Are you ready to transition from basic tools to Advanced Computational Biology and Data Science? Join our specialized 6-Month Internship Program on Tools and Techniques in Bioinformatics (Level-3), designed to take you from Linux automation and R programming to cutting-edge Bulk RNA-seq, Single-Cell analysis, and Cancer Bioinformatics.

📚 Course Curriculum & Modules: This internship covers 24+12 (project) classes divided into 8 intensive modules with 7 hands-on assignments, culminating in a dedicated 3-month research project focused on High-Throughput Sequencing Data Analysis.

Module 1: Basic RNA-seq Introduction
Build your foundation from the ground up. This module covers the definition, history, and scope of Bioinformatics, then moves into the Central Dogma and why RNA-seq matters. You will learn to read essential biological data formats (FASTA, FASTQ, Phred quality scores, count matrices) and retrieve datasets from public repositories like NCBI GEO, ENA, and SRA Toolkit.

Module 2: Linux Command Line
Transition from a casual user to a computational pro. You will set up a professional Linux Environment (Ubuntu/WSL), understand kernel concepts, and manage software using Conda/Bioconda. The module covers essential terminal commands (cd, ls, grep, awk, sed), file permissions, and writing Shell Scripts (.sh) to automate bioinformatics pipelines, plus a comparison of Cloud platforms (Galaxy) vs. local command line.

Module 3: R Programming for Bioinformatics
Unlock the power of statistical programming. Starting from R fundamentals (vectors, matrices, lists, dataframes, control structures, apply family), you will master data manipulation using dplyr and tidyr. You will handle biological sequences with Biostrings and create publication-ready figures using ggplot2, including scatter plots, boxplots, faceting, and Complex Heatmaps.

Module 4: Bulk RNA-seq Data Analysis
Master the industry-standard pipeline for differential expression. You will process raw sequencing data using FastQC, Trimmomatic/Cutadapt, and MultiQC, followed by alignment using HISAT2/STAR. The module covers quantification (featureCounts, HTSeq, Salmon, Kallisto), normalisation (TPM, RPKM, CPM), and rigorous DGE analysis using DESeq2, edgeR, and limma-voom. You will also learn Meta-Analysis: combining multiple datasets across platforms, batches, and studies to identify robust combined DEGs.

Module 5: Single-Cell RNA-seq Data Analysis
Step into the future of genomics. This extensive module covers the complete scRNA-seq workflow using Seurat and Scanpy. You will learn 10x Genomics droplet-based technology, Barcodes and UMIs, Quality Control (mitochondrial content, doublet filtering), and master Dimensionality Reduction (PCA, UMAP, t-SNE). The course guides you through graph-based Clustering, Marker Gene Identification, and advanced visualisation using Dot Plots and Feature Plots.

Module 6: Systems Biology
Go beyond gene lists to biological insights. You will interpret your Differentially Expressed Genes using Gene Ontology (GO), KEGG Pathway analysis, Reactome, and GSEA. The module also covers Protein-Protein Interaction (PPI) network construction, network visualisation, and Hub Gene identification.

Module 7: Cancer Bioinformatics
Apply your skills to the most active field in biomedical research. You will start with an overview of Cancer Bioinformatics, learn how to design a complete workflow for cancer research, and master data mining and processing from major cancer databases. From there the module moves into multi-omics expression analysis (transcriptomic and proteomic), Survival Prognosis analysis, Genetic alteration and DNA methylation analysis, Gene-immune analysis, Immune infiltration profiling, Gene effect score prediction, and Drug sensitivity analysis.

Module 8: Research Project & Career Guidelines
Classes 25 - 36 (3 Months) Capstone Research Project. Apply your advanced skills in a real-world scenario. You will select a specialized topic in RNA-seq Data Analysis or Cancer Bioinformatics. Under expert mentorship, you will execute the analysis, generate publication-quality figures, and receive step-by-step guidance on Scientific Paper Writing and journal submission.