One of the main attractions of using the R (http://cran.at.r-project.org) environment is the ease with which users can write their own programs and custom functions. The R programming syntax is extremely easy to learn, even for users with no previous programming experience. Once the basic R programming control structures are understood, users can use the R language as a powerful environment to perform complex custom analyses of almost any type of data.

Aim

The “R Programming for Data Analytics in Bioinformatics” workshop aims to equip participants with the essential skills to harness the power of R for data analysis, visualization, and statistical modeling. This 3-day workshop is designed to provide hands-on experience with R, enabling participants to transform raw data into actionable insights.

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Workshop Objectives

To create vectors and matrices and perform simple operations on them.
To extract relevant information and incorporating into data file.
To perform statistical analysis and visualization of given data set.

Workshop Structure

Day 1: Introduction to R and R Studio, Vector and Matrices

Vector and matrices, importing data into R, Sub setting data, and logistics statement
Setting up the working directory, Producing numeric summaries for categorical and numeric variables

Day 2: R packages and Statistical Analysis

Working on dplyr, Amelia, gmodels R packages.
Basics Statistical Analysis with R

Day 3: Data Visualization and prediction model

Data Visualization with ggplot2
Insulin prediction model

Participant’s Eligibility

Undergraduate degree in Bioinformatics, Biology, Biotechnology or related fields.
Professionals in data-driven industries such as, healthcare, or marketing.
Individuals with a keen interest in data analysis and statistical computing

Important Dates

Registration Ends

2024-09-24
Indian Standard Timing 7:00 PM

Workshop Dates

2024-09-24 to 2024-09-26
Indian Standard Timing 8:00 PM

Workshop Outcomes

Proficiency in R programming and data manipulation.
Ability to conduct statistical analysis and hypothesis testing.
Competence in creating and interpreting data visualizations.
Knowledge of predictive modeling techniques.
Hands-on experience with real-world data analytics projects.

Mentor Profile

Fee Structure

Student

INR. 999
USD. 30

Ph.D. Scholar / Researcher

INR. 1199
USD. 35

Academician / Faculty

INR. 1399
USD. 50

Industry Professional

INR. 1699
USD. 75

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