Bioinformatics Mastery: Your Journey From Beginner To Expert

Bioinformatics Beginners to advance course to learn in 10 hours to understand the simple and complex topics of bioinfo

What you'll learn

Foundational Understanding: Acquire a solid grasp of fundamental bioinformatics concepts, including data analysis, algorithms, and computational techniques.

Practical Skills Development: Develop hands-on proficiency in utilizing popular bioinformatics tools and software for tasks such as sequence analysis,

Data Integration Techniques: Learn advanced methods for integrating diverse biological data types, enabling a holistic approach to understanding complex data.

Problem-Solving Strategies: Enhance problem-solving skills by applying bioinformatics approaches to real-world biological questions and challenges.

You will learn about the history and applications of bioinformatics

You will learn Basic demonstration of Bioinformatics tools

Different databases used in bioinformatics

Interpretation of Sequence Alignment

Tools Used in sequence Alignment in bioinformatics

Alignment Methods and Representation

They will be able to use and know different categories of sub-databases of NCBI.

Plant Genome Databases

Secondary Databases in Bioinformatics

Protein basic Concepts

Understanding different techniques for protein prediction

Understanding Comparative or Homology modeling

Protein Modeling Using GUI Interface

Swiss Model hands on training

Protein Modeling Using CLI Interface

Protein Modeling Using Modeller

The basics of Next Generation Sequencing and how it can be used for Differential gene expression analysis via RNA sequencing.

Quality Control of NGS data

Trimming the Reads of NGS Data

Different tools for aligning reads to genome

Differential Expression Analysis.

Ultimately understand how technologies like RNA sequencing could be used to identify specific genes that can cause certain conditions.

Heatmap Generation of Results

Interpret the results of DEG's

Understanding Bioinformatics Pipeline concept

Use of Galaxy for NGS data processing

Introduction to R

Data Analysis Using R

Introduction to Linux

Data Analysis using Linux

Introduction to Python

Data Analysis using Python Language

Requirements

Understanding Bioinformatics Basic Concepts

Background knowledge of Biology and genetics

Description

Get ready to dive into an extensive and in-depth bioinformatics course that is worth every penny and second of your time! This comprehensive program covers a wide range of bioinformatics topics, taking you from a beginner stage to a master level in the field.The Bioinformatics course offers a holistic overview, encompassing all the essential concepts, tools, and techniques employed in the analysis and interpretation of biological data.We kick off with a captivating Introduction to Bioinformatics, where you'll explore the rich history and development of the field, understanding its pivotal role in modern biology research. Discover the diverse applications of bioinformatics in genomics, transcriptomics, proteomics, and metabolomics, and witness how it revolutionizes these areas.In the following section, we delve into Biological Databases. Gain proficiency in navigating and utilizing various database types, including NCBI, Ensembl, and UniProt. Learn the art of effectively searching these databases and master the management of biological data.Prepare yourself for an enlightening exploration of File Formats in Bioinformatics. Familiarize yourself with commonly used file formats such as FASTA, FASTQ, SAM/BAM, and VCF. Discover valuable tools and techniques for manipulating, converting, and parsing these formats, equipping yourself with essential skills for data manipulation.Next up, we tackle the intricacies of Sequence Alignment and Tools. Delve into the principles underlying sequence alignment and gain hands-on experience with powerful tools and algorithms like BLAST, ClustalW, and MUSCLE. Learn to interpret and analyze alignment results, extracting meaningful insights from your data.Command Line Bioinformatics takes center stage in the subsequent section. Unleash the potential of bioinformatics tools and software using the command line interface (CLI). Master fundamental UNIX commands, navigate directories, create and edit files, and seamlessly run bioinformatics tools from the command line.In Bioinformatics and Genomics on GUI and CLI, we equip you with a versatile skill set. Learn how to leverage graphical user interfaces (GUIs) and CLI-based tools simultaneously. Explore popular GUI-based bioinformatics tools like Geneious and CLC Bio, alongside CLI-based tools such as BWA and GATK. Gain the flexibility to choose the most suitable approach for your bioinformatics endeavors.As the course draws to a close, we delve into Bioinformatics and Proteomics. Unlock the principles of proteomics and delve into tools and techniques for protein identification, quantification, and analysis. Explore how bioinformatics aids in predicting protein structure and function, as well as designing drugs and therapies based on protein interactions.Each section of this course offers practical exercises, real-world examples, and valuable insights. You'll work with actual biological data, honing your skills in interpreting and visualizing results, and gaining a profound understanding of the challenges and opportunities bioinformatics presents.Are you ready to embark on this transformative bioinformatics journey? Enroll in our course today and unlock the limitless potential of this captivating field!

