ライフサイエンスコーパス: mining

1 ication of new protease inhibitors by genome mining.

2 ression (Human Protein Atlas) and literature mining.

3 ition (NER) is a key task in biomedical text mining.

4 cientific literature by using automated text mining.

5 re a marine resource considered for deep sea mining.

6 has been proposed as a way to supplement REE mining.

7 ltiple disciplines from ecology to text data mining.

8 overable without prior hypotheses using data mining.

9 ch features largely based on biomedical text mining.

10 fective data visualization, integration, and mining.

11 l factors for the climate impact of landfill mining.

12 environmental management plans for deep-sea mining.

13 tool to characterize watersheds affected by mining.

14 unity of using "big data" in biomedical text mining.

15 nd validated 4 (66.7%) of them by literature mining.

16 to structure large textual corpora for data mining.

17 ce pollutants associated with metal and coal mining.

18 (TCGA) RNA-Seq analysis and PubMed abstract mining.

19 5) associations were confirmed by literature mining.

20 d the skills to efficiently perform database mining.

21 geosciences, paleoecology, astrobiology, and mining.

22 Mining 16 years of archival data, we find no evidence fo

23 can be computationally intractable even for mining a dataset containing just a few hundred transacti

24 nt and intuitive web-interface for easy data mining, a comprehensive RESTful API and client libraries

25 We applied frequent itemset mining, a technique traditionally used for market basket

26 issions reduction, environmental protection, mining accident prevention, chemical and process industr

27 integrated approach was taken involving data mining across multiple information resources including d

28 de (principally pyrite)-containing rock from mining activities and from natural environments is expos

29 nt of the changes and temporal linkages with mining activities are difficult to establish given restr

30 l effects of elevated metals and reduced pH, mining activities influence aquatic organisms indirectly

31 hat may experience major impacts from future mining activities.

32 rce of REE to humans in areas unperturbed by mining activities.

33 tagenicity was observed for sites closest to mining activities; however, the indirect-acting mutageni

34 incorporate single-cell tracking and a data-mining algorithm into our approach to obtain RNA element

35 weighted interest measure and an association mining algorithm to find the strength of association bet

36 ble-length k-mers using a distributed string-mining algorithm.

37 to visualize data and to apply advanced data mining analysis methods to explore the data and draw bio

38 Automated text-mining analysis was performed to extract data on P value

39 work and trade opportunities offered by gold mining and agricultural companies but continue to depend

40 the social and environmental impacts of gold mining and agricultural concessions in Myanmar's Hukaung

41 However, gold mining and agricultural concessions reduce tree cover, p

42 ecies from biological samples, enabling data mining and automating lipid identification and external

43 Genome mining and biochemical studies have shown that oomycetes

44 ue to Brazil; to mitigate adverse impacts of mining and conserve tropical forests globally, environme

45 nd GTEx, creating new opportunities for data mining and deeper understanding of gene functions.

46 steady state and applied an integrated data-mining and functional genomics approach to identify a rh

47 the major organs of the mouse, allowing data mining and generating knowledge to elucidate the roles o

48 th century due to emissions from gold/silver mining and Hg production.

49 of analysis and visualization tools for data mining and hypothesis generation, personal workbench spa

50 ally regulate FKBP5 Following in silico data mining and initial target expression validation, miR-511

51 Part of the solution lies in mining and integrating information from various discipli

52 cal issues regarding consent for future data mining and intellectual property.

53 Coupling data mining and laboratory experiments is an efficient method

54 ated disorders by performing literature data mining and manual curation.

55 structed an AAgAtlas database 1.0 using text-mining and manual curation.

56 posal of elemental mercury (Hg(0)) wastes in mining and manufacturing areas has caused serious soil a

57 ew bioavailability data from the Bunker Hill Mining and Metallurgical Complex Superfund Site (BHSS) i

58 ssessment of GHG emissions produced from the mining and milling of uranium in Canada.

59 utational strategy that integrates structure mining and modeling approaches, using which we identify

60 employed network pharmacology including text mining and molecular docking to identify the potential t

61 with results from logistic regression, text-mining and molecular-level measures for comorbidities su

62 Data mining and multivariate statistics were employed to eval

63 nium (U) contamination occurs as a result of mining and ore processing; often in alluvial aquifers th

64 ytoremediation of soils contaminated through mining and oxidation of sulphur-bearing Zn minerals or e

65 Uranium groundwater contamination due to U mining and processing affects numerous sites globally.

66 s into the risks associated with uranium (U) mining and processing, we investigated the biogeochemica

67 oving environmental outcomes associated with mining and refining activities.

