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1 ing relative biomass abundances and increase false absences.

2 al data and the developed method, we compute false alarm and miss error probabilities in wild-type ce

3 two types of incorrect cell decisions called false alarm and miss.

4 In biological terms, a higher false alarm metric in this abnormal TNF signaling system

5 dularity levels were associated with a lower false alarm rate.

6 We propose the "false alarm" hypothesis, in which AGEs that are present

7 e emergency warnings of volcanic activity as false alarms.

8 In the RF group, 2 patients developed a false aneurysm, and 1 patient needed surgical repair.

9 at false-CRISPRs could be used to reduce the false annotation of CRISPRs, therefore showing them to b

10 At higher frequencies (>/=15%), the false answers influenced the MD to a greater extent, whe

11 ication, in which signals are either true or false, art and fiction consist of signals without determ

12 These false assignments will eventually lead to wrong conclusi

13 etle Darwinylus marcosi, family Oedemeridae (false blister beetles), that had an earlier gymnosperm (

14 H model uses the language of science to lend false credibility to a problematic sociocultural discour

15 We called these elements false-CRISPRs and further classified them into groups, i

16 We demonstrated that false-CRISPRs could be used to reduce the false annotati

17 e low-resolution basket catheter is prone to false detections and may incorrectly identify rotors tha

18 l abilities, so contrasting the two may be a false dichotomy.

19 characteristic (ROC) curve (AUC), number of false discoveries and statistical power.

20 multiple testing procedures for controlling false discoveries in genomic studies.

21 An underestimated FDR can lead to unexpected false discoveries in the follow-up validation experiment

22 mplicated data processing that contribute to false discoveries.

23 coding regions, but is highly susceptible to false discovery and misinterpretation.

24 ntly associated with dilated cardiomyopathy (false discovery corrected P</=0.05), with 3 of them reac

25 mbly-based approach would have great risk of false discovery of novel SNVs.

26 171 bacterial taxa that were significantly (false discovery rate < 0.05) more or less abundant, resp

27 ased expression of 276 transcripts (FC > 2x, false discovery rate < 0.05), including IFNG, TNF, CSF2,

28 lly expressed in HDM APT (fold change >2 and false discovery rate < 0.05), with increased expression

29 n containing 3 (NRLP3) inflammasome members (false discovery rate < 0.05).

30 inflamed colon and TNF-alpha-treated cells (false discovery rate < 0.05).

31 ferential DNA methylation of UNC5C and ENC1 (false discovery rate < 0.05).

32 tations more frequently in males (based on a false discovery rate < 0.1), in comparison to zero of 18

33 EB1, GSDMB, GRAMD3 and ENSA; P < 5 x 10(-8); false discovery rate < 1%).

34 ied 63 differentially methylated CpGs (DMCs; false discovery rate < 5%) proximal to 81 genes (across

35 fy conserved sequences as short as 9 bp with false discovery rate </=0.05.

36 s were found to be differentially expressed (false discovery rate <0.05), of which seven genes replic

37 factors, and caloric intake controlled for (false discovery rate <0.2).Of 113 diet-related metabolit

38 l, 4,901 genes with a fold change >1.5 and a false discovery rate <5% were detected in patients versu

39 ly developed genetic pleiotropic conditional false discovery rate (cFDR) approach to discover novel l

40 tified several significant pathways for BMD [false discovery rate (FDR) < 0.05], such as KEGG FOCAL A

41 ng over 10,000 gene targets (eGenes), with a false discovery rate (FDR) < 5%.

42 the 23,060 significant cis-regulated genes (false discovery rate (FDR) </= 0.05), 2,743 (12%) showed

43 ficantly higher blood erythritol [P < 0.001, false discovery rate (FDR) = 0.0435], and the targeted a

44 nt, (ii) a Bonferroni adjustment and (iii) a false discovery rate (FDR) adjustment which is widely us

45 ating characteristic (ROC) curve to minimize false discovery rate (FDR) and calculate the best thresh

46 testing procedure, named Bon-EV, to control false discovery rate (FDR) based on Bonferroni's approac

47 gress in multiple testing procedures such as false discovery rate (FDR) control, methods that take in

48 t a much larger number of putative loci at a false discovery rate (FDR) of 5% (refs.

