scholarly journals Estimation of prokaryote genomic DNA G+C content by sequencing universally conserved genes

2006 ◽  
Vol 56 (5) ◽  
pp. 1025-1029 ◽  
Author(s):  
Pierre-Edouard Fournier ◽  
Karsten Suhre ◽  
Ghislain Fournous ◽  
Didier Raoult
Keyword(s):  
Strong Correlation ◽  
Genomic Dna ◽  
Gene Sequence ◽  
Single Copy ◽  
Coefficient Of Determination ◽  
Median Size ◽  
Prokaryotic Genomes ◽  
Conserved Genes ◽  
Clusters Of Orthologous Groups

Determination of the DNA G+C content of prokaryotic genomes using traditional methods is time-consuming and results may vary from laboratory to laboratory, depending on the technique used. We explored the possibility of extrapolating the genomic DNA G+C content of prokaryotes from gene sequences. For this, 127 universally conserved genes were studied from 50 prokaryotic genomes in the Clusters of Orthologous Groups database. Of these, 57 genes were present as a single copy in the genomes of 157 different prokaryote species available in GenBank. There was a strong correlation [coefficient of determination (r 2) >95 %] between the DNA G+C contents of 20 genes and their corresponding genomes. For each of the 157 prokaryotic genomes studied, the DNA G+C content of the 20 genes was used to determine a ‘calculated’ genome DNA G+C content (CGC) and this value was compared with the ‘real’ genome DNA G+C content (RGC). In order to select the most suitable gene for the determination of CGC values, we compared the r 2 and median mol% difference between CGC and RGC as well as the sensitivity of each gene to provide CGC values for prokaryotic genomes that differ by less than 5 mol% from their RGC. The highly conserved ftsY gene (median size 1144 nucleotides), a vertically inherited member of the GTPase superfamily, showed the highest r 2 value of 0.98, the smallest median mol% difference between CGC and RGC of 1.06 and a sensitivity of 100 %. Using ftsY DNA G+C content values, the CGC values of 100 genomes not included in the calculation of r 2 differed by less than 5 mol% from their RGC values. These data suggest that the genomic DNA G+C content of prokaryotes may be estimated easily and reliably from the ftsY gene sequence.

PENGARUH, FASILITAS, MOTIVASI DAN DISIPLIN KERJA TERHADAP KINERJA KARYAWAN PADA PT ZEBRA ASABA INDUSTRI, JAKARTA BARAT

2018 ◽  
Vol 13 (1) ◽  
pp. 38-48
Author(s):  
Mudofar Mudofar
Keyword(s):  
Strong Correlation ◽  
Work Performance ◽  
Employee Performance ◽  
Coefficient Of Determination ◽  
Performance Variables ◽  
Relationship Of ◽  
Descriptive Method

The purpose of this study is to determine the effect of facilities, motivation, and workdiscipline on the work performance of PT Zebra Asaba Industrui employees. The research methodused is descriptive method with regression and correlation approaches which is a method that aims todescribe the influence and relationship of something that is going on at the time the research isconducted. The results of this study indicate partially or simultaneously facility variables,motivation, and work discipline have a significant effect on employee performance. The magnitude ofthe correlation value (R) is 0.924 which means that there is a strong correlation / relationshipbetween facilities, motivation, and work discipline with employee performance. The amount ofadjusted coefficient of determination (R2) is 0.793 or 79.3%, which means that independentvariables can explain changes in employee performance variables by 79.3% while the remaining20.7% is explained by other factors beyond this research.

scholarly journals Modeling Population Spatial-Temporal Distribution Using Taxis Origin and Destination Data

2021 ◽  
Vol 13 (7) ◽  
pp. 3727
Author(s):  
Fatema Rahimi ◽  
Abolghasem Sadeghi-Niaraki ◽  
Mostafa Ghodousi ◽  
Soo-Mi Choi
Keyword(s):  
Regression Analysis ◽  
Mean Squared Error ◽  
Population Distribution ◽  
Temporal Distribution ◽  
Coefficient Of Determination ◽  
Temporal Modeling ◽  
Location Data ◽  
Time Period ◽  
Proposed Model