68 Assphage, was discovered by metagenomic data mining and reported to be abundant in and closely associ

69 e predicted by serum pharmacochemistry, text mining and similarity match.

70 sicochemical data for particles sampled near mining and smelting operations and a background urban si

71 Mining and summarizing NSD-ncRNA association data can he

72 to quantify dust emissions from the open-pit mining and upgrading of Athabasca bituminous sands (ABS)

73 challenge in bioinformatics relates to data mining and visualization.

74 nual literature curation, computational text mining, and genome analysis.

75 blems arising within signal processing, data mining, and machine learning naturally give rise to hard

76 s from January 2010 to March 2016, reference mining, and pharmaceutical manufacturers.

77 s from January 2010 to March 2016, reference mining, and pharmaceutical manufacturers.

78 action network prediction, coexpression data mining, and phylogenetic profiling all produced incomple

79 and precious metal geology, mineralization, mining, and processing.

80 to protein markers derived from public data mining, and whether mass spectrometry can be utilized to

81 Many text mining applications depend on accurate named entity reco

82 ntegration with FDA drug labels enables text mining applications for drug adverse events and clinical

83 eir subsequent annotation together with text mining applications for linking chemistry with biologica

84 as can be utilised to develop efficient text mining applications on cell types and cell lines.

85 Lastly, we validate this mining approach by heterologous expression of two cluste

86 aB in the kidney cortex, and a targeted data mining approach identified components of the noncanonica

87 ficial neural network-based integrative data mining approach to data from three cohorts of patients w

88 In this study, we present an automated text mining approach using Latent Semantic Indexing (LSI) for

89 We combined the group theory and data mining approach within the Organic Materials Database th

90 Using a computational sequence database mining approach, we identify two class 2 CRISPR-Cas syst

91 Recent advances in metabolomic and genome mining approaches have uncovered a poorly understood met

92 ealizing the predictive capabilities of data mining approaches is a curated, open-access, up-to-date

93 Contrary to prior efforts, the power of data mining approaches lies in the ability to discern synerge

94 y did not decline sharply with distance from mining areas.

95 tainty being acknowledged in biomedical text mining as an attribute of text mined interactions (event

96 ombustion and artisanal and small-scale gold mining (ASGM) in Asian countries determine recent atmosp

97 me coverage and to facilitate effective data mining, assembly was done using different filtering para

98 Mining available gene expression data sets allowed to ob

99 forest based retention time prediction, text-mining based false positive removal/true positive rankin

100 In addition, data mining based on the search for specific sequence motifs

101 n and disease association using a novel text-mining-based machine learning approach.

102 Mining breast cancer TCGA (The Cancer Genome Atlas) data

103 ample, we show how to boost association rule mining by an integrated use of the stochastic search and

104 t may be possible to automate LCI using data mining by establishing a reproducible approach for ident

105 also provide a basis for more extensive data mining by providing a comprehensive list of miRNAs capab

106 rate was "agriculture" (by occupation) and "mining" (by industry).

107 trative and managerial" (by occupation) and "mining" (by industry).

108 ncode a variety of sortases, natural sortase mining can be a viable complementary approach akin to en

109 or data analysis is that the process of data mining can become uncoupled from the scientific process

110 that a state-of-the-art physics-guided data mining can provide an efficient pathway for knowledge di

111 NGS of BAC pools as a potential approach for mining candidates underlying QTLs of this species; iii)

112 and improve its usefulness as a resource for mining clinically actionable drug targets.

113 ssessing nodule abundance is of interest for mining companies and to monitor potential environmental

114 on and degradation compared with logging and mining concessions, and the unprotected landscape.

115 vernance regimes when matched to logging and mining concessions.

116 Land-cover changes driven by mining, dam and road construction, agriculture and cattl

117 By mining data for >1,500 disease-causing mutants, we found

118 By mining data from hundreds of experimental phase diagrams

119 between proteins and diseases, based on text mining data processed from scientific literature.

120 t) exposed within the Fairbanks and Klondike mining districts of Alaska, USA, and the Yukon Territory

121 In Brazil's Amazon, mining drives deforestation far beyond operational lease

122 By industry; mining, electricity and gas, fisheries, and agriculture

123 A phenotyping algorithm mining electronic medical records was developed and vali

124 omputational-experimental approach with text mining-enhanced quantitative proteomics.

