A big welcome to “Bioinformatics: Introduction and Methods” from Institute for Applied Research and Training (IART)! In this course, you will become familiar with the concepts and computational methods in the exciting interdisciplinary field of bioinformatics and their applications in biology, the knowledge and skills in bioinformatics you acquired will help you in your future study and research.
Course Duration: 1 Month, There are 3 modules in this course
Eligibility:- Under Graduate, Graduate and Post Graduate
Mode of Instruction: English and Hindi
Module 1: Course Duration: 1 Month
Chapter 1: Introduction: A brief Introduction and history of bioinformatics.
Chapter 2: Aim, Scope and Research areas of Bioinformatics
Chapter 3: Databases in Bioinformatics: Introduction, A tour to Biological Databases such as National Center for Biotechnology Information (NCBI), Ensembl, Entrez Molecular Sequence Database, EMBL Nucleotide Sequence Database (EMBL-Bank), DNA Data Bank of Japan (DDBJ), RCSB PDB, Swiss-Prot etc; Available Resources and Data Submission at molecular databases
Chapter 4: Biological Database Retrieval System (DNA, mRNA and Protein Sequence retrieval)
Chapter 5: Sequence Alignments: Introduction, Concept of Alignment, Sequence alignment using Basic local alignment search tool (Blast), Multiple Sequence Alignment (MSA) by CLUSTALW, Scoring Matrices, Percent Accepted Mutation (PAM), Blocks of Amino Acid Substitution Matrix (BLOSUM).
Chapter 6: Molecular Phylogeny: Methods of Phylogeny, Software for Phylogenetic Analyses, Consistency of Molecular Phylogenetic Prediction
Chapter 7: Primer designing using tools such as primer blast and primer3
Module 2: Advanced (Transcriptome analysis), Course duration: 1 Month
Chapter 1: Introduction of RNA seq and required tools
Chapter 2: Mapping sequencing reads to a reference genome or transcriptome (HISAT2, TopHat Tuxedo pipeline)
Chapter 3: Quantifying expression levels of individual genes and transcripts (Featurecount,Cuffdiff)
Chapter 4: Identifying specific genes and transcripts that are differentially expressed between samples (edgeR, limma-voom, DESeq2)
Chapter 5: Ontology and identification of molecular pathways (iDEP, DAVID, GSEA)
Chapter 6: Enriched gene and pathway network analysis (Cytoscape, String etc)
Module 3: Advanced (Structural bioinformatics), Course duration: 1 Month
Chapter 1: Introduction to structural bioinformatics
Chapter 2: Structural databases and their role
Chapter 3: Data retrieval from structural database
Chapter 4: Structure visualization and manipulation using PYMOL and UCSF Chimera and discovery studio
Chapter 5: Introduction and hands on session on protein-ligand docking for interaction pattern analysis using auto dock vina
Chapter 6: Introduction to MD Simulation
Applications and Job Opportunities:
Applications:
- Research: This course provides a strong foundation for pursuing research in various fields like genomics, proteomics, systems biology, and drug discovery.
- Biotech Industry: The skills gained are relevant to roles in pharmaceutical companies, biotechnology firms, and diagnostic labs.
- Academia: Graduates can work as research assistants or instructors in universities and colleges.
- Data Science: The knowledge of bioinformatics tools and databases can be applied to data science jobs in the healthcare and life sciences sectors.
Job Opportunities :
- Bioinformatics Analyst: Analyze biological data, develop algorithms, and create databases.
- Computational Genomics Researcher: Research the function and evolution of genes using computational methods.
- Structural Biologist: Study the structure and function of proteins and other molecules.
- RNA-Seq Analyst: Analyze RNA sequencing data to understand gene expression patterns.
- Drug Discovery Scientist: Utilize bioinformatics tools to identify and develop new drugs.
Additional :
- The course’s focus on advanced topics like transcriptome and structural bioinformatics makes it attractive to employers seeking specialized talent.
- The practical hands-on sessions with software tools like BLAST, ClustalW, and PyMOL will be valuable for job applications.
- Pursuing a Master’s thesis project can further enhance your skills and research experience.
Note: Thesis work/projects are also available for Master's students and can be customized according to requirements.
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