scholarly journals Biclique extension as an effective approach to predict novel interaction partners in metabolic compound-protein interaction networks.

2021 ◽  
Author(s):  
Sandra Thieme ◽  
Dirk Walther
Keyword(s):  
Protein Interactions ◽  
Metabolic Networks ◽  
Experimental Testing ◽  
Statistical Significance ◽  
False Positive Rate ◽  
Critical Role ◽  
Tca Cycle ◽  
Unknown Compound ◽  
E Coli ◽  
Positive Rate

Motivation: Metabolic networks are complex systems of connected chemical reactions with physical interactions between metabolites and proteins playing a critical role for both metabolic conversion and regulation. In this study, we aimed to predict previously unknown compound-protein interactions (CPI) by transferring the concept of biclique extension, which was developed in the context of drug-target interaction prediction and that is based on the rationale that interactions that readily extend an existing biclique are real, to metabolic CPI networks. Results: We developed and tested a workflow to predict CPIs based on the concept of extending existing bicliques and applied it to E. coli and human using their respective known CPI network as input. Depending on the chosen biclique size, for the E. coli network we reached a sensitivity of 39% with an associated precision of 59%. For the larger human CPI network, a sensitivity of 78% with a false-positive rate of less than 5% and an associated precision of 75% was obtained. At more stringent settings, a precision as high as 95% was attainable at the expense of a lowered recall. Prediction performance significantly exceeded that obtained using randomized networks as input. Predicted novel interactions were tested for biomolecular function involvement, with TCA-cycle and ribosomal processes found associated with particularly pronounced statistical significance. As we demonstrate, our approach holds great potential to increase efficiency of experimental testing of CPIs and can readily be transferred to other species of interest. Availability and implementation: The R code and datasets are available at https://github.com/SandraThieme/BiPredict.

scholarly journals Detex for Detection of Escherichia coli O157 in Raw Ground Beef and Raw Ground Poultry

2001 ◽  
Vol 84 (3) ◽  
pp. 752-760 ◽  
Author(s):  
Yvette M Henry ◽  
Nandini Natrajan ◽  
Wendy F Lauer
Keyword(s):  
Escherichia Coli ◽  
False Positive Rate ◽  
Ground Beef ◽  
Escherichia Coli O157 ◽  
Department Of Agriculture ◽  
E Coli ◽  
Metal Plating ◽  
Positive Rate ◽  
Meat Samples ◽  
Inspection Service

Abstract A method for detection of Escherichia coli O157 in beef and poultry is presented. The method is antibody-based and uses a patented antibody-specific metal-plating procedure for the detection of E. coli O157 in enriched meat samples. Both raw ground beef and raw ground poultry were tested as matrixes for the organism. The sensitivity and specificity of the assay were 98 and 90%, respectively. The accuracy of the assay was 96%. Overall, the method agreement between the E. coli O157 Detex assay and the U.S. Department of Agriculture/Food Safety Inspection Service method was 96%. Sample temperature upon loading of the apparatus was critical to the observed false-positive rate of the system.

scholarly journals iSUMO - integrative prediction of functionally relevant SUMOylation events

2016 ◽  
Author(s):  
Xiaotong Yao ◽  
Shuvadeep Maity ◽  
Shashank Gandhi ◽  
Marcin Imielenski ◽  
Christine Vogel
Keyword(s):  
Protein Interactions ◽  
Large Scale ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
False Positive Rate ◽  
Protein Protein Interactions ◽  
Cellular Functions ◽  
Positive Rate ◽  
Protein Nucleic Acid ◽  
Scale Experiment

AbstractPost-translational modifications by the Small Ubiquitin-like Modifier (SUMO) are essential for diverse cellular functions. Large-scale experiment and sequence-based predictions have identified thousands of SUMOylated proteins. However, the overlap between the datasets is small, suggesting many false positives with low functional relevance. Therefore, we integrated ~800 sequence features and protein characteristics such as cellular function and protein-protein interactions in a machine learning approach to score likely functional SUMOylation events (iSUMO). iSUMO is trained on a total of 24 large-scale datasets, and it predicts 2,291 and 706 SUMO targets in human and yeast, respectively. These estimates are five times higher than what existing sequence-based tools predict at the same 5% false positive rate. Protein-protein and protein-nucleic acid interactions are highly predictive of protein SUMOylation, supporting a role of the modification in protein complex formation. We note the marked prevalence of SUMOylation amongst RNA-binding proteins. We validate iSUMO predictions by experimental or other evidence. iSUMO therefore represents a comprehensive tool to identify high-confidence, functional SUMOylation events for human and yeast.

scholarly journals Thymine Sensitizes Gram-Negative Pathogens to Antibiotic Killing

