OmicsLogic Program at the Institute of Genetic Engineering (IGE)
The OmicsLogic programs were designed to quickly introduce complex bioinformatics topics and relevant research projects to help develop understanding while avoiding the complexities of coding. The topics are explored in a project setting that combines insight into the typical problems addressed by a bioinformatician and exposure to the analysis logic, highlighted by our unique online research and learning environment, the T-BioInfo platform
Upcoming Events
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03September
Induction to OmicsLogic
Introduction to OmicsLogic Program at the Institute of Genetic Engineering (IGE) Mohit Mazumder & Pratim Chakraborty, Sep 3, 2019 Workshop I Introduction and commencement...
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03September
Introduction to OmicsLogic Program
ntroduction to OmicsLogic Program at the Institute of Genetic Engineering (IGE) Mohit Mazumder & Pratim Chakraborty, Sep 3, 2019 Workshop I Introduction and commencement...
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03September
Introduction to OmicsLogic Program
Introduction to OmicsLogic Program at the Institute of Genetic Engineering (IGE) Mohit Mazumder & Pratim Chakraborty, Sep 3, 2019 Workshop I Introduction and commencement...
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06September
Introduction to Big Data Bioinformatics
Introduction to multi-omics (Definitions) Knowledge-Driven vs. Data-Driven Discovery and Examples Applications of Bioinformatics in Agriculture, Neuroscience, Cancer Biology, Immunology, Defense and Healthcare
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10September
Introduction to Genomics
Cell, Nucleus and Chromosomes The DNA molecule and its structure Genome variations: A detailed understanding Targeted Sequencing, Whole Exome Sequencing and Whole Genome Sequencing...
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17September
Next Generation Sequencing: Transcriptomics
Processing Raw NGS Data (read mapping and quantification) Analysis (differential gene expression, factor regression analysis) Interpretation (Gene Ontologies and Gene Set Enrichment Analysis)
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24September
Transcriptomics 2
Filtering, removing noise and Normalization Techniques Exploring multi-dimensional data using PCA visualization Principal Components and variance – outliers, filtering, normalization
