scholarly journals Motif Evaluation by Leave-one-out Scoring

2006 ◽  
Author(s):  
Audrey Girouard ◽  
Noah W. Smith ◽  
Donna K. Slonim
Keyword(s):  
Leave One Out

QSAR Studies of Halogenated Pyrimidine Derivatives as Inhibitors of Human Dihydroorotate Dehydrogenase Using Modified Bee Algorithm

2018 ◽  
Vol 21 (5) ◽  
pp. 381-387 ◽  
Author(s):  
Hossein Atabati ◽  
Kobra Zarei ◽  
Hamid Reza Zare-Mehrjardi
Keyword(s):  
External Validation ◽  
Correlation Coefficients ◽  
Quantitative Structure Activity Relationship ◽  
Molecular Structures ◽  
Dihydroorotate Dehydrogenase ◽  
Pyrimidine Derivatives ◽  
Qsar Studies ◽  
Bee Algorithm ◽  
Test Sets ◽  
Leave One Out

Aim and Objective: Human dihydroorotate dehydrogenase (DHODH) catalyzes the fourth stage of the biosynthesis of pyrimidines in cells. Hence it is important to identify suitable inhibitors of DHODH to prevent virus replication. In this study, a quantitative structure-activity relationship was performed to predict the activity of one group of newly synthesized halogenated pyrimidine derivatives as inhibitors of DHODH. Materials and Methods: Molecular structures of halogenated pyrimidine derivatives were drawn in the HyperChem and then molecular descriptors were calculated by DRAGON software. Finally, the most effective descriptors for 32 halogenated pyrimidine derivatives were selected using bee algorithm. Results: The selected descriptors using bee algorithm were applied for modeling. The mean relative error and correlation coefficient were obtained as 2.86% and 0.9627, respectively, while these amounts for the leave one out−cross validation method were calculated as 4.18% and 0.9297, respectively. The external validation was also conducted using two training and test sets. The correlation coefficients for the training and test sets were obtained as 0.9596 and 0.9185, respectively. Conclusion: The results of modeling of present work showed that bee algorithm has good performance for variable selection in QSAR studies and its results were better than the constructed model with the selected descriptors using the genetic algorithm method.

Label-Free Mass Spectrometry-Based Plasma Proteomics Identified LY6D, DSC3, CDSN, SERPINB12, and SLURP1,as Novel Protein Biomarkers For Pulmonary Tuberculosis

2019 ◽  
Vol 17 ◽  
Author(s):  
Xiaoli Yu ◽  
Lu Zhang ◽  
Na Li ◽  
Peng Hu ◽  
Zhaoqin Zhu ◽  
...  
Keyword(s):  
Pulmonary Tuberculosis ◽  
Search Algorithm ◽  
Differentially Expressed ◽  
P Value ◽  
Plasma Samples ◽  
Label Free ◽  
Protein Biomarkers ◽  
Protein Database ◽  
Leave One Out ◽  
Potential Biomarkers

Aim: We aimed to identify new plasma biomarkers for the diagnosis of Pulmonary tuberculosis. Background: Tuberculosis is an ancient infectious disease that remains one of the major global health problems. Until now, effective, convenient, and affordable methods for diagnosis of Pulmonary tuberculosis were still lacked. Objective: This study focused on construct a label-free LC-MS/MS based comparative proteomics between six tuberculosis patients and six healthy controls to identify differentially expressed proteins (DEPs) in plasma. Method: To reduce the influences of high-abundant proteins, albumin and globulin were removed from plasma samples using affinity gels. Then DEPs from the plasma samples were identified using a label-free Quadrupole-Orbitrap LC-MS/MS system. The results were analyzed by the protein database search algorithm SEQUEST-HT to identify mass spectra to peptides. The predictive abilities of combinations of host markers were investigated by general discriminant analysis (GDA), with leave-one-out cross-validation. Results: A total of 572 proteins were identified and 549 proteins were quantified. The threshold for differentially expressed protein was set as adjusted p-value < 0.05 and fold change ≥1.5 or ≤0.6667, 32 DEPs were found. ClusterVis, TBtools, and STRING were used to find new potential biomarkers of PTB. Six proteins, LY6D, DSC3, CDSN, FABP5, SERPINB12, and SLURP1, which performed well in the LOOCV method validation, were termed as potential biomarkers. The percentage of cross-validated grouped cases correctly classified and original grouped cases correctly classified is greater than or equal to 91.7%. Conclusion: We successfully identified five candidate biomarkers for immunodiagnosis of PTB in plasma, LY6D, DSC3, CDSN, SERPINB12, and SLURP1. Our work supported this group of proteins as potential biomarkers for pulmonary tuberculosis, and be worthy of further validation.