49 We used conjunction false discovery rate (FDR) to evaluate genetic pleiotrop

50 nce of the tools in terms of sensitivity and false discovery rate (FDR) using real data and simulated

51 blood at epigenome-wide significance level [false discovery rate (FDR)<0.05].

52 sociated SNPs by estimating stratum-specific false discovery rate (FDR), where strata are classified

53 idely used statistical method for estimating false discovery rate (FDR), which is a conventional sign

54 t SNPs with significant Bayes factor at a 5% false discovery rate (FDR).

55 ative enrichment score (RES) and conditional false discovery rate (FDR).

56 fied cross-linked peptide pairs passing a 5% false discovery rate (on average approximately 21% more

57 groups improved on improvement index (>30%; false discovery rate [FDR] corrected p < 0.0008) and non

58 in areas of alpha-s- and beta-casein (P<.01, false discovery rate [FDR]<.1).

59 , and 50 showed at least 1.5-fold variation (false discovery rate adjustment q value <0.05).

60 s from multiple phenotypes using conditional false discovery rate analysis provides increased power t

61 Genetic loci identified by conditional false discovery rate analysis.

62 novel ALS-associated loci using conditional false discovery rate analysis.

63 e number of associated disease genes at a 5% false discovery rate by an average of 2.1-fold compared

64 ompared by using a general linear model with false discovery rate control for multiple comparisons.

65 s analysis, p values were significant at the false discovery rate corrected threshold of p=0.0156.

66 sm (statistical parametric mapping analyses, false discovery rate corrected).

67 the benefits of open searching for improved false discovery rate estimation in proteomics.

68 ctional analysis identified 17 novel loci at false discovery rate less than 0.05 with overlap between

69 Using the conjunction false discovery rate method, this study analyzed GWAS da

70 ergy (P = 1.4e-17) encompassing 29 loci at a false discovery rate of less than 0.05.

71 transcripts and genes from 1599 genes (DEGs; false discovery rate P<0.05, fold change |2|, controllin

72 with the majority (22/29) of genes passing a false discovery rate threshold of 0.3.

73 tistical significance (fold change>/=1.5 and false discovery rate</=0.05), to identify unique proteom

74 ly expressed in vivo compared with in vitro (false discovery rate, </=0.001; 2-fold change) with 557

75 plicated in at least one replication cohort (false discovery rate, <25%).

76 significant single-nucleotide polymorphisms (false discovery rate, 15%) in 4 quantitative trait loci

77 and -28.24 [-56.29 to 12.08], respectively; false discovery rate-adjusted P = .01 and .03, respectiv

78 , and 10.72 [-11.23 to 29.57], respectively; false discovery rate-adjusted P = .01, .04, and .05, res

79 itine; median change, 7.83 [-5.64 to 26.99]; false discovery rate-adjusted P = .03).

80 False discovery rate-based statistics identified a highe

81 False discovery rate-corrected voxel-based findings were

82 ed cell supernatants were identified at a 1% false discovery rate.

83 ially abundant proteins with a corresponding false discovery rate.

84 3,301 unique cross-links at approximately 1% false discovery rate.

85 , difficulties replicating findings and high false discovery rates).

86 significant covariances and also to control false discovery rates, even when the sample size is smal

87 , and permutation testing was used to assess false discovery rates.

88 and smoking, and p-values were adjusted for false discovery.

89 -trait-associated changes in expression at a false-discovery rate < 0.05.

90 hain fatty acid (SCFA) producer Lachnospira [false-discovery rate (FDR)-corrected P = 0.25] but decre

91 ltiple hypothesis testing by controlling the false-discovery rate (FDRWilcoxon, FDRNoether) with a si

92 he curve of 0.64, p<0.0001), but with a high false-discovery rate of 72%.