During dangerous circumstances, knowledge about population distribution is essential for urban infrastructure architecture, policy-making, and urban planning with the best Spatial-temporal resolution. The spatial-temporal modeling of the population distribution of the case study was investigated in the present study. In this regard, the number of generated trips and absorbed trips using the taxis pick-up and drop-off location data was calculated first, and the census population was then allocated to each neighborhood. Finally, the Spatial-temporal distribution of the population was calculated using the developed model. In order to evaluate the model, a regression analysis between the census population and the predicted population for the time period between 21:00 to 23:00 was used. Based on the calculation of the number of generated and the absorbed trips, it showed a different spatial distribution for different hours in one day. The spatial pattern of the population distribution during the day was different from the population distribution during the night. The coefficient of determination of the regression analysis for the model (R2) was 0.9998, and the mean squared error was 10.78. The regression analysis showed that the model works well for the nighttime population at the neighborhood level, so the proposed model will be suitable for the day time population.

scholarly journals A Multimethod Analysis for Average Annual Precipitation Mapping in the Khorasan Razavi Province (Northeastern Iran)

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 592
Author(s):  
Mehdi Aalijahan ◽  
Azra Khosravichenar
Keyword(s):  
Regional Planning ◽  
Interpolation Method ◽  
Absolute Error ◽  
Rain Gauge ◽  
Annual Precipitation ◽  
Coefficient Of Determination ◽  
Distance Weighting ◽  
Average Annual Precipitation ◽  
Inverse Distance

The spatial distribution of precipitation is one of the most important climatic variables used in geographic and environmental studies. However, when there is a lack of full coverage of meteorological stations, precipitation estimations are necessary to interpolate precipitation for larger areas. The purpose of this research was to find the best interpolation method for precipitation mapping in the partly densely populated Khorasan Razavi province of northeastern Iran. To achieve this, we compared five methods by applying average precipitation data from 97 rain gauge stations in that province for a period of 20 years (1994–2014): Inverse Distance Weighting, Radial Basis Functions (Completely Regularized Spline, Spline with Tension, Multiquadric, Inverse Multiquadric, Thin Plate Spline), Kriging (Simple, Ordinary, Universal), Co-Kriging (Simple, Ordinary, Universal) with an auxiliary elevation parameter, and non-linear Regression. Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and the Coefficient of Determination (R2) were used to determine the best-performing method of precipitation interpolation. Our study shows that Ordinary Co-Kriging with an auxiliary elevation parameter was the best method for determining the distribution of annual precipitation for this region, showing the highest coefficient of determination of 0.46% between estimated and observed values. Therefore, the application of this method of precipitation mapping would form a mandatory base for regional planning and policy making in the arid to semi-arid Khorasan Razavi province during the future.

Real-Time PCR Determination of Escherichia coli Genomic DNA Contamination in Plasmid Preparations

2002 ◽  
Vol 301 (1) ◽  
pp. 151-153 ◽  
Author(s):  
Adrián Vilalta ◽  
Vanessa Whitlow ◽  
Terrie Martin
Keyword(s):  
Escherichia Coli ◽  
Real Time ◽  
Real Time Pcr ◽  
Genomic Dna ◽  
Dna Contamination

scholarly journals BAGET 2.0: an updated web tool for the effortless retrieval of prokaryotic gene context and sequence

2021 ◽  
Author(s):  
Benjamin Hepp ◽  
Violette Da Cunha ◽  
Florence Lorieux ◽  
Jacques Oberto
Keyword(s):  
Gene Sequence ◽  
Single Gene ◽  
Daily Basis ◽  
Web Tool ◽  
Web Based ◽  
Internet Explorer ◽  
Prokaryotic Genomes ◽  
Exploration Tool ◽  
Genome Browsers ◽  
Archaeal Gene

Abstract Motivation The retrieval of a single gene sequence and context from completely sequenced bacterial and archaeal genomes constitutes an intimidating task for the wet bench biologist. Existing web-based genome browsers are either too complex for routine use or only provide a subset of the available prokaryotic genomes. Results We have developed BAGET 2.0 (Bacterial and Archaeal Gene Exploration Tool), an updated web service granting access in just three mouse clicks to the sequence and synteny of any gene from completely sequenced bacteria and archaea. User-provided annotated genomes can be processed as well. BAGET 2.0 relies on a local database updated on a daily basis. Availability and implementation BAGET 2.0 befits all current browsers such as Chrome, Firefox, Edge, Opera and Safari. Internet Explorer 11 is supported. BAGET 2.0 is freely accessible at https://archaea.i2bc.paris-saclay.fr/baget/

Peran Faktor Pendorong Pada Keputusan Berkunjung Ke Kebun Raya Bogor

2021 ◽  
Vol 4 (1) ◽  
pp. 17
Author(s):  
Yuviani Kusumawardhani ◽  
Alma Alviana
Keyword(s):  
Correlation Coefficient ◽  
Significant Influence ◽  
Strong Correlation ◽  
Quantitative Research ◽  
Hypothesis Test ◽  
Botanical Garden ◽  
Coefficient Of Determination ◽  
Driving Factor ◽  
Motivating Factors ◽  
Botanical Gardens

