Syllabus

Module 1: Introduction to Omics Technologies
Overview and general principles of omics technologies in biotechnology, Omics approaches: Genomics, Proteomics, Transcriptomics and Metabolomics, Meta-omics (genomics, proteomics, transcriptomics, metabolomics) and Functional omics
Module 2: Applications of Omics in Biotechnology
Application of Omics in different fields of biotechnology including agriculture, environment, pharmaceuticals, medicine, forensic, discovery of novel organisms, enzymes, value added products etc.,
Module 3: Genomics and Genomic Technologies
Genomics, covering DNA sequencing technologies (e.g., DNA-sequencing, Genome Sequencing, Next Generation Sequencing (NGS), gene expression microarray), genome annotation, and computational tools for data analysis.
Module 4: Proteomics, Transcriptomics and Metabolomics
Tools for Proteomics techniques like mass spectrometry, protein separation methods (e.g., SDS-PAGE, 2D-PAGE). The Transcriptomics techniques including RNA-Seq, gene expression microarrays, and the role of regulatory RNAs like miRNAs and lncRNAs. The Metabolomics techniques covers NMR, mass spectrometry, and GC.
Module 5: Meta-Omics and Functional Omics
Basics of Meta-Omics, which integrates multiple Omics data for a holistic understanding of biological systems, and Functional Omics, which helps discover novel organisms, enzymes, and bio-products.
Module 7: Computational Tools for Omics Data Analysis
Computational Tools for Omics data analysis, including bioinformatics platforms, data integration techniques, and machine learning for predictive modeling. Designing of Omics-based research, covering data collection, analysis, and ethical considerations.

1. To understand the general principles and methodologies of omics technologies (genomics, proteomics, transcriptomics, and metabolomics).

2. To gain knowledge about the applications of omics in biotechnology across various sectors (agriculture, environment, pharmaceuticals, medicine, forensics).

3. To analyze omics data through computational approaches, including data integration, big data handling, and genome annotation.

4. To understand the significance of meta-omics and functional omics in the discovery of novel organisms, enzymes, and value-added products for biotechnology-driven industries.

Upon completion of this course, students will be able to:
1. Explain the principles and strategies behind genomics, proteomics, transcriptomics, and metabolomics technologies.
2. Demonstrate the ability to conduct basic experiments using various omics tools (e.g., DNA sequencing, RNA-Seq, Mass Spectrometry).
3. Integrate various omics data (genomics, proteomics, transcriptomics, metabolomics) to make biological discoveries and predictions.
4. Apply omics technologies to solve real-world problems in biotechnology sectors like agriculture, pharmaceuticals, medicine, and forensics.
5. Design omics-based research projects to discover novel organisms, enzymes, and valuable bio-products.

DebmalyaBarh Vasco Azevedo, Omics Technologies and Bio-engineering, 1st Edition, Volume 1: Towards Improving Quality of Life, Academic Press

Wittmann, C. and Lee, S.Y. eds, Systems metabolic engineering, Springer Science & Business Media

Barh, D., Zambare, V. and Azevedo, V. eds, Omics: applications in biomedical, agricultural, and environmental sciences, CRC Press

Kihara, D. ed, Protein function prediction for omics era, Springer Science & Business Media

Journal of Proteome Research

Nature Biotechnology