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
Foundations of Bioinformatics: Explore genomic bioinformatics, databases, and tools like GenBank and PubMed, bridging biotechnology with bioinformatics.
Next Generation Sequencing (NGS): Understand bioinformatics' role in NGS, covering techniques, applications, and Linux basics, including cloud technology.
Python and Biopython: Master Python essentials tailored for bioinformatics, with a focus on data manipulation and Biopython for biological sequence analysis.
R Programming and Bioconductor: Learn R programming and Bioconductor for statistical analysis and visualization in bioinformatics, enhancing research proficiency.
RNA and DNA Sequencing Analysis: Acquire practical skills in RNA and DNA Seq data analysis, including variant detection, annotation, and pathway analysis.
Microarray and Metagenome Analysis: Gain expertise in microarray technology, metagenome analysis, and pathway network analysis using advanced tools.
HR Session: Develop soft skills and prepare for career advancement through HR sessions covering resume building, interview skills, and professional networking.
Research Project and Paper Publication: Apply acquired skills in a two-month NGS research project, leading to paper publication, and enhancing practical proficiency.
Course Outcomes
Gain a comprehensive understanding of bioinformatics fundamentals and their applications in biotechnology research.
Master NGS techniques and platforms, coupled with programming skills in Python and R for efficient data analysis.
Acquire expertise in utilizing Bioconductor for sequence analysis and visualization, enhancing research proficiency.
Develop practical skills in RNA and DNA Seq data analysis, including variant detection and pathway analysis.
Enhance proficiency in microarray and metagenome analysis, leading to advanced research capabilities.
Apply acquired skills in a two-month NGS research project, leading to paper publication, and prepare for advanced studies and careers in life sciences.
Develop a strong understanding of Bioinformatics & NGS basics, Linux, Cloud Computing, Python, and R for NGS applications.
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.