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuan Liu ◽  
Kangni Yang ◽  
Yuqian Jia ◽  
Jingru Shi ◽  
Ziwen Tong ◽  
...  
Keyword(s):  
Galleria Mellonella ◽  
Animal Health ◽  
Critical Role ◽  
Tca Cycle ◽  
Bacterial Metabolism ◽  
Infection Model ◽  
Gram Negative Bacteria ◽  
Independent Manner ◽  
Gram Negative ◽  
E Coli

Diminished antibiotic susceptibility of bacterial pathogens is an increasingly serious threat to human and animal health. Alternative strategies are required to combat antibiotic refractory bacteria. Bacterial metabolic state has been shown to play a critical role in its susceptibility to antibiotic killing. However, the adjuvant potential of nucleotides in combination with antibiotics to kill Gram-negative pathogens remains unknown. Herein, we found that thymine potentiated ciprofloxacin killing against both sensitive and resistant-E. coli in a growth phase-independent manner. Similar promotion effects were also observed for other bactericidal antibiotics, including ampicillin and kanamycin, in the fight against four kinds of Gram-negative bacteria. The mechanisms underlying this finding were that exogenous thymine could upregulate bacterial metabolism including increased TCA cycle and respiration, which thereby promote the production of ATP and ROS. Subsequently, metabolically inactive bacteria were converted to active bacteria and restored its susceptibility to antibiotic killing. In Galleria mellonella infection model, thymine effectively improved ciprofloxacin activity against E. coli. Taken together, our results demonstrated that thymine potentiates bactericidal antibiotics activity against Gram-negative pathogens through activating bacterial metabolism, providing a universal strategy to overcome Gram-negative pathogens.

A Realistic Seizure Prediction Study Based on Multiclass SVM

2017 ◽  
Vol 27 (03) ◽  
pp. 1750006 ◽  
Author(s):  
Bruno Direito ◽  
César A. Teixeira ◽  
Francisco Sales ◽  
Miguel Castelo-Branco ◽  
António Dourado
Keyword(s):  
Statistical Significance ◽  
False Positive Rate ◽  
Patient Specific ◽  
Support Vector ◽  
Seizure Prediction ◽  
Feature Sets ◽  
Scalp Eeg ◽  
Positive Rate ◽  
Eeg Recordings ◽  
Multiclass Svm

A patient-specific algorithm, for epileptic seizure prediction, based on multiclass support-vector machines (SVM) and using multi-channel high-dimensional feature sets, is presented. The feature sets, combined with multiclass classification and post-processing schemes aim at the generation of alarms and reduced influence of false positives. This study considers 216 patients from the European Epilepsy Database, and includes 185 patients with scalp EEG recordings and 31 with intracranial data. The strategy was tested over a total of 16,729.80[Formula: see text]h of inter-ictal data, including 1206 seizures. We found an overall sensitivity of 38.47% and a false positive rate per hour of 0.20. The performance of the method achieved statistical significance in 24 patients (11% of the patients). Despite the encouraging results previously reported in specific datasets, the prospective demonstration on long-term EEG recording has been limited. Our study presents a prospective analysis of a large heterogeneous, multicentric dataset. The statistical framework based on conservative assumptions, reflects a realistic approach compared to constrained datasets, and/or in-sample evaluations. The improvement of these results, with the definition of an appropriate set of features able to improve the distinction between the pre-ictal and nonpre-ictal states, hence minimizing the effect of confounding variables, remains a key aspect.

Marginal Effects in Interaction Models: Determining and Controlling the False Positive Rate

2017 ◽  
Vol 51 (9) ◽  
pp. 1144-1176 ◽  
Author(s):  
Justin Esarey ◽  
Jane Lawrence Sumner
Keyword(s):  
Political Parties ◽  
False Positive ◽  
Software Package ◽  
Statistical Significance ◽  
False Positive Rate ◽  
Marginal Effect ◽  
Marginal Effects ◽  
Political Studies ◽  
Positive Rate ◽  
The Relationship

When a researcher suspects that the marginal effect of [Formula: see text] on [Formula: see text] varies with [Formula: see text], a common approach is to plot [Formula: see text] at different values of [Formula: see text] along with a pointwise confidence interval generated using the procedure described in Brambor, Clark, and Golder to assess the magnitude and statistical significance of the relationship. Our article makes three contributions. First, we demonstrate that the Brambor, Clark, and Golder approach produces statistically significant findings when [Formula: see text] at a rate that can be many times larger or smaller than the nominal false positive rate of the test. Second, we introduce the interactionTest software package for R to implement procedures that allow easy control of the false positive rate. Finally, we illustrate our findings by replicating an empirical analysis of the relationship between ethnic heterogeneity and the number of political parties from Comparative Political Studies.

scholarly journals The impact of P-hacking on "Redefine statistical significance"

