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My research focuses on the intersection of genetics, genomics, and plant pathology, specifically emphasising plant-pathogen interactions within the Brassica napus-Leptosphaeria maculans and B. napus-Verticillium longisporum pathosystems. I employ a multidisciplinary approach, combining my expertise in plant pathology with advanced bioinformatics and computational biology techniques. One of my work's key aspects involves identifying and diagnosing fungal pathogens affecting plant materials in field and laboratory settings. By leveraging my extensive plant pathology knowledge and cutting-edge molecular techniques, I contribute to developing, analysing, and visualising genomic data related to these plant-pathogen interactions. This profile provides Basic to Pro Python, R and SAS codes with plant genetics, genomics and agricultural-based examples and Statistical, Artificial Intelligence and Machine Learning programming.

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Aria Dolatabadian's Projects

mauve-alignment-with-genoplotr icon mauve-alignment-with-genoplotr

Mauve is a system for constructing multiple genome alignments in the presence of large-scale evolutionary events such as rearrangement and inversion.

model-generalization-on-unseen-data icon model-generalization-on-unseen-data

With go.Scatter, you can easily color your plot based on a predefined data split. By coloring the training and the testing data points with different colors, you can easily see if whether the model generalizes well to the test data or not.

mothur- icon mothur-

Mothur is an open source software package for bioinformatics data processing.

multiple-linear-regression icon multiple-linear-regression

Multiple linear regression is a regression model that estimates the relationship between a quantitative dependent variable and two or more independent variables using a straight line.

multivariate-analysis-using-r icon multivariate-analysis-using-r

Multivariate analysis is defined as: The statistical study of data where multiple measurements are made on each experimental unit and where the relationships among multivariate measurements and their structure are important.

network icon network

Network graph (force directed graph) is a mathematical structure (graph) to show relations between points in an aesthetically-pleasing way.

non-parametric-statistical-test-in-python icon non-parametric-statistical-test-in-python

The Mann-Whitney U test, also known as the Wilcoxon rank-sum test, is a non-parametric statistical test used to determine if there is a significant difference between two independent groups. It is used when the data does not meet the assumptions of normality or when comparing ordinal or ranked data.

ordinary-least-square-ols-with-plotly.express icon ordinary-least-square-ols-with-plotly.express

This example shows how to use plotly.express's trendline parameter to train a simply Ordinary Least Square (OLS) for predicting the tips waiters will receive based on the value of the total bill.

orthogonal-design icon orthogonal-design

In experimental design, an orthogonal design refers to a design where the factors or variables being investigated are independent or orthogonal to each other. In other words, the levels of one factor do not systematically influence or interact with the levels of another factor.

pair-plot-using-seaborn icon pair-plot-using-seaborn

Pair plot is used to understand the best set of features to explain a relationship between two variables or to form the most separated clusters. It also helps to form some simple classification models by drawing some simple lines or make linear separation in our data-set.

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