93 dentified cis-eQTLs for 12,400 genes at a 1% false-discovery rate.

94 We note that false-discovery rates can be estimated at different poin

95 and would have a significantly lower average false genotype rate than using whole-exome sequencing to

96 t attribution for KB, in accordance with its false identity as oral epidermoid carcinoma, but only 57

97 d a modified location-cueing paradigm, where false information about the percentage of cue validity (

98 othetical risk derived from the demonstrably false LNTH.

99 ible but never encoded events (i.e., related false memories).

100 ll have many false positive interactions and false negative edge loss due to the limitations of high-

101 In particular, the false negative errors restrict the search space of such

102 ntiretroviral therapy was observed to have a false negative OMT result, from July 2015 urine samples

103 of prostate needle biopsies, which have high false negative rates.

104 this test has substantial false positive and false negative rates.

105 curacy and reduced false positive as well as false negative rates.

106 se tools suffer from high false positive and false negative rates.

107 e to catalyze the reverse direction to avoid false negative results.

108 of the test reliability, as indicated by the false-negative (FN), false-positive (FP), and fixation l

109 e/Epi test; Cepheid, Sunnyvale, CA) found no false-negative and 4 false-positive cobas Cdiff test res

110 Overall false-negative and false-positive fractions were 22% and

111 is, was significantly lower expressed in PET false-negative cases (5.3-fold change, P < .001) which p

112 ogic correlation although false-positive and false-negative cases exist.

113 g appropriate antimicrobial therapy, with no false-negative cases.

114 method that accounts for false-positive and false-negative errors to test deer saliva for chronic wa

115 vity with human and porcine fVIII leading to false-negative HSM results.

116 I-RADS) version 2 score to better understand false-negative lesion characteristics.

117 e a relevant number of patients with FDG-PET false-negative MM and a strong association between hexok

118 -positive, true-negative, false-positive and false-negative patients as classified against any refere

119 The higher analytic sensitivity and lower false-negative rate of HTS improves upon FC for MRD dete

120 formed (PPV3), 30.4% (95% CI: 29.9%, 30.9%); false-negative rate, 4.8 per 1000 (95% CI: 4.6, 5.0); se

121 ecommendations; harms (false-positive rates, false-negative rates, surgery rates).

122 ver e-cigarette use), indicating substantial false-negative rates.

123 There were no false-negative ratings.

124 asmodium falciparum hrp2 (pfhrp2) gene cause false-negative RDT results and have never been investiga

125 the number of antimalarial treatments due to false-negative RDT results.

126 However, pfhrp2 gene deletions yielding false-negative RDTs, first reported in South America in

127 ed negative OFOQ results as true-negative or false-negative relative to nucleic acid amplification te

128 , and may explain an important proportion of false-negative resistance determinations.

129 ing recurrent or persistent EMPD; causes for false-negative results according to their location, hist

130 ities <100/muL, which accounted for 75.7% of false-negative results and 33.3% of PCR-detectable infec

131 by using MR imaging may thus help to reduce false-negative results and improve risk assessment.

132 test performance and factors contributing to false-negative results in longitudinal studies, we exami

133 However, the risk of PET false-negative results in the presence of carbidopa is a

134 er of true- and false-positive and true- and false-negative results were extracted to fit a cross-tab

135 False-negative results were found in 2 patients and occu

136 No false-negative results were found.

137 vel parasitemia, and PfHRP-II tests can give false-negative results when P. falciparum strains do not

138 Seven of the 1982 patients (0.4%) had false-negative results with the staged algorithm.

139 The AST systems showed false-negative results with varying numbers, misidentify

140 problems associated with false-positive and false-negative results, inconsistencies and low reactivi

141 The observed false-negative screening results also underline that BM

142 ogenicity, host factors, vaginal microbiome, false-negative screening, and/or changes in antibiotic r

143 All 4 false-negative stx1 or stx2 results were reported for fr

144 rasound did not detect a retinal detachment (false-negative).

