Comprehensive Bioinformatics: Learn Genomics Data Analysis

Unlocking Genomic Data Analysis Mysteries through Practical Bioinformatics Applications for Research Purpose

What you'll learn

Understand Genomic Fundamentals

Sequence Alignment

Genome Annotation Analysis

Gene Structure Analysis

Variant Calling

Gene Location on chromosome

Transcriptomics

Proteomics

Phylogenetics

Functional Genomics

Bioinformatics Tools for Genomic Analysis

Practical Genomics Data Analysis

Research-oriented Bioinformatics Techniques

Genomic Sequencing and Coding

Transcriptomics Data analysis

Requirements

Basic Biological Knowledge

Curiosity and Enthusiasm

Computer Literacy

Description

Embark on a transformative journey into the fascinating realm of genomics and bioinformatics with our course, "Comprehensive Bioinformatics: Learning Genomics Data Analysis." This comprehensive program is meticulously crafted to empower learners with the knowledge and skills essential for unlocking the secrets encoded in the DNA of living organisms.What You Will Learn:This course takes a hands-on approach, guiding you through the following key areas:Genomic Fundamentals:Gain a deep understanding of the structure and function of genomes.Explore the language of DNA and the genetic code.Bioinformatics Basics:Learn how bioinformatics tools are integral to genomics research.Develop proficiency in handling and processing large genomic datasets.Genomic Data Analysis Techniques:Acquire practical skills in analyzing genomic data using a variety of bioinformatics tools.Explore methods for variant calling, gene location on chromosomes, and gene structure analysis.Applications in Research:Understand how genomics contributes to disease research, biotechnology, and agriculture.Explore real-world case studies to apply your knowledge in research-oriented scenarios.Capstone Project:Apply your acquired skills and knowledge in a comprehensive capstone project.Demonstrate your proficiency in genomics data analysis using bioinformatics tools.Who Should Enroll:Biologists, geneticists, and healthcare professionals eager to enhance their skills in genomics data analysis.Computer science and IT professionals interested in transitioning into bioinformatics.Researchers and academics across diverse disciplines seeking to integrate genomics into their projects.Students in biological sciences looking to expand their practical skills in genomics and bioinformatics.Prerequisites:While a basic understanding of biology and computer literacy is recommended, this course is designed to accommodate learners with varying levels of expertise.Outcome:Upon completion, you will possess the tools and knowledge to navigate genomic landscapes, making you adept at employing bioinformatics for comprehensive genomics data analysis. Join us on this exciting journey to decode the genetic blueprint and contribute to cutting-edge research and discovery. Enroll now to unlock the potential of genomics!

Overview

Section 1: Introduction

Lecture 1 Introduction to Genomics for Bioinformatics

Section 2: Sequence Alignment

Lecture 2 Pairwise Sequence Alignment

Lecture 3 Multiple Sequence Alignment

Lecture 4 Sequence Alignment Using Mega

Section 3: Genome Annotation Analysis

Lecture 5 Genome Annotation and visualization

Section 4: Gene Structure Analysis

Lecture 6 Intron and Exon Analysis

Section 5: Linux in Bioinformatics (optional)

Lecture 7 Introduction and Why CLI in Bioinformatics

Lecture 8 CLI and GUI Explanation

Lecture 9 if we already have Graphical user interface system why we should use CLI?

Lecture 10 Short Practical with Programming Language

Lecture 11 Why Would You Use CLI over GUI?

Lecture 12 Drawbacks of CLI and GUI

Lecture 13 Foundation behind CLI Shell explanation

Lecture 14 Linux Introduction and Usage Over years

Lecture 15 Linux Distros

Lecture 16 Why Ubuntu Operating System

Lecture 17 WSL Explanation

Lecture 18 Linux Vs Unix

Lecture 19 (Practical) Making A Subsystem For Linux In Windows OS

Lecture 20 Linux File Handling Commands

Lecture 21 Accessing And Creating Files In Windows Os

Lecture 22 Basic Process Management Commands for Linux OS

Lecture 23 E-utilities on the Linux Command Line

Lecture 24 Installing NCBI through CLi

Lecture 25 Entrez Direct Functions

Lecture 26 Mrna And Protein Seq Retrieval

Lecture 27 Batch Retrieval of Protein Using Taxon Id

Lecture 28 Retrieving CDS From Reference Genome

Lecture 29 Explaining Different Commands

Lecture 30 Commands

Section 6: Variant Calling Analysis on Linux

Lecture 31 Introduction of Course Section

Lecture 32 Variants and Types

Lecture 33 Understanding the Metadata and Software's

Lecture 34 Getting Data From SRA Using SRA Toolkit

Lecture 35 Quality Control and Trimming

Lecture 36 Sam and Bcf Tools and Fixing NS and Calling Variants

Lecture 37 Alignment to Reference Genome

Lecture 38 Separation of SNP's and Indels Variants

Lecture 39 Visualizing Variants Using IGV and UCSC Browser

Lecture 40 Pipeline Code

Section 7: Gene location on Chromosome

Lecture 41 Gene location on Chromosome Analysis

Section 8: Transcriptomics (NGS Data) Analysis using GUI and CLI

Lecture 42 Introduction of Course Section

Lecture 43 Next-generation sequencing

Lecture 44 Generations of Sequencing

Lecture 45 NGS Workflow

Lecture 46 SRA Database introduction

Lecture 47 SRA File

Lecture 48 Galaxy Server Intro to Goals

Lecture 49 Galaxy Server And Objects

Lecture 50 Getting Onto Galaxy

Lecture 51 Tools For NGS Data Analysis

Lecture 52 Getting SRA Runs from Databases And platform

Lecture 53 Ncbi Genome to Galaxy

Lecture 54 Getting Sra Runs To Galaxy

Lecture 55 Fastqc Tool To Dataset Generated Dataset

Lecture 56 Trimmomatic Tool On Dataset

Lecture 57 Alignment/genome Mapping

Lecture 58 Abundance Estimation Tool On Dataset

Lecture 59 From Values To Visuals (Heatmap)

Lecture 60 Understanding NGS For Linux

Lecture 61 Getting the SRA Reads

Lecture 62 Bioinformatics Pipeline

Lecture 63 Checking the Quality of Data

Lecture 64 Quality Trimming of data

Lecture 65 Aligners and Aligning Reads to genome

Lecture 66 SAM and Bam File Indexing and Sorting

Lecture 67 Feature Extraction

Lecture 68 Pipeline Code

Section 9: Proteomics

Lecture 69 Protein Structure Prediction

Lecture 70 Homology Modeling

Lecture 71 GUI based Modeling of Proteins

Lecture 72 Command Line based Protein Modeling

Lecture 73 De-Novo and Machine Learning Modeling

Lecture 74 Protein Visualization Analysis

Lecture 75 Motifs and Domains analysis

Lecture 76 Protein Physical Parameters and Location Analysis

Lecture 77 Protein Pathway and Enrichment Analysis

Lecture 78 Protein-Protein Interaction Network

Lecture 79 Proteins Pathway Analysis

Section 10: Phylogenetics

Lecture 80 Phylogenetics Analysis

Section 11: Functional Genomics

Lecture 81 Gene Enrichment Analysis

Biologists and Geneticists,Bioinformatics Enthusiasts,Healthcare and Medical Professionals,Computer Science and IT Professionals,Researchers and Academics