<p>Bogor Botanical Garden is one of the icons of the Bogor City. Bogor Botanical Garden is a tourist site that has a forest concept but is located in the center of Bogor City so that access to Bogor Botanical Garden is easily accessible. Bogor Botanical Gardens is located in Ir. H. Juanda number 13, Bogor, West Java, Indonesia. This study was conducted to determine the effect of the Motivation Driving Factor on the Decision to Visit in Bogor Botanical Garden.</p><p>This research uses quantitative research, with descriptive methods. Many of the samples studied were 100 respondents who had visited Bogor Botanical Gardens.</p><p>Based on the results of the study it was concluded that from the results of the hypothesis test (T-Test) conducted by the researcher produced a tcount of 10.463&gt; Ttable 1.98447. This shows that there is a significant influence between the Motivating Factors for Visiting Decisions. The influence of motivating factors on the decision to visit Bogor Botanical Gardens with a strong correlation coefficient of 0.726 because it is between 0.600-0.799. The coefficient of determination or the percentage of influence of the Factors Driving Tourist Motivation (X) Decision to Visit (Y) is 52.8%. Meanwhile, the remaining 47.2% is influenced by other variables not examined in this research.</p>

Growth Pattern in Skeletal Class I Malocclusion: A Cephalometric Study

2021 ◽  
Vol 11 (1) ◽  
pp. 49-54
Author(s):  
Sujal Amatya ◽  
Rabindra Man Shrestha ◽  
Shristi Napit
Keyword(s):  
Growth Pattern ◽  
Strong Correlation ◽  
Class I ◽  
Facial Growth ◽  
Skeletal Class ◽  
Facial Height ◽  
Lateral Cephalograms ◽  
Growth Modification ◽  
Cephalometric Study

Introduction: Great emphasis has been given to the evaluation of sagittal apical base relationship in orthodontic diagnosis and treatment planning. The prediction of magnitude and direction of facial growth based on sagittal relationship will help in orthodontic treatment with growth modification. The objective of the study is to assess the growth pattern in skeletal Class I malocclusion. Materials and Method: 104 subjects (52 male and 52 female) with the age between 18-30 years with Class I skeletal relation was selected from lateral cephalograms of patients visiting the Department of Orthodontics, Kantipur Dental College. The ANB angle was measured to assess the sagittal jaw relationship and the Jarabak’s ratio to access the growth pattern. Descriptive statistics were calculated for each parameter. Pearson’s test was done to evaluate the correlation between the parameters. Independent t-test was done to compare Anterior Facial height (AFH), Posterior Facial Height (PFH) and Jarabak’s ratio between male and female subjects. Result: Among the total subjects with skeletal Class I malocclusion; hyperdivergent growth pattern was least (10.57%), followed by normodivergent (18.26%) and hypodivergent growth pattern (71.15%). Mean Jarabak’s ratio for hyperdivergent, normodivergent and hypodivergent growth pattern were 58.65±1.94, 63.98±0.85 and 69.98±4.13 respectively. Very strong correlation was found between AFH and PFH in hyperdivergent (r = 0.821) and normodivergent group (r =0.978). Strong correlation was found in hypodivergent group between AFH and PFH (r =0.743). Also, strong correlation was found in hypodivergent group between PFH and Jarabak’s ratio (r =0.643). Conclusion: Hypodivergent growth pattern was the dominant growth pattern in skeletal Class I malocclusion. PFH influenced the determination of Jarabak’s ratio more than the AFH in hypodivergent growth pattern. Hypodivergent growth pattern is correlated with large SNB angle.

scholarly journals A NON-DESTRUCTIVE METHOD FOR ESTIMATING LEAF AREA OF Ceiba glaziovii (Kuntze) K. Schum.

FLORESTA ◽  
2019 ◽  
Vol 50 (1) ◽  
pp. 1063
Author(s):  
João Everthon da Silva Ribeiro ◽  
Francisco Romário Andrade Figueiredo ◽  
Ester Dos Santos Coêlho ◽  
Walter Esfrain Pereira ◽  
Manoel Bandeira de Albuquerque
Keyword(s):  
Leaf Area ◽  
Regression Models ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Linear Measurements ◽  
Maximum Width ◽  
Bias Index ◽  
Different Shapes ◽  
Non Destructive