145 The true-positive, false-positive, false-negative, and unconfirmed rates for unknown primar

146 tive scans for primary tumor were considered false-negative.

147 f patients with solid malignancies; however, false negatives and false positives remain major limitat

148 ged by their intrinsic diversity, leading to false negatives and incomplete characterisation.

149 coreference resolution are a common cause of false negatives in information extraction from the scien

150 ttenuating the number of false positives and false negatives under high-throughput screening conditio

151 t sensitivity and minimize the likelihood of false negatives.

152 full potential of chemical libraries due to false negatives.

153 Assess the impact of false-positives (FP), false-negatives (FN), fixation losses (FL), and test dur

154 study was to describe the proportion of PET false-negativity in a representative set of 227 newly di

155 signals must be reliably discriminated from false or noise signals.

156 pproach reliably discerns bona fide PAS from false PAS that arise due to internal poly(A) tracts, a c

157 Flagging and removing such false peaks manually is a time-consuming task and prone

158 ties than traditional LC-MS/MS, produced one false positive and did not detect 6 confirmed compounds.

159 se deficiency, but this test has substantial false positive and false negative rates.

160 owever, many of these tools suffer from high false positive and false negative rates.

161 still suffers from non-negligible numbers of false positive and negative SNV and INDEL calls that wer

162 atched spectra in spite of potential risk of false positive annotations emerging from automation.

163 , in terms of increased accuracy and reduced false positive as well as false negative rates.

164 tion sequencing (NGS) data is susceptible to false positive calls due to sequencing, mapping and othe

165 To better distinguish true from false positive calls, we present a method that uses geno

166 cific reasons why XCMS and MZmine 2 find the false positive EIC peaks that they do and in what ways t

167 ed procedure is able to properly control the false positive error rate at the nominal level.

168 .18-3.83) and had a predicted probability of false positive HCC greater than 10% regardless of larges

169 ltiple DNA cleavage events can be a cause of false positive hit identification.

170 nd peptide retention prediction filtering of false positive identifications.

171 e of the tested compounds may be measured as false positive inhibitors with the much-utilized ThT ass

172 ent years, most PPI networks still have many false positive interactions and false negative edge loss

173 It can also be a rate-limiting step if high false positive or negative rates necessitate multiple ro

174 redicting CRM activity, but is also prone to false positive predictions.

175 ional 9 true positives being discovered at a false positive probability of 0.2 and 5 additional true

176 accurate in QTN effect estimation, had less false positive rate and required less computing time tha

177 At a False Positive Rate of 5%, our method determines true po

178 icted with sensitivities of 63% and 58% at a false positive rate of 6% and 7% at 12 and 24 hours, res

179 At 24 hours, sensitivity of 65% with a false positive rate of 6% was obtained.

180 Our goal was to reduce the false positive rate of CM diagnosis, and so the algorith

181 ed that LASSO had the higher power and lower false positive rate than the other three methods.

182 sent in mate-pair sequencing and reduces the false positive rate while maintaining sensitivity.

183 As a result, pKWmEB effectively controlled false positive rate, although a less stringent significa

184 tein interactions at the expense of only 19% false positive rate.

185 the data adaptive method in order to compare false positive rates.

186 ns in sets of isogenic samples with very low false positive rates.

187 retention time prediction, text-mining based false positive removal/true positive ranking, chemical t

188 In either case, we found a high level of false positive results and a general lack of correlation

189 hat the proposed method has low fractions of false positive/negative bouton detections (2/0 out of 18

190 the highest selectivities, yielding only one false positive; however, it was bias toward the most int

191 There were 52 true-negative (29%) and 17 false-positive (10%) (18)F-FDG PET/CT studies.

192 ty, as indicated by the false-negative (FN), false-positive (FP), and fixation loss (FL) rates, on gl

193 th good histopathologic correlation although false-positive and false-negative cases exist.