Overview

Section 1: Introduction to Bioinformatics

Lecture 1 Course Introduction

Lecture 2 Introduction of Bioinformatics field

Lecture 3 History of Bioinformatics

Lecture 4 Components of bioinformatics

Lecture 5 Working in Bioinformatics

Lecture 6 Career Outlook for bioinformaticians

Lecture 7 Careers for bioinformaticians

Lecture 8 Applications of Bioinformatics

Lecture 9 Applications of Bioinformatics Pt:2

Section 2: Bioinformatics Databases and File Formats

Lecture 10 Introduction of Biological Databases

Lecture 11 Types of Biological Databases

Lecture 12 Difference Between Primary and Secondary Databases

Lecture 13 Primary Databases

Lecture 14 Explaining Primary Databases

Lecture 15 Explaining Primary Databases pt:2

Lecture 16 Explaining Primary Databases Last

Lecture 17 Introduction of Secondary Databases

Lecture 18 Explaining Secondary Databases

Lecture 19 Explaining Secondary Databases pt:2

Lecture 20 Explaining Secondary Databases Pt:3

Lecture 21 Explaining Secondary Databases Pt:4

Lecture 22 Introduction of Literature Databases

Lecture 23 Explaining Literature Databases

Lecture 24 Introduction of File Formats

Lecture 25 Explaining different File Formats

Lecture 26 Summary of File Formats

Section 3: Plant Databases

Lecture 27 Plant database introduction

Lecture 28 Types Of Databases

Lecture 29 Brassica Database

Lecture 30 Phytozome

Lecture 31 Ensembl Plants

Lecture 32 Gsad Database

Lecture 33 NCBI Database

Lecture 34 Pgdjb Database

Lecture 35 Ptgbase Database

Lecture 36 Rdna Database

Lecture 37 Gdb Browser

Section 4: Sequence Alignment in Bioinformatics

Lecture 38 Introduction of Sequence Alignment

Lecture 39 History of Sequence Alignment

Lecture 40 Alignment Methods

Lecture 41 Interpretation of Sequence Alignment

Lecture 42 Representation and Storing of Sequences

Lecture 43 Significance and Uses of Sequence Alignment

Lecture 44 Software Used for Sequence Alignment

Lecture 45 Pairwise Sequence Alignment

Lecture 46 Tools for Pairwise Sequence Alignment

Lecture 47 Multiple Sequence Alignment

Lecture 48 Tools for Multiple Sequence Alignment

Lecture 49 Clustal tool for alignment

Section 5: Proteomics Using Bioinformatics

Lecture 50 Section Introduction

Lecture 51 Explaining Homology Modeling

Lecture 52 GUI based Modeling of Proteins

Lecture 53 Command Line based Protein Modeling

Lecture 54 De-Novo and Machine Learning Methods

Lecture 55 Protein Structure Prediction

Lecture 56 Protein Visualization Analysis

Lecture 57 Phylogenetics Analysis

Lecture 58 Motifs and Domains analysis

Lecture 59 Protein Physical Parameters and Location Analysis

Lecture 60 Protein-Protein Interaction and Enrichment Analysis

Lecture 61 Proteins Pathway Analysis

Section 6: Linux in Bioinformatics (Command Line Bioinformatics)

Lecture 62 Introduction and Why CLI in Bioinformatics

Lecture 63 CLI and GUI Explanation

Lecture 64 if we already have Graphical user interface system why we should use CLI?