125 Building statistical models by mining existing clinical trial data can enable prospecti

126 ate) traits at the gene- or pathway-level by mining existing single GWAS or meta-analyzed GWAS data.

127 ic compounds (VOCs) for each of four surface mining facilities, determined with a top-down approach u

128 l filtering of GWAS results followed by text-mining filtering revealed relationships between ADGRV1 a

129 tistical filtering of GWAS results, and text-mining filtering using Gene Relationships Across Implica

130 thy survivors, who experienced the same coal mining flood disaster.

131 Twitter makes it a promising target for data mining for ADE identification and intervention.

132 RTS allows for specific and efficient genome mining for antibiotics with interesting and novel target

133 s process can be dramatically accelerated by mining for new ligands in a typical pharmaceutical compo

134 will further facilitate computational genome mining for the discovery of novel bioactive molecules.

135 In this study, we present a novel literature-mining framework for enhancing the predictions of DDIs a

136 Based on data mining from AERS-DM, PPI use appears to be associated wi

137 linical terms is an important aspect of text mining from electronic health records, which are increas

138 overexpressing mice in conjunction with data mining from the Cancer Genome Atlas showed that the neut

139 direct sequencing, KIR genotyping, and data mining from the Great Ape Genome Project, we characteriz

140 les from the itemset space, and perform rule mining from the reduced transaction dataset generated by

141 Mining fungal and plant genomes along with evolutionary

142 Mining generated reads it was possible to identify diffe

143 ed pseudopods that we call "alpha-motility." Mining genomic data reveals a clear trend: only organism

144 Oil sands mining has been linked to increasing atmospheric deposit

145 Landfill mining has been proposed as an innovative strategy to mi

146 Genome mining has enabled the identification of Mbn operons in

147 Text mining identified 4,572,043 P values in 1,608,736 MEDLIN

148 l linkage disequilibrium analysis and allele mining identified possible candidate genes which may mod

149 identified by using a combination of genome mining, imaging, and expression studies in the natural p

150 hantom midge (Chaoborus) collected from five mining-impacted lakes by determining the distribution of

151 three-dimensional assessment of mountaintop mining impacts is necessary to predict both the severity

152 and topographic disturbance associated with mining in an 11500 km(2) region of southern West Virgini

153 ering techniques, very few were designed for mining in growth phenotype data.

154 intop mining is the most common form of coal mining in the Central Appalachian ecoregion.

155 and confirmed consanguinity followed by data mining in the exomes of 1,348 PD-affected individuals id

156 icking through GEPIA greatly facilitate data mining in wide research areas, scientific discussion and

157 e validated a few top predicted DTIs through mining independent drug databases and literatures.

158 Here we quantify mining-induced deforestation and investigate the aspects

159 Mining-induced deforestation is not unique to Brazil; to

160 The rapid development of mining industries drives income-based GHG emissions of r

161 Pathways leading to such impacts include mining infrastructure establishment, urban expansion to

162 Data mining is a suitable tool for this purpose, especially g

163 Text mining is increasingly used to manage the accelerating p

164 Mountaintop mining is the most common form of coal mining in the Cen

165 being disrupted by the construction of dams, mining, land-cover changes, and global climate change.

166 Mining large datasets using machine learning approaches

167 e that an algorithm originally used for text mining, latent Dirichlet allocation, can be adapted to h

168 reased Amazon forest loss up to 70 km beyond mining lease boundaries, causing 11,670 km(2) of defores

169 imes more deforestation than occurred within mining leases alone.

170 iosis, and an exciting coalescence of genome mining, lipid profiling, and tracer studies collectively

171 xtensive and intensive agriculture, resource mining, livestock grazing and urban settlement.

172 We sought to determine whether data mining longitudinal physiologic data in a nonhuman prima

173 stems can be accurately predicted using data-mining, machine-learning techniques.

174 om fugitive emissions of dusts from open-pit mining, may have long-term ecological ramifications.

175 In recent years, genome mining methodologies have been widely adopted to identif

176 Cancer taxonomy and developed automatic text mining methodology and a tool (CHAT) capable of retrievi

177 Vitro in biomedical literature by using text mining methods and present our results.

178 iomedical networks and models, aided by text mining methods that provide evidence from literature.