2017 ◽  
Author(s):  
Harry Crane
Keyword(s):  
False Positive ◽  
Statistical Significance ◽  
False Positive Rate ◽  
Perceived Benefits ◽  
Replication Rate ◽  
Recent Proposal ◽  
Positive Rate ◽  
Replication Crisis ◽  
The Impact ◽  
Lower Cutoff

A recent proposal to "redefine statistical significance" (Benjamin, et al. Nature Human Behaviour, 2017) claims that false positive rates "would immediately improve" by factors greater than two and replication rates would double simply by changing the conventional cutoff for 'statistical significance' from P<0.05 to P<0.005. I analyze the veracity of these claims, focusing especially on how Benjamin, et al neglect the effects of P-hacking in assessing the impact of their proposal. My analysis shows that once P-hacking is accounted for the perceived benefits of the lower threshold all but disappear, prompting two main conclusions: (i) The claimed improvements to false positive rate and replication rate in Benjamin, et al (2017) are exaggerated and misleading. (ii) There are plausible scenarios under which the lower cutoff will make the replication crisis worse.

Miniaturized Fluorogenic Assays for Enumeration of E. coli and Enterococci in Marine Water

1991 ◽  
Vol 24 (2) ◽  
pp. 137-141 ◽  
Author(s):  
J. F. Hernandez ◽  
J. M. Guibert ◽  
J. M. Delattre ◽  
C. Oger ◽  
C. Charrière ◽  
...  
Keyword(s):  
False Positive ◽  
Membrane Filtration ◽  
Uv Light ◽  
False Positive Rate ◽  
Selective Medium ◽  
English Channel ◽  
Standard Methods ◽  
E Coli ◽  
Microtitration Plate ◽  
Positive Rate

To detect E. coli, 4-methylumbelliferyl α-D-glucuronide (MUG) was incorporated into a modified Al-broth. To detect enterococci, 4-methylumbelliferyl α-D-glucoside (MUD) was incorporated into a selective medium. To each well of a sterile 96-well microtitration plate, 100 µl of media was added, air dried, covered with sterile tape and stored at 4°C. To enumerate the indicator bacteria using this method, 200 µ1 of diluted or undiluted water was added to wells with MUG and MUD media. The plates were incubated for 36-40 hours at 44°C and observed in the dark for fluorescence by UV light (366nm). Fifty subsurface marine waters from four areas were examined. The recovery rate of the fluorogenic assays is equal or superior to 3-tubes MPN and membrane filtration. The microtitration plate with MUG is more specific for E. coli than the membrane filtration. A 87.4 % confirmation rate was observed with the fluorogenic assay compared to a 31.7 % false-positive rate with membranes. For the enterococci, the analysis of 23 English Channel and North Sea samples indicated that the fluorogenic assay and the standard methods had the same specificity (<5 % of false-positive on 107 strains identified). In contrast, the microtitration plate with MUD showed, by far, the best specificity on 13 Mediterranean samples. A 100 % confirmation rate was observed with the fluorogenic assay while 44 % and 63 % false-positive rates were observed with 3 tubes MPN and MF respectively.

scholarly journals Genotypic and Phenotypic Characterization of Escherichia coli Isolates from Feces, Hands, and Soils in Rural Bangladesh via the Colilert Quanti-Tray System

2014 ◽  
Vol 81 (5) ◽  
pp. 1735-1743 ◽  
Author(s):  
Timothy R. Julian ◽  
M. Aminul Islam ◽  
Amy J. Pickering ◽  
Subarna Roy ◽  
Erica R. Fuhrmeister ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
False Positive ◽  
False Positive Rate ◽  
Pathogen Transmission ◽  
Environmental Matrices ◽  
Content Type ◽  
E Coli ◽  
Biochemical Assays ◽  
Positive Rate ◽  
Genotypic Characteristics

ABSTRACTThe increased awareness of the role of environmental matrices in enteric disease transmission has resulted in the need for rapid, field-based methods for fecal indicator bacteria and pathogen detection. Evidence of the specificity of β-glucuronidase-based assays for detection ofEscherichia colifrom environmental matrices relevant to enteric pathogen transmission in developing countries, such as hands, soils, and surfaces, is limited. In this study, we quantify the false-positive rate of a β-glucuronidase-basedE. colidetection assay (Colilert) for two environmental reservoirs in Bangladeshi households (hands and soils) and three fecal composite sources (cattle, chicken, and humans). We investigate whether or not the isolation source ofE. coliinfluences phenotypic and genotypic characteristics. Phenotypic characteristics include results of biochemical assays provided by the API-20E test; genotypic characteristics include the Clermont phylogroup and the presence of enteric and/or environmental indicator genessfmH,rfaI, andfucK. Our findings demonstrate no statistically significant difference in the false-positive rate of Colilert for environmental compared to enteric samples.E. coliisolates from all source types are genetically diverse, representing six of the seven phylogroups, and there is no difference in relative frequency of phylogroups between enteric and environmental samples. We conclude that Colilert, and likely other β-glucuronidase-based assays, is appropriate for detection ofE. colion hands and in soils with low false-positive rates. Furthermore,E. coliisolated from hands and soils in Bangladeshi households are diverse and indistinguishable from cattle, chicken, and human fecal isolates, using traditional biochemical assays and phylogrouping.