scholarly journals Is jumbo biopsy forceps comparable to cold snare for diminutive colorectal polyps? – a meta-analysis

2021 ◽  
Vol 09 (01) ◽  
pp. E9-E13
Author(s):  
Sachin Srinivasan ◽  
Peter D. Siersema ◽  
Madhav Desai
Keyword(s):  
Meta Analysis ◽  
Complete Removal ◽  
Colorectal Polyps ◽  
Comparable Efficacy ◽  
Incomplete Resection ◽  
Complication Rates ◽  
Biopsy Forceps ◽  
Significant Difference ◽  
Leave One Out ◽  
Endoscopic Assessment

Abstract Background and study aims Diminutive colorectal polyps are increasingly being detected and it is not clear whether jumbo biopsy forceps (JBF) has comparable efficacy to that of cold snare polypectomy (CSP) for management of these lesions. Methods An electronic literature search was performed for studies comparing resection rates of JBF and CSP for diminutive polyps (≤ 5 mm). The primary outcome was incomplete resection rate (IRR). Secondary outcomes included failure of tissue retrieval and complication rates (post-polypectomy bleeding, perforation etc.). Leave-one-out analysis was performed to examine the disproportionate role of any of the studies. Meta-analysis outcomes and heterogeneity (I2) were computed using Comprehensive meta-analysis software. Results A total of 4 studies (3 randomized controlled trials and 1 retrospective study) with 407 patients and 569 total polyps (mean size of 3.62 mm) was included for analysis. IRR of JBF was slightly higher than that of CSP (10.2 % vs 7.2 %) but this was not statistically significantly different (Pooled OR 1.76; 95 % CI 0.94–3.28; I2 = 0). Leave-one-out analysis showed no significant difference in the pooled OR comparison either. Two of the 4 studies reported 0 % failure of tissue retrieval for JBF and 1 % and 4.3 % for CSP. There were no complications for either group from the 2 studies that reported this outcome. The quality of the included studies was moderate to high. Conclusions This systematic review with only limited data shows that JBF and CSP are not statistically different in completely removing diminutive polyps, although careful endoscopic assessment is needed to ensure complete removal of all polyp tissue.

scholarly journals How Accurate Is an Unmanned Aerial Vehicle Data-Based Model Applied on Satellite Imagery for Chlorophyll-a Estimation in Freshwater Bodies?

2021 ◽  
Vol 13 (6) ◽  
pp. 1134
Author(s):  
Anas El-Alem ◽  
Karem Chokmani ◽  
Aarthi Venkatesan ◽  
Lhissou Rachid ◽  
Hachem Agili ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Unmanned Aerial Vehicle ◽  
Optical Sensors ◽  
Regional Scale ◽  
Turbid Waters ◽  
Vehicle Data ◽  
Freshwater Bodies ◽  
Aerial Vehicle ◽  
Leave One Out ◽  
Semi Empirical

Optical sensors are increasingly sought to estimate the amount of chlorophyll a (chl_a) in freshwater bodies. Most, whether empirical or semi-empirical, are data-oriented. Two main limitations are often encountered in the development of such models. The availability of data needed for model calibration, validation, and testing and the locality of the model developed—the majority need a re-parameterization from lake to lake. An Unmanned aerial vehicle (UAV) data-based model for chl_a estimation is developed in this work and tested on Sentinel-2 imagery without any re-parametrization. The Ensemble-based system (EBS) algorithm was used to train the model. The leave-one-out cross validation technique was applied to evaluate the EBS, at a local scale, where results were satisfactory (R2 = Nash = 0.94 and RMSE = 5.6 µg chl_a L−1). A blind database (collected over 89 lakes) was used to challenge the EBS’ Sentine-2-derived chl_a estimates at a regional scale. Results were relatively less good, yet satisfactory (R2 = 0.85, RMSE= 2.4 µg chl_a L−1, and Nash = 0.79). However, the EBS has shown some failure to correctly retrieve chl_a concentration in highly turbid waterbodies. This particularity nonetheless does not affect EBS performance, since turbid waters can easily be pre-recognized and masked before the chl_a modeling.

scholarly journals Prevalence of Metastatic Lateral Lymph Nodes in Asian Patients with Lateral Lymph Node Dissection for Rectal Cancer: A Meta-analysis