194 with a statistical method that accounts for false-positive and false-negative errors to test deer sa

195 calculation of true-positive, true-negative, false-positive and false-negative patients as classified

196 wever, for gelatin, problems associated with false-positive and false-negative results, inconsistenci

197 n, technical parameters, number of true- and false-positive and true- and false-negative results were

198 specificity of 95% (58/61), caused by three false-positive calls with ARMS-PCR.

199 minations identified 42.9% (39 of 91) of the false-positive cases to be the same lesion as the IBC.

200 Sunnyvale, CA) found no false-negative and 4 false-positive cobas Cdiff test results.

201 False-positive detection, acute infection during the win

202 Outcomes included number of infants with false-positive diagnoses linked to ART per 1,000 ART ini

203 d infants incorrectly treated with ART after false-positive diagnosis (e.g., medication toxicities);

204 BP responses but are not more likely to have false-positive DSE results.

205 tive predictive value for HCC (R1, two fewer false-positive findings).

206 Overall false-negative and false-positive fractions were 22% and 2%, respectively;

207 The risk of false-positive HCC is markedly higher in certain groups,

208 False-positive HCC was defined as answering "no" to the

209 ed T2 MELD exceptions, of which 245 (6%) had false-positive HCC.

210 ed bioenergetic shunt that greatly minimizes false-positive hits, we identify mitoxantrone out of mor

211 s can deliver a multitude of data, including false-positive hits.

212 pplied to ligand screening in the context of false-positive hits.

213 ble to distinguish between true-positive and false-positive homology groups.

214 true-positive lesions in five patients and a false-positive lesion in one patient.

215 gest that disseminated NTM disease may cause false-positive LF-LAM results.

216 n subjects with F0-F2 fibrosis, the rates of false-positive LSM results for F3-F4 fibrosis increased

217 biopsies, or other procedures performed for false-positive or indeterminate surveillance results.

218 with cirrhosis experience physical harm for false-positive or indeterminate surveillance tests-more

219 periments and that this variability leads to false-positive peak calls.

220 ding XCMS-online and MZmine2, yield numerous false-positive peak detections.

221 We use this approach to show a reduction in false-positive peaks as well as improved consistency acr

222 ingle chromatin marks leads to high rates of false-positive predictions.

223 , benign, or normal findings, resulting in a false-positive rate of 29.6%.

224 on positively correlates with the behavioral false-positive rate of face choices.

225 d success as they all suffered from the high false-positive rate of target prediction results.

226 Screening performance (sensitivity, false-positive rate) and diagnostic accuracy (95% confid

227 redictive value to predict poor recovery (0% false-positive rate), and provided equal performance to

228 fractures at high sensitivity and with a low false-positive rate, as well as to calculate vertebral b

229 e (<10%) of vision abnormalities showed high false-positive rates (usually >75%).

230 False-positive rates for progression in normal eyes usin

231 the potential harms of treatment (ie, higher false-positive rates in low-prevalence populations) as s

232 on by history of coronary heart disease, the false-positive rates of association tests will be close

233 Importantly, false-positive rates were not affected by selection bias

234 her USPSTF screening recommendations; harms (false-positive rates, false-negative rates, surgery rate

235 in low positive predictive values (PPVs) and false-positive rates, with a lack of precision in accura

236 Once the anti-HBc alone pattern is detected, false-positive reactivity should be ruled out and furthe

237 dered noteworthy after the correction by the false-positive report probability.

238 TBDRplus performed on positive cultures, the false-positive resistance rate for direct testing of MTB

239 No false-positive response is generated when the sensors ar

240 -6 dB) loss, primarily owing to an elevated false-positive response rate.

241 y 100%; 95% CI 88.4-100) with two additional false-positive results (specificity 99.9%; 99.7-100).

242 Commercial ELISA kits are known to give false-positive results for OTA concentrations when pheno

243 nt of genetic dependency, thereby leading to false-positive results in copy number-amplified regions.

