Complete Mirna Profiling Using Bioinformatics And Ngs

What you'll learn

Introduction to miRNA Biology
Basic Linux for Bioinformatics
Small RNA Sequencing Workflow
Adapter Trimming
Genome Alignment
miRDeep2 Complete Pipeline
Differential Expression
Target Gene Prediction
Functional Enrichment

Requirements

This course is designed for both beginners and researchers. You do not need prior experience in bioinformatics to start. Basic understanding of Biology, Genetics, or Molecular Biology is recommended. No prior programming knowledge is required. No prior Linux experience is required — Linux is taught from the basics in this course. A computer running Windows, macOS, or Linux with at least 8 GB RAM (16 GB recommended for larger datasets). An internet connection to download practice datasets and bioinformatics software. A willingness to learn hands-on Next Generation Sequencing (NGS) data analysis using real research datasets.

Description

Learn miRNA Profiling and Small RNA-Seq analysis from raw sequencing data to biological interpretation through a practical, hands-on bioinformatics workflow.This course is designed for biotechnology students, bioinformatics students, life science researchers, PhD scholars, molecular biologists, and bioinformaticians who want to develop practical skills in analyzing miRNA sequencing data.You will learn how to build an end-to-end miRNA bioinformatics pipeline, starting with raw FASTQ files and progressing through quality control, adapter trimming, read alignment, miRNA identification, differential expression, target prediction, and functional enrichment analysis.What You Will LearnUnderstand miRNA biology, biogenesis, and regulation of gene expressionLearn the fundamentals of Small RNA Sequencing and NGS dataWork with Linux and command-line tools for bioinformaticsPerform sequencing quality control using FastQC Perform adapter trimming and read filtering using CutadaptAlign miRNA sequencing reads using BowtieIdentify known and novel miRNAs using miRDeep2Work with miRBase and miRNA reference databasesPerform differential miRNA expression analysisAnalyze expression data using RCreate PCA plots, volcano plots, heatmaps, and other publication-ready visualizationsPerform miRNA target gene predictionExplore target databases and integrate miRNA–gene informationPerform Gene Ontology (GO) and KEGG pathway enrichment analysisApply the complete workflow to a real-world research projectComplete WorkflowYou will follow a practical workflow:FASTQ → Quality Control → Adapter Trimming → Read Filtering → Alignment → miRNA Identification → Expression Analysis → Differential Expression → Target Prediction → KEGG Enrichment Hands-On LearningThis is not just a theoretical course. You will work with sequencing datasets and learn how individual bioinformatics tools fit together into a complete research workflow.You will also learn how to organize your analysis, interpret results, troubleshoot common problems, and generate figures suitable for research reports and publications.Who Is This Course For?This course is suitable for:Biotechnology and Bioinformatics studentsBSc.and MSc Life Science studentsPhD scholars and academic researchersMolecular Biology and Genetics researchersBioinformaticiansBiomedical researchersWet-lab scientists moving into computational biologyResearchers working with NGS and transcriptomics dataAnyone interested in miRNA biomarkers and small RNA sequencingDo You Need Previous Bioinformatics Experience?No. The course is designed to take learners from the fundamentals to a complete practical miRNA analysis workflow.Basic knowledge of biology, genetics, or molecular biology is helpful, but previous experience with Linux, R, programming, or NGS analysis is not required.Tools CoveredLinux | FastQC | Cutadapt | Bowtie | SAMtools | miRDeep2 | miRBase | R | DESeq2 | Target Prediction | KEGG Pathway AnalysisBy the end of the course, you will have the practical knowledge needed to perform miRNA sequencing analysis from raw FASTQ data through differential expression, target prediction, functional enrichment, and biological interpretation.
This course is designed for anyone who wants to learn miRNA Profiling and Small RNA-Seq analysis using bioinformatics tools through a practical, hands-on approach. Biotechnology students who want to develop practical NGS and bioinformatics skills. Bioinformatics students and beginners who want to learn an end-to-end miRNA sequencing workflow. MSc and PhD researchers working on miRNA, genomics, transcriptomics, cancer biology, biomarkers, or molecular biology. Molecular biology and genetics researchers who want to analyze their own miRNA sequencing data. Life science graduates looking to transition from wet-lab research to computational biology. Biomedical and clinical researchers interested in miRNA-based biomarker discovery and disease research. Bioinformaticians who want to expand their skills into small RNA sequencing and miRNA analysis. Researchers and students working with NGS data who want hands-on experience with Linux, miRDeep2, Bowtie, DESeq2, R, and functional analysis. Faculty and research professionals who want to understand and implement a complete miRNA bioinformatics workflow.,This course is especially suitable if you want to learn how to go from: Raw FASTQ files → Quality Control → Adapter Trimming → Alignment → Known/Novel miRNA Identification → Differential Expression → Target Prediction → GO/KEGG Enrichment → Biological Interpretation,Who Should NOT Take This Course? This course may not be suitable for learners looking for only theoretical information about miRNA biology. The focus is on practical bioinformatics, NGS data analysis, and research-oriented workflows.

Homepage

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