179 ARTS integrates target directed genome mining methods, antibiotic gene cluster predictions and

180 derlying structure in the genomic data, data mining might identify this and thus improve downstream a

181 This results in Canadian uranium mining-milling contributing only 1.1 g CO2e/kWh to total

182 We examined interactions between the leaf-mining moth Cameraria ohridella, the bacterial causal ag

183 Mountaintop removal coal mining (MTM) is a form of surface mining where ridges an

184 ge will contribute to sustaining supply, but mining must continue and grow for the foreseeable future

185 nt sensors for detecting and monitoring post-mining natural attenuation of Se oxyanions at ISR sites.

186 Metal recycling based on urban mining needs to be established to tackle the increasing

187 primarily over an area of intensive surface mining, NO2 tropospheric vertical column densities (VCDs

188 t species, leading to an enriched source for mining novel enzymes for biotechnology applications.

189 Systematic mining of 80+ years of the phytochemistry and biology li

190 and constitutes a promising resource for the mining of agriculturally important genes.

191 y NMR combined with virtual screening and re-mining of biochemical high-throughput screening (HTS) hi

192 tion of candidate target genes by systematic mining of comparative, epigenomic and regulatory annotat

193 rticipatory surveillance systems, as well as mining of digital traces such as social media, Internet

194 ese fungi through the release and subsequent mining of genome sequences.

195 We show how archiving and mining of intraoperative hemodynamic data in orthotopic

196 Mining of leaf- and trichome-specific transcriptomes rev

197 It also demonstrates that a deep mining of natural functionalities of living systems is a

198 or research effort linked to possible future mining of polymetallic nodules.

199 y combining new field measurements with data mining of previously unavailable well attributes and num

200 ncludes 2767 fusion genes obtained from text mining of PubMed abstracts.

201 greater resilience is achievable through the mining of resistance alleles from compatible wild sunflo

202 Data mining of RNA-Seq experiments with mouse models of intes

203 rediction errors of GRNs hinder optimal data mining of RNA-Seq transcriptome profiles.

204 rtunities for possible expansion and further mining of the data from this ingenious design.

205 To facilitate further mining of the disease methylome, three new web tools wer

206 From a concept mining of the existing literature, a set of hypothetical

207 Mining of the golden larch root transcriptome revealed a

208 nd, where the dominant contributions are the mining of the rare earth oxide ceria, the manufacturing

209 signals across genomes, (iii) automated text-mining of the scientific literature and (iv) computation

210 Very recently, a novel approach for data mining of the vast compilations of tumour NGS data succe

211 We illustrate how systematic mining of this phosphodiesterase structure and ligand in

212 Further mining of this proteomic resource may enable engineering

213 Mining of transplant immunomes for strong myeloma surfac

214 Through mining of V ores (130 x 10(9) g V/y) and extraction and

215 Mining oncogenomic databases revealed that loss of the P

216 deforestation and investigate the aspects of mining operations, which most likely contribute.

217 e county level, reflecting prospective urban mining opportunities.

218 strength aqueous media that often occur in U mining or contaminated sites, which makes U(VI) very mob

219 n sludge were similar to those in profitable mining ores, with total flux values of up to 6.8 USD per

220 nd clinical studies, bioinformatic knowledge mining, pathway and network analyses, short-duration in

221 ant for potentially optimizing their role in mining phosphorus (P) in agricultural ecosystems.

222 ure according to an automated text and image-mining pipeline on a daily basis.

223 We used a sophisticated text-mining pipeline to extract 1.15 million unique whole rea

224 s study demonstrates a holistic approach for mining plant collections to accelerate crop improvement.

225 There is growing interest in mining polymetallic nodules in the abyssal Clarion-Clipp

226 Mining poses significant and potentially underestimated

227 d sites were used to demonstrate that a data mining prediction model using the classification and reg

228 a more economical and environmentally benign mining process, as well as the design of more effective

229 with extracting palladium using present-day mining processes.

230 Many mining projects targeting rare earth elements (REE) are

231 ng mass spectrometry, microscopy, and genome mining, provides an effective way for mappings of proteo

232 Through mining publicly accessible PCa gene expression datasets,

233 nsformations downstream of a historical gold mining region.

234 During eddy-induced elevated flow periods mining-related plumes, potentially supplemented by natur

235 d that the employed method is sufficient for mining relevant molecular features from the data.

236 text is an important task in biomedical text mining research, facilitating for instance the identific

237 as well as the design of more effective post-mining restoration strategies and human health-risk asse

238 In particular, the mining sector reduced its TF through outsourcing process

239 t here our recently developed web-based text mining services for biomedical concept recognition and n

240 stration Adverse Event Reporting System Data Mining Set (AERS-DM).