244 hreshold of alpha = 2.5% for controlling for false-positive results or type 1 error, regardless of th

245 All specimens with false-positive results were found to contain stx1 or stx

246 otracer, as well as conditions that engender false-positive results.

247 ing a negative screening as the reference, a false-positive screening examination increased the risk

248 P = .03) compared with women with a previous false-positive screening with benign biopsy.

249 and 2.8 (95% CI: 1.8, 4.4) for women with a false-positive screening without and with needle biopsy,

250 ompared with those detected after a previous false-positive screening.

251 varying amounts of CCDs sufficient to cause false-positive test results up to 2 kUA/L with nonglycos

252 As a consequence of a false-positive test, 65 individuals required at least on

253 Harms were sensitive to the rates of false-positive testing and the frequency of liver biopsy

254 ients, 150 (95% CI, 146-154) had one or more false-positive tests equating to a number needed to harm

255 linked to and retained in care for 10 years (false-positive) or lifelong (true-positive).

256 did not actually have a retinal detachment (false-positive).

257 The true-positive, false-positive, false-negative, and unconfirmed rates fo

258 te constraint to prevent the accumulation of false positives across large-scale data sets.

259 enging to develop; attenuating the number of false positives and false negatives under high-throughpu

260 False positives are limited using the introduced Sequent

261 g/L as a threshold associated with almost no false positives at acceptable sensitivity.

262 igher sensitivity than Aptima, but with more false positives from pharyngeal samples.

263 False positives from structural OCT can be mitigated wit

264 However, bidirectional promoters scored as false positives in CRISRPi.

265 To reduce this overflow of false positives in next-generation sequencing (NGS) scre

266 datasets and estimated a potential source of false positives in one dataset.

267 r groups as well as seven adult controls; no false positives or negatives were identified.

268 d malignancies; however, false negatives and false positives remain major limitations.

269 ith different error properties; it minimizes false positives resulting from mapping errors and other

270 tions and predicting arguably higher quality false positives that are located nearby the native bindi

271 ands; hGal-3C-25 of 25; hGal-7-28 of 30); no false positives were detected.

272 ng correction can generate a large number of false positives while multi-testing correction tremendou

273 the confidence in calls, reduce the risk of false positives, and help characterize complex events.

274 se new algorithms detect significantly fewer false positives.

275 re packages reported a substantial number of false positives.

276 de of tRNA space and flags them as candidate false positives.

277 pped to a reference genome to further reduce false positives.

278 tudies and have a higher likelihood of being false positives.

279 se additional flagged features were verified false positives.

280 y 2.2% of MARGI-identified interactions were false positives.

281 Assess the impact of false-positives (FP), false-negatives (FN), fixation los

282 he later progressive diseases on CT, with no false-positives.

283 drug-target pairs, which introduces a lot of false-positives.

284 ue positivity was significantly greater than false positivity (P < 0.0001).

285 e contents with perfect accuracy without any false prediction.

286 ectively decreased participants' updating of false prior beliefs concerning %CV, reflected in a decre

287 new predictor is 37% higher and the absolute false rate is four times lower in comparison with the st

288 Occasional false-reactive Aptima results in uninfected individuals,

289 cue enhances memory for words and increases false recall.

290 incidence assay performance is evaluated via false recency rate (FRR) and mean duration of recent inf

291 of prior probabilities for null hypotheses, false report probability is likely to exceed 50% for the

292 Notably, we also found cases of false-resistance because of the misclassification of pol

293 reported here eliminates the possibility of false result as in case of serotype specific DNA sensor.

294 rotors, although provoked the apparition of false rotors during 100% of time.

295 correct classification rates for genuine and false samples over 98.6% and 93.1%, respectively, indica

296 by the Environmental Protection Agency under false scientific pretenses.

297 ange with negligible nonspecific binding and false signal in undiluted serum.

298 e with insignificant nonspecific binding and false signal in undiluted serum.

299 odes reduces as the database grows and that 'false' species-unique barcodes remain >5% until the data

300 ither mask true treatment effects or suggest false treatment effects relative to analyses of time to