About this course
This is a Super 30 Bioinformatics Batch offering a 6-month comprehensive training program certified by LSSSDC (Life Sciences Sector Skill Development Council), Government of India. The course provides 28 credits, includes third-party examination, and offers 100% job placement assistance with exclusive interview opportunities. Participants receive research guidance and publication support, hands-on training with a practical approach, and live interaction with industry experts.
What you will learn
Practical Bioinformatics Skills: Hands-on experience in bioinformatics tools and techniques for real-world applications
Sequence Analysis Proficiency: Techniques for sequence alignment, genomics, and proteomics using BLAST and ClustalW
Data Management and Retrieval: Navigating, importing, and managing data from bioinformatics databases (GenBank, PDB, UCSC)
Programming Skills: Proficiency in Python, R, and Linux for bioinformatics applications
Algorithm and Data Structure Knowledge: Essential algorithms and data structures for bioinformatics
Machine Learning and AI: Applying ML techniques to bioinformatics data analysis
Research Publication Guidance: Conducting research and publishing findings in reputable journals
Career Readiness: 100% placement assistance with career counseling and interview preparation
Industry Certification: Government-recognized certificate validating bioinformatics proficiency
Networking Opportunities: Connecting with industry professionals and staying updated on bioinformatics trends
Skills you will gain
Bioinformatics Analysis
Next-Generation Sequencing (NGS)
Python Programming
R Programming
Linux Command Line
Sequence Analysis
Variant Calling
RNAseq Analysis
Microarray Analysis
Metagenomics
Machine Learning
Statistical Analysis
Database Management (NCBI
PDB)
BLAST
Algorithm Development
Cloud Computing (AWS)
SQL Database Management
Cheminformatics
Molecular Docking
Research Publication
Scientific Writing
Data Visualization
Certification
Yes, this course provides LSSSDC (Life Sciences Sector Skill Development Council) Government of India Certification with 28 credits.
Issued by LSSSDC
Course curriculum
20 modules
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Introduction to Bioinformatics and its Applications in Life Sciences
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Types of sequencing and introduction to NGS
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Introduction to NGS applications
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Introduction and overview of Bioinformatics & NCBI Gene Database Exploration
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NCBI Gene Database Exploration
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UCSC Genome Browser: Overview and Hands-on Exercises
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Introduction to PubMed Database
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KEGG Database: Overview and Practical Exercises
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Overview of Expasy server
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Protein Databases (PDB): Overview and Practical Exercises
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ClinVar & OMIM database
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GWAS catalog database
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Introduction to Ensembl Database
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Introduction to Online BLAST with Practical Exercises
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Setting Up Standalone BLAST and Hands-on Exercises
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Advanced Standalone BLAST Applications and Exercises
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Multiple Sequence Alignment Using CLUSTALW
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Multiple Sequence Alignment Using MEGA
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Introduction to Linux: Overview and Installation
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Essential Linux Commands for Beginners to Advanced Linux Commands
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Managing Packages in Linux (repositories, source code and conda enviroment)
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Bash Scripting: Variables, Conditionals & Loops
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Bash Scripting, AWK and SED
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Installation and Environment Setup
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Data Types in Bioinformatics Computing
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String Handling for DNA and Protein Sequences
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Efficient Data Structures for Biological Data
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Control Structures for Genome Data Processing
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Functions for Automating Bioinformatics Tasks
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Importing, Exporting, and Handling Biological Files
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Data Manipulation for Sequence and Expression Analysis
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Visualization of Genomic and Proteomic Data
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Biopython for Sequence and Structural Analysis
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Getting Started with R for Bioinformatics
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Understanding Data Types in R
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Efficient Data Structures for Genomic Data
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Importing, Exporting, and Handling Biological Data
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Control Structures for Data Processing in R
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Functions for Automating Bioinformatics Workflows
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Managing and Utilizing R Packages for Analysis
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Sequence Analysis with Bioconductor
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Data Manipulation for Genomic and Expression Data
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Visualizing Biological Data with R-1 (Basic plots, PCA plot, Venn diagram)
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Visualizing Biological Data with R-2(Heatmap, volcano plot, MA plot)
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Introduction to NGS and DNAseq
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Basic Terminologies in NGS
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Understanding of SRA database
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Installing Tools in Linux for Variant Calling
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Quality Control of Reads
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Trimming and Filtering Reads
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Genome Indexing and Read Alignment
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Variation calling using GATK
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Predicting Variant Effects
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Variation Visualization (IGV)
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Docker installation
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DNAseq pipeline in docker -1
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DNAseq pipeline in docker -2
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DNAseq pipeline in docker -3
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DNAseq pipeline in docker -4
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Introduction to RNA-seq and Key Terminologies
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Setting Up Tools in Linux for Gene Expression Analysis
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Quality Control and Read Trimming
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Genome Indexing and Read Alignment using Hisat2 & salmon
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Data Normalization Using Cufflinks and featurecounts
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Merging Data and Identifying Differentially Expressed Genes using deseq2
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Interpretation of DEG Results
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Annotation of Differentially Expressed Genes using DAVID
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Functional and Pathway Enrichment Analysis using shinyGO ,clusterProfiler & Enrichr
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Network Analysis of gene interaction using stringDB
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Network editing using cytoscape
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Setting Up Tools for De Novo RNA-seq(Trinity)
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Setting Up Tools for De Novo RNA-seq(RSEM/edgeR/Assembly-stats)
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Data Downloading and Quality Control
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Transcriptome Assembly creation
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Estimating Abundance Counts
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Generating Count Matrix and Identifying DEGs
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Performing BLAST Analysis
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Interpretation of DEG Results
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Annotation of Differentially Expressed Genes