241 expression quantitative trait loci database mining showed association between the protective minor a

242 We find mining significantly increased Amazon forest loss up to

243 elter operation in Hayden, AZ, (ii) a legacy mining site with extensive mine tailings in Iron King, A

244 as found applications in many fields such as mining, solid state chemistry, biochemistry and medical

245 We used a data-mining strategy to identify highly expressed genes in Ch

246 at CSD-CrossMiner closes an important gap in mining structural data and will allow users to extract m

247 Data-mining studies strongly suggest that 12-HETER1 expressio

248 bspace is a powerful strategy in general for mining such big data.

249 By using advanced data mining, supervised machine learning, and network analysi

250 Here we develop MiSL (Mining Synthetic Lethals), an algorithm that mines pan-c

251 s in a systematic biological Knowledge-based mining system for Genome-wide Genetic studies (KGG).

252 e biomedical literature using the eGIFT text-mining system.

253 We demonstrated that DTM, a text mining technique, can be a powerful computational approa

254 verall, these findings demonstrate that data mining techniques (e.g., machine learning algorithms) ef

255 ta, application of machine learning and data mining techniques has become more attractive given the r

256 The system employed association mining techniques to build a k-profile representing a us

257 With UMLS and association mining techniques, BiomedSearch can effectively utilize

258 nt genome sequencing, they will allow genome mining technologies to be applied to plant natural produ

259 Mining the data for underlying genetic or phenotypic str

260 the data are provided by the submitter, and mining the data in the SRA is complicated by both the am

261 Mining the data platform with largest connected componen

262 s a comprehensive and user friendly tool for mining the druggable genome for precision medicine hypot

263 The second DEG is constructed by mining the history of Twitter users.

264 This study was initiated by mining the Ixodes ricinus salivary gland transcriptome f

265 in the reference case (i.e., alternative to mining the landfill), the background energy system, the

266 It starts by mining the literature to quickly extract a set of genes

267 Mining the Organic Materials Database, we present band s

268 tion under physiological conditions in vitro Mining the simulation data linked formation of this disu

269 but reduced in the receptor mutant, dorn1-3 Mining the transcriptome data revealed that ATP induces

270 Current approaches to mining these data largely rely on binary classifications

271 Mining this resource, we find that most chromosomal aber

272 The difficulty in organizing and mining this unprecedented amount of information has stim

273 Here we propose a machine learning method to mining through publicly available literature on RNA inte

274 hese results demonstrate the ability of text mining to contribute to the ongoing debate about the rep

275 This opens up for the use of data mining to discover unknown drug-drug interactions in car

276 s datasets of human asthma, followed by text mining to evaluate functional marker relevance of discov

277 In this study, we use text mining to extract information from the descriptions of o

278 ditions for the net contribution of landfill mining to global warming using a novel, set-based modeli

279 overdue for public release by applying text mining to identify dataset references in published artic

280 cribing our first steps into the use of text mining to identify protein-related entities, the large-s

281 Here we use text mining to study 15,311 research papers in which mice wer

282 yzer of Bioresource Citation (ABC) is a data mining tool extracting strain related publications, pate

283 gy Consortium Integrative Database is a data-mining tool that includes 379 neuropathology data sets f

284 ss this issue we developed OncoScore, a text-mining tool that ranks genes according to their associat

285 With the assistance of the PubTator text-mining tool, we tagged more than 10 000 articles to asse

286 Existing mining tools are excellent at detecting BGCs or resistan

287 lity databases require manual curation, text mining tools can facilitate the curation process, increa

288 scripts requires the development of specific mining tools to facilitate the visual exploration of evi

289 arch by providing genome annotation and data mining tools.

290 val, preprocessing, topic modeling, and data mining using Latent Dirichlet Allocation (LDA) topic out

291 Through data mining using our structural and biochemical information,

292 nother series of individuals with DEE and by mining various sequencing datasets.

293 on and analysis tools for comprehensive data mining via intuitive graphical interfaces and APIs.

294 A new data-mining warehouse, HymenopteraMine, based on the InterMin

295 ore than 27,000 m3 of contaminated soils and mining waste were removed from 820 residences and ore pr

296 a lead finding approach based on literature-mining, we discovered that anabaenopeptins, cyclic pepti

297 By genome-enabled receptor mining, we identified 566 putative planarian GPCRs and c

298 moval coal mining (MTM) is a form of surface mining where ridges and mountain tops are removed with e

299 recognition is critical for biomedical text mining, where it is not unusual to find entities labeled

300 rging computational approaches based on text mining which offer a great opportunity to organize and r