The determination of leaf area is of fundamental importance in studies involving ecological and ecophysiological aspects of forest species. The objective of this research was to adjust an equation to determine the leaf area of Ceiba glaziovii as a function of linear measurements of leaves. Six hundred healthy leaf limbs were collected in different matrices, with different shapes and sizes, in the Mata do Pau-Ferro State Park, Areia, Paraíba state, Northeast Brazil. The maximum length (L), maximum width (W), product between length and width (L.W), and leaf area of the leaf limbs were calculated. The regression models used to construct equations were: linear, linear without intercept, quadratic, cubic, power and exponential. The criteria for choosing the best equation were based on the coefficient of determination (R²), Akaike information criterion (AIC), root mean square error (RMSE), Willmott concordance index (d) and BIAS index. All the proposed equations satisfactorily estimate the leaf area of C. glaziovii, due to their high determination coefficients (R² ≥ 0.851). The linear model without intercept, using the product between length and width (L.W), presented the best criteria to estimate the leaf area of the species, using the equation 0.4549*LW.

scholarly journals The Effect of Financial Leverage, Operating Leverage and Current Ratio on Profitability at PT. Manunggal Persada Jakarta

2019 ◽  
Vol 3 (2) ◽  
pp. 135
Author(s):  
Waluyo Jati
Keyword(s):  
Hypothesis Testing ◽  
Regression Coefficient ◽  
Sampling Technique ◽  
Coefficient Of Determination ◽  
Analysis Tool ◽  
Financial Leverage ◽  
Current Ratio ◽  
Independent Variable ◽  
Operating Leverage

Funds can be obtained from company owners or from outside parties. The purpose of this study was to determine the effect of financial leverage, operating leverage and current ratio on profitability at PT. Manunggal Persada Jakarta. The method used in this research is descriptive with an associative approach, the sampling technique used is proportional random sampling using the census or saturated sampling method with a sample of 7 years of financial statements. The analysis tool uses classical assumption testing, regression testing, determination coefficient testing and hypothesis testing. The results of the study concluded that the regression coefficient value of Financial leverage of 0.005 was positive with a contribution of 19.3%. Hypothesis testing obtained a significance value of 0.324> 0.05. Regression coefficient value of Operating leverage of 0.001 is positive with a contribution of 16.5%. Hypothesis testing obtained a significance value of 0.368> 0.05. Current coefficient regression value of 0.158 is positive with a contribution of 31.9%. Hypothesis testing obtained a significance value of 0.187> 0.05. Obtained a regression equation Y = 0.110 + 0.009X1 + 0.001X2 + 0.177X3, the regression coefficient value of each positive independent variable with a correlation of 0.927 and a coefficient of determination of 85.8% while the remaining 14.2% is influenced by other factors. Hypothesis testing obtained by calculating Fcount> Ftable or (6.064> 4.120). Thus simultaneously there is a positive and significant effect between financial leverage, operating leverage and current ratio to rentability.

scholarly journals The Influence Of International Brand Image Toward Guest's Decision To Stay At The Four Star Hotel In Lampung

2021 ◽  
Vol 4 (1) ◽  
pp. 38
Author(s):  
Dina Mayasari Soewoyo ◽  
Handono W Widodo
Keyword(s):  
Brand Image ◽  
Linear Regression Analysis ◽  
Software Tool ◽  
Primary Data ◽  
Coefficient Of Determination ◽  
Analysis Technique ◽  
Independent Variable ◽  
Decision To Stay ◽  
Decisions To Stay

<div class="WordSection1"><p>This survey research using the quantitative method was carried out during the Covid-19 pandemic, from May to August 2020 at the 4-star hotel in Lampung Province, Indonesia. The purpose of this study was to determine the influence of the independent variable, namely the image of the international hotel brand toward the dependent variable of guests' decisions to stay at the hotel. Primary data of the study were obtained from the results of distributing questionnaires which were carried out directly to 60 guests who were staying, as research samples and measured using a Likert scale of 1 - 4. Apart from distributing questionnaires, research data collection was also gained through observation, documentation, and literature review. All data collected were then grouped, reduced, tabulated and processed, analyzed descriptively, and statistically, in accordance with the context of the problem being studied using the SPSS 22.0 software tool.</p><p>Based on the simple linear regression analysis technique T-test (partial), R test and R square test, it was found that the value of T count (9,048) was greater than the T table (1,671), with a significance value of 0 or below the significance limit of 0.05. Both variables have a correlation coefficient of 0.765 and a coefficient of determination of 0.585. So it can be concluded that the international hotel brand image has a strong, positive, and significant influence on guest decisions to stay at the 4-star hotel in Lampung, with an effect of 58.5% while the rest, namely 41.5%, is influenced by other variables not examined in this study.</p></div><br clear="all" /><p><em> </em></p>

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