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Enrichment Analysis of DEGs
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Introduction to Metagenomics Analysis
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Setting Up Tools for Metagenomics
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Data Downloading and Preprocessing
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Quality Control and Read Trimming
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Importing Data into QIIME2
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Quality Assessment Using DADA2
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Phylogenetic Diversity Analysis of Microbial Communities
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Taxonomic Classification of Sequences
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Visualization with Krona Plot
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Phylogenetic tree construction using MEGA
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Introduction to Microarray Technology- Part1
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Introduction to Microarray Technology-Part2
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Data Downloading and Preprocessing
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Microarray Processing Pipeline up to Normalization
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Differential Gene Expression Analysis in Microarray
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Annotation of Differentially Expressed Genes
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Enrichment Analysis of DEGs
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Network Analysis of Gene Interactions
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Visualization with Volcano Plot
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Heatmap Generation for DEG Representation
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Fundamentals of Machine Learning for Genomic Data
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Linear Models and Nearest Neighbors for Pattern Recognition
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Probabilistic Machine Learning Concepts and Applications
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Support Vector Machines SVM Theory and Implementation
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Naïve Bayes Classifier Fundamentals and Bioinformatics Use Cases
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Decision Trees and Random Forest Interpretable ML Models
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Logistic Regression for Predictive Analysis in Bioinformatics
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Clustering Algorithms for Unsupervised Learning
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Validation Techniques for Machine Learning Models
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Machine Learning for Biomedical Image Analysis
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Introduction to Statistical Methods for Bioinformatics
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Descriptive Statistics and Data Structures
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Correlation and Regression Analysis for Genomic Data
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Probability and Bayes Theorem in Bioinformatics
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Sampling Techniques and Distribution Theory
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Hypothesis Testing for Data Analysis
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Statistical Tools for Data Management, Analysis, and Visualization
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Inferential Statistics for Biological Data Interpretation
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Interpreting Statistical Outputs for Decision Making
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Practical Applications of Statistical Methods in Bioinformatics
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Program Design: Principles and Methods
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Basic Structures for Algorithm Development
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Efficient vs Naïve Algorithms
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Structured Programming and Divide and Conquer
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Object -Oriented Approaches and Greedy Algorithms
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Introduction to AWS
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Introduction to Compute Storage Databases
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Introduction to AWS Services and free tier acount creation
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creation s3 bucket, Ec2 instance and connection
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Execution of pipeline through EC2 instance
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Basic SQL Syntax and Data Types
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Relational Databases and Data Operations
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SQL for Data Import, Export, and Manipulation
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Working with SQL Files and Query Execution
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SQL Workbench for Bioinformatics Data Analysis
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Drug Discovery and Development Process: Understanding QSAR Principles
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Introduction to Drug Discovery Process
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Role of Computational Methods
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Utilizing Biological Databases and GCP Standards
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Chemical Structure Visualization
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Visual Representation of Biological Processes and Structures in Data Analysis
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Biomolecules- Properties and function
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Molecular Docking and Molecular Dynamics
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Pharmacophore Modeling
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Pharmacophore Modelling applications
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Introduction to Single-Cell Omics
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Package installation
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Single-Cell RNA-Seq Analysis Workflow
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Bulk vs Single-Cell RNA-Sequencing
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Quality Control and Preprocessing of scRNA Data
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Normalization and Batch Effect Correction
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Cell Clustering and Type Identification
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Dimensionality Reduction and Data Visualization
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Trajectory and Pseudotime Analysis
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Cell-Cell Communication and Interaction Mapping
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Introduction to PCR & Gene Sequence
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Basic Primer Design
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Primer Quality Checking
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Primer Specificity & In-Silico PCR
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Mini Project
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EMPLOYABILITY SKILLS
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WORK MANAGEMENT
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MANAGE YOUR WORK TO MEET REQUIREMENTS
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WORK EFFECTIVELY WITH COLLEAGUES
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BUILD AND MAINTAIN RELATIONSHIPS AT WORKPLACE
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BUILD AND MAINTAIN CLIENT SATISFACTION
What you need to start
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Educational: Bachelor's degree in life sciences, biotechnology, bioinformatics, or related field (preferred)
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Prerequisites: Basic understanding of biology
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Technical: Reliable internet connection, functional computer, necessary software
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Attendance: Minimum 75% attendance requirement
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Examination: Must clear third-party government exam
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Commitment: Ability to complete assignments and projects on time
Who this course is for
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Life Sciences Graduates (Biotechnology, Microbiology, Biochemistry)
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Bioinformatics Students and Professionals
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Research Scholars and PhD Candidates
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Healthcare Professionals
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Data Scientists interested in biological data
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Academic Professionals seeking industry certification
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Career changers entering bioinformatics field