2021 ◽  
Author(s):  
Niki Christou ◽  
Jeremy Meyer ◽  
Christophe Combescure ◽  
Alexandre Balaphas ◽  
Joan Robert-Yap ◽  
...  
Keyword(s):  
Lymph Nodes ◽  
Meta Analysis ◽  
Neoadjuvant Treatment ◽  
Rectal Surgery ◽  
Node Dissection ◽  
Asian Countries ◽  
Mesorectal Excision ◽  
Lateral Lymph Node ◽  
Pooled Prevalence ◽  
Leave One Out

Abstract Importance Rectal cancers occupy the eighth position worldwide for new cases and deaths for both men and women. These cancers have a high tendency to form metastases in the mesorectum but also in the lateral lymph nodes. The therapeutic approach for the involved lateral lymph nodes remains controversial. Objective We performed a systematic review and meta-analysis to assess the prevalence of metastatic lateral lymph nodes in patients with lateral lymph node dissection (LLND) for rectal cancer, which seems to be a fundamental and necessary criterion to discuss any possible indications for LLND. Methods Data sources–study selection–data extraction and synthesis–main outcome and measures. We searched MEDLINE, EMBASE and COCHRANE from November 1, 2018, to November 19, 2018, for studies reporting the presence of metastatic lateral lymph nodes (iliac, obturator and middle sacral nodes) among patients undergoing rectal surgery with LLND. Pooled prevalence values were obtained by random effects models, and the robustness was tested by leave-one-out sensitivity analyses. Heterogeneity was assessed using the Q-test, quantified based on the I2 value and explored by subgroup analyses. Results Our final analysis included 31 studies from Asian countries, comprising 7599 patients. The pooled prevalence of metastatic lateral lymph nodes was 17.3% (95% CI: 14.6–20.5). The inter-study variability (heterogeneity) was high (I2 = 89%). The pooled prevalence was, however, robust and varied between 16.6% and 17.9% according to leave-one-out sensitivity analysis. The pooled prevalence of metastatic lymph nodes was not significantly different when pooling only studies including patients who received neoadjuvant treatment or those without neoadjuvant treatment (p = 0.44). Meta-regression showed that the pooled prevalence was associated with the sample size of studies (p < 0.05), as the prevalence decreased when the sample size increased. Conclusion The pooled prevalence of metastatic lateral lymph nodes was 17.3% among patients who underwent rectal surgery with LLND in Asian countries. Further studies are necessary to determine whether this finding could impact the therapeutic strategy (total mesorectal excision with LLND versus total mesorectal excision with neoadjuvant radiochemotherapy).

scholarly journals In Silico Prediction of Drug–Drug Interactions Mediated by Cytochrome P450 Isoforms

Pharmaceutics ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 538
Author(s):  
Alexander V. Dmitriev ◽  
Anastassia V. Rudik ◽  
Dmitry A. Karasev ◽  
Pavel V. Pogodin ◽  
Alexey A. Lagunin ◽  
...  
Keyword(s):  
Cytochrome P450 ◽  
Drug Interactions ◽  
Cytochromes P450 ◽  
Investigational Drug ◽  
Web Resource ◽  
Average Accuracy ◽  
Structural Formulas ◽  
Cytochrome P450 Isoforms ◽  
Leave One Out ◽  
Important Drug

Drug–drug interactions (DDIs) can cause drug toxicities, reduced pharmacological effects, and adverse drug reactions. Studies aiming to determine the possible DDIs for an investigational drug are part of the drug discovery and development process and include an assessment of the DDIs potential mediated by inhibition or induction of the most important drug-metabolizing cytochrome P450 isoforms. Our study was dedicated to creating a computer model for prediction of the DDIs mediated by the seven most important P450 cytochromes: CYP1A2, CYP2B6, CYP2C19, CYP2C8, CYP2C9, CYP2D6, and CYP3A4. For the creation of structure–activity relationship (SAR) models that predict metabolism-mediated DDIs for pairs of molecules, we applied the Prediction of Activity Spectra for Substances (PASS) software and Pairs of Substances Multilevel Neighborhoods of Atoms (PoSMNA) descriptors calculated based on structural formulas. About 2500 records on DDIs mediated by these cytochromes were used as a training set. Prediction can be carried out both for known drugs and for new, not-yet-synthesized substances. The average accuracy of the prediction of DDIs mediated by various isoforms of cytochrome P450 estimated by leave-one-out cross-validation (LOO CV) procedures was about 0.92. The SAR models created are publicly available as a web resource and provide predictions of DDIs mediated by the most important cytochromes P450.

