Dr. Omics Education;

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Course Requirements

Motivation to Learn: A strong desire to engage with and understand the material.
Basic Knowledge: Familiarity with biology and molecular biology concepts.
Interest in Technology: Eagerness to learn about the latest technologies in Next-Generation Sequencing (NGS).
Software: Free software will be utilized, so no additional software purchases are necessary.
Hardware: A laptop with a minimum of 4GB RAM and 100GB of hard disk space.

Course Description

Comprehensive Introduction to Bioinformatics: Explore foundational bioinformatics databases like NCBI GenBank, UCSC Genome Browser, and PubMed for biomedical research.
Linux for Bioinformatics: Master Linux basics, command-line tools, and installation of bioinformatics tools for seamless data processing and analysis.
Python Programming for Bioinformatics: Develop skills in Python, Biopython, and file handling to analyze and organize biological data effectively.
R Programming for Data Analysis: Learn data visualization, statistical analysis, and biological data management using R programming.
NGS Data Analysis: Dive into the entire NGS workflow, including DNAseq and RNAseq analysis, variant calling, annotation, and visualization using tools like GATK and IGV.
Hands-On Practice with Mini Project: Apply learned skills in a real-world scenario through a practical genomics mini-project, focusing on RNAseq analysis and pathway enrichment.

Course Outcomes

Bioinformatics Database Proficiency: Gain expertise in navigating and utilizing key bioinformatics databases and tools for research applications.
Linux and Tool Deployment: Effectively use Linux commands and install tools critical for bioinformatics workflows.
Programming Mastery: Analyze and process biological data using Python and R, leveraging their libraries and statistical capabilities.
NGS Workflow Expertise: Perform end-to-end NGS analyses, including quality control, alignment, variation calling, and functional analysis.
Advanced Visualization Skills: Utilize tools like IGV and statistical techniques in R for data visualization and interpretation.
Practical Application: Solve real-world bioinformatics problems by implementing a mini-project that integrates learned techniques and tools.

Rules & Regulations

Attendance and Participation: Maintain a minimum of 75% attendance. Regular assessments and attendance contribute to performance evaluation.
Discipline: Maintain punctuality and respect in live classes. Engage actively and interact respectfully with instructors and peers.
Course Fee Payment: Pay course fees on time to avoid suspension or cancellation of access.
Assignments and Project: Complete assignments and projects sincerely and submit them on time.
Feedback and Communication: Maintain open communication with instructors and provide constructive feedback.
Certification: A certificate will be awarded upon course completion.

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