Is histoscanning a valid tool to detect prostate cancer in repeat biopsy?

2012 ◽  
Vol 30 (5_suppl) ◽  
pp. 57-57
Author(s):  
Robin Epplen ◽  
Julius van Essen ◽  
David J. K. P. Pfister ◽  
Daniel Porres ◽  
Axel Heidenreich
Keyword(s):  
Prostate Cancer ◽  
Statistical Significance ◽  
False Positive Rate ◽  
False Negative ◽  
False Negative Rate ◽  
Repeat Biopsy ◽  
Grid Pattern ◽  
Transrectal Biopsy ◽  
Positive Rate ◽  
Positive Core

57 Background: Histoscanning is a novel ultrasound-based software programme, which uses back-scattered ultrasound, to detect and visualize prostate carcinoma. It is not clear to date which additive information histoscanning will deliver terms of additive information to ultrasound guided transrectal biopsy as research is scarce.Therefore we aimed to analyze our data on repeat biopsy with histoscanning prior to intervention. Methods: From Sept. 2009 till present, 61 patients, mean age 62 yrs, that were scheduled for repeat biopsy received Histoscanning prior to intervention. Acquired data were retrospectively processed with Histoscanning software version 2.2 and prostate was divided into a 6 grid pattern. Lesions ≥0,5ml were considered positive. Biopsies were taken according to Vienna normogram and processed by an experienced uropathologist. Results: Mean number of biopsies prior to repeat was 2. Mean PSA at repeat biopsy was 7,135 ng/ml, mean prostate volume accounted for 45.5 ml. A total of 15/61 men were diagnosed with cancer (24,59%), Gleason Score (Gl.) of 6 n=10, n=2 Gl. 3+4=7, n=2 Gl. 4+4; n=2 Gl. 4+5=9 respectively. A total of 43/834=5.15% positive cores were obtained, averaging 0.7 per person. Mean Volume of Histoscanning lesions per scan: 1,48 ml; no statistical significance can be detected regarding the volume per sextant and a positive core. False positive rate was 90/366=24,6%; false negative rate was 19/366=5,2%. Overall sensitivity was 29,69%, specifity accounted for 73.3%. PPV was calculated at 8.16% and NPV at 92,88%. PSA had no influence on detection rate. Conclusions: In this highly seleted patient cohort Histoscanning had no beneficial nor additive information on detecting prostate cancer. Further research should has to be done regarding Histoscanning lesions with different histopathological features such as prostatitis and fibrosis.

scholarly journals Inferring the genetic architecture of expression variation from replicated high throughput allele-specific expression experiments

2019 ◽  
Author(s):  
Xinwen Zhang ◽  
J.J. Emerson
Keyword(s):  
False Positive ◽  
Statistical Significance ◽  
False Positive Rate ◽  
Regulatory Sequences ◽  
Binomial Model ◽  
Specific Expression ◽  
Allele Specific Expression ◽  
Expression Variation ◽  
Positive Rate ◽  
Allele Specific

AbstractGene expression variation between alleles in a diploid cell is mediated by variation in cis regulatory sequences, which usually refers to the differences in DNA sequence between two alleles near the gene of interest. Expression differences caused by cis variation has been estimated by the ratio of the expression level of the two alleles under a binomial model. However, the binomial model underestimates the variance among replicated experiments resulting in the exaggerated statistical significance of estimated cis effects and thus many false discoveries of cis-affected genes. Here we describe a beta-binomial model that estimates the cis-effect for each gene while permitting overdispersion of variance among replicates. We demonstrated with simulated null data (data without true cis-effect) that the new model fits the true distribution better, resulting in approximately 5% false positive rate under 5% significance level in all null datasets, considerably better than the 6%-40% false positive rate of the binomial model. Additional replicates increase the performance of the beta-binomial model but not of the binomial model. We also collected new allele-specific expression data from an experiment comprised of 20 replicates of a yeast hybrid (YPS128/RM11-1a). We eliminated the mapping bias problem with de novo assemblies of the two parental genomes. By applying the beta-binomial model to this dataset, we found that cis effects are ubiquitous, affecting around 70% of genes. However, most of these changes are small in magnitude. The high number of replicates enabled us a better approximation of cis landscape within species and also provides a resource for future exploration for better models.

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