Mapping Arctic clam abundance using multiple datasets, models, and a spatially explicit accuracy assessment

2019 ◽  
Vol 76 (7) ◽  
pp. 2349-2361
Author(s):  
Benjamin Misiuk ◽  
Trevor Bell ◽  
Alec Aitken ◽  
Craig J Brown ◽  
Evan N Edinger
Keyword(s):  
Spatial Autocorrelation ◽  
Cross Validation ◽  
Predictive Accuracy ◽  
Accuracy Assessment ◽  
Small Scale ◽  
Suitable Habitat ◽  
Distribution Models ◽  
Management Tools ◽  
Seabed Topography ◽  
Leave One Out

Abstract Species distribution models are commonly used in the marine environment as management tools. The high cost of collecting marine data for modelling makes them finite, especially in remote locations. Underwater image datasets from multiple surveys were leveraged to model the presence–absence and abundance of Arctic soft-shell clam (Mya spp.) to support the management of a local small-scale fishery in Qikiqtarjuaq, Nunavut, Canada. These models were combined to predict Mya abundance, conditional on presence throughout the study area. Results suggested that water depth was the primary environmental factor limiting Mya habitat suitability, yet seabed topography and substrate characteristics influence their abundance within suitable habitat. Ten-fold cross-validation and spatial leave-one-out cross-validation (LOO CV) were used to assess the accuracy of combined predictions and to test whether this was inflated by the spatial autocorrelation of transect sample data. Results demonstrated that four different measures of predictive accuracy were substantially inflated due to spatial autocorrelation, and the spatial LOO CV results were therefore adopted as the best estimates of performance.

CLASSIFICATION OF HIGH-DIMENSIONAL MICROARRAY DATA WITH A TWO-STEP PROCEDURE VIA A WILCOXON CRITERION AND MULTILAYER PERCEPTRON

2011 ◽  
Vol 10 (01) ◽  
pp. 1-14
Author(s):  
VLADIMIR NIKULIN ◽  
TIAN-HSIANG HUANG ◽  
GEOFFREY J. MCLACHLAN
Keyword(s):  
Data Mining ◽  
Feature Selection ◽  
High Dimensional ◽  
Second Step ◽  
Support Vector ◽  
Step Procedure ◽  
Leave One Out ◽  
Natural Combination ◽  
Feature Selection Techniques

The method presented in this paper is novel as a natural combination of two mutually dependent steps. Feature selection is a key element (first step) in our classification system, which was employed during the 2010 International RSCTC data mining (bioinformatics) Challenge. The second step may be implemented using any suitable classifier such as linear regression, support vector machine or neural networks. We conducted leave-one-out (LOO) experiments with several feature selection techniques and classifiers. Based on the LOO evaluations, we decided to use feature selection with the separation type Wilcoxon-based criterion for all final submissions. The method presented in this paper was tested successfully during the RSCTC data mining Challenge, where we achieved the top score in the Basic track.

scholarly journals Genome-wide inferring gene–phenotype relationship by walking on the heterogeneous network

2010 ◽  
Vol 26 (9) ◽  
pp. 1219-1224 ◽  
Author(s):  
Yongjin Li ◽  
Jagdish C. Patra
Keyword(s):  
Heterogeneous Network ◽  
Gene Network ◽  
Genetic Diseases ◽  
Supplementary Information ◽  
Disease Genes ◽  
Phenotypic Data ◽  
Disease Associations ◽  
Improved Performance ◽  
Leave One Out ◽  
Phenotype Network

Abstract Motivation: Clinical diseases are characterized by distinct phenotypes. To identify disease genes is to elucidate the gene–phenotype relationships. Mutations in functionally related genes may result in similar phenotypes. It is reasonable to predict disease-causing genes by integrating phenotypic data and genomic data. Some genetic diseases are genetically or phenotypically similar. They may share the common pathogenetic mechanisms. Identifying the relationship between diseases will facilitate better understanding of the pathogenetic mechanism of diseases. Results: In this article, we constructed a heterogeneous network by connecting the gene network and phenotype network using the phenotype–gene relationship information from the OMIM database. We extended the random walk with restart algorithm to the heterogeneous network. The algorithm prioritizes the genes and phenotypes simultaneously. We use leave-one-out cross-validation to evaluate the ability of finding the gene–phenotype relationship. Results showed improved performance than previous works. We also used the algorithm to disclose hidden disease associations that cannot be found by gene network or phenotype network alone. We identified 18 hidden disease associations, most of which were supported by literature evidence. Availability: The MATLAB code of the program is available at http://www3.ntu.edu.sg/home/aspatra/research/Yongjin_BI2010.zip Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

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