contigs predicted to originate from the s

298 e assembly of labeled genomes and subsequent binning, where high community G + C generally reduced th

299 For binning, which is synonymous with the clustering of OTUs

300 rgue against the use of weighted statistical binning within a species tree estimation pipeline.