Mastering Knowledge:
Expert-Guided, Live Session Mentorship
Basic Information
Bioinformatics data analysis and pipeline development
Cohort-based Course
Explore the intersection of biology and data science in our Bioinformatics course. Master the art of analyzing Next-generation sequencing data (RNA-seq) and developing pipelines to solve complex biological problems efficiently. The rapid advancement of high-throughput technologies has revolutionized biomedical research, necessitating scalable and reproducible methods for both experiments and computational analysis due to the growing volume and complexity of data. Transforming this data into useful information requires numerous tools, parameter optimization, and integration of evolving reference data. To address these challenges, workflow managers were created. These tools streamline pipeline development, optimize resource usage, manage software installations and versions, and ensure workflows can run across various computing platforms, promoting portability and sharing.
In this course, you will learn how to develop.
No prior knowledge is required. Learn through practice.
- Bioinformatics data files, structured and unstructured files
- Bioinformatics tools
- How to leverage workflow management tools to develop a reproducible, scalable, and scalable RNA-seq data analysis pipeline
- Programming languages: R and Python, and Shell
- Perform your custom analysis pipelines
Module 1: Introduction to shell
This module introduces students to the fundamental concepts of Unix shell scripting, tailored for those analyzing data in a scientific setting. Module 1 begins with an overview of shell scripts, file management, directories, and the processes of editing, viewing, and concatenating files. It also covers how to connect to servers using the terminal.
Module 2: Hands-on Python environment
This module will enable students to configure the environment for core software used in the pipeline management tool, with a primary focus on understanding the bioinformatics tools for the canonical RNA-seq data analysis pipeline and setting up environmental dependencies.
Module 3: Introduction to Bioinformatics tools for RNA-seq data analysis
Students will learn how to handle different types of RNA-seq data, including structured and unstructured data, and how to use Bioinformatics tools.
Module 4: Advanced bioinformatics pipeline development
The final module will delve deep into the development of the pipeline. Topics covered will include how to process the raw fastq files, trim them, quality check, map the reads, obtain raw read counts, and finally normalize the read counts. Besides that, students will learn to write Python and R scripts for data analysis and visualization. Finally, share the pipeline with an online code repository.
Instructors Information
Hosted By
Alva James
PhD in Molecular medicine (curriculum bioinformatics and biostatistics) oncology and cancer biology
Course Overview
Course overview
Bioinformatics Data Analysis & Pipeline Dev.
Explore bioinformatics, analyzing genetic data and creating pipelines for groundbreaking insights in biology. Transform big data into discovery.
02
Bioinformatics students
03
Software developers in the life sciences sector
01
Biomedical researchers
02
Bioinformatics students
03
Software developers in the life sciences sector
01
Biomedical researchers
02
Bioinformatics students
prev
next
Course Benefits
Bioinformatics: Data & Pipelines
Comprehensive Understanding of Bioinformatics Tools and Techniques
Gain a deep understanding of the various bioinformatics software, databases, and tools critical for analyzing biological data.
Skills in Pipeline Development
Learn to design and implement bioinformatics pipelines, enabling the automation of data analysis for more efficient research workflows.
Enhanced Data Analysis Capabilities
Master the ability to process, analyze, and interpret large datasets, a skill highly valued in the fields of genomics, proteomics, and beyond.
Critical Thinking and Problem-Solving
Develop strong problem-solving skills by tackling real-world bioinformatics challenges, enhancing your ability to innovate and think critically in research.
Employability and Career Advancement
Improve your prospects for employment and career advancement within academia, pharmaceuticals, biotechnology, and other sectors increasingly reliant on bioinformatics expertise.
Course modules
Course modules
01
Introduction to Bioinformatics and Data Analysis
This module provides an overview of the fundamental concepts in bioinformatics, including data types, databases, and the importance of bioinformatics in modern biology. Students will learn about sequence analysis, structure prediction, and the basics of genetic variation analysis.
02
Bioinformatics Tools and Software
In this module, students will be introduced to essential bioinformatics software, tools, and resources. Emphasis will be placed on the use of open-source tools for sequence alignment, genome assembly, and annotation. Practical sessions will include hands-on exercises to familiarize students with command-line tools and graphical user interfaces.
03
Pipeline Development for High-throughput Data
This module focuses on the development and implementation of bioinformatics pipelines for processing large-scale genomic data. Students will learn about workflow management systems, data integration, and automation techniques. Case studies will be used to illustrate the design and optimization of pipelines for various types of bioinformatic analyses.
This course includes
3 modules
Applying knowledge through projects
Exclusive community of fellow members
Access to course materials for a lifetime
Immediate access to the instructor
Feedback and reflection with guidance
Learning is way better with live cohorts
Engaging in learning becomes immensely enriching when accompanied by live cohorts, fostering dynamic interactions and shared insights.
The educational experience reaches new heights when learning is undertaken within live cohorts, creating a vibrant and supportive community for knowledge exchange.
Discover the unparalleled benefits of collaborative learning as live cohorts elevate the educational journey, providing real-time engagement and a sense of camaraderie.
Next generation sequencing (NGS) data analysis and pipeline development
Subscribe to be the first to know about the next cohort