Lecture 65 Short Practical with Programming Language

Lecture 66 Why Would You Use CLI over GUI?

Lecture 67 Foundation behind CLI Shell explanation

Lecture 68 Drawbacks of CLI and GUI

Lecture 69 Linux Introduction and Usage Over years

Lecture 70 Linux Distros

Lecture 71 Why Ubuntu Operating System

Lecture 72 WSL Explanation

Lecture 73 Linux Vs Unix

Lecture 74 (Practical) Making A Subsystem For Linux In Windows OS

Lecture 75 Linux File Handling Commands

Lecture 76 Accessing And Creating Files In Windows Os

Lecture 77 Basic Process Management Commands for Linux OS

Lecture 78 E-utilities on the Linux Command Line

Lecture 79 Installing NCBI through CLi

Lecture 80 Entrez Direct Functions

Lecture 81 Mrna And Protein Seq Retrieval

Lecture 82 Batch Retrieval of Protein Using Taxon Id

Lecture 83 Retrieving CDS From Reference Genome

Lecture 84 Explaining Different Commands

Lecture 85 Commands

Section 7: NGS Data Analysis using Galaxy and Linux

Lecture 86 Introduction of Course Section

Lecture 87 Next-generation sequencing

Lecture 88 Generations of Sequencing

Lecture 89 NGS Workflow

Lecture 90 SRA Database introduction

Lecture 91 SRA File

Lecture 92 Galaxy Server Intro to Goals

Lecture 93 Galaxy Server And Objects

Lecture 94 Getting Onto Galaxy

Lecture 95 Tools For NGS Data Analysis

Lecture 96 Getting SRA Runs from Databases And platform

Lecture 97 Ncbi Genome to Galaxy

Lecture 98 Getting Sra Runs To Galaxy

Lecture 99 Fastqc Tool To Dataset Generated Dataset

Lecture 100 Trimmomatic Tool On Dataset

Lecture 101 Alignment/genome Mapping

Lecture 102 Abundance Estimation Tool On Dataset

Lecture 103 From Values To Visuals (Heatmap)

Lecture 104 Understanding NGS For Linux

Lecture 105 Getting the SRA Reads

Lecture 106 Bioinformatics Pipeline

Lecture 107 Checking the Quality of Data

Lecture 108 Quality Trimming of data

Lecture 109 Aligners and Aligning Reads to genome

Lecture 110 SAM and Bam File Indexing and Sorting

Lecture 111 Feature Extraction

Lecture 112 Pipeline Code

Section 8: Variant Calling Analysis Using Linux

Lecture 113 Introduction of Course Section

Lecture 114 Variants and Types

Lecture 115 Understanding the Metadata and Software's

Lecture 116 Getting Data From SRA Using SRA Toolkit

Lecture 117 Quality Control and Trimming

Lecture 118 Sam and Bcf Tools and Fixing NS and Calling Variants

Lecture 119 Alignment to Reference Genome

Lecture 120 Separation of SNP's and Indels Variants

Lecture 121 Visualizing Variants Using IGV and UCSC Browser

Lecture 122 Pipeline Code

Section 9: Python for Bioinformatics

Lecture 123 Introduction to Bioinformatics and Why Python

Lecture 124 BioPython Introduction

Lecture 125 GitHub Repository for Python

Lecture 126 Setting up Coding Environment

Lecture 127 Explaining the libraries for the course

Lecture 128 Advance File Formats of Bioinformatics with BioPython

Lecture 129 Sequence Analysis Using Biopython

Lecture 130 Database Retrieval/Accessing Using Biopython

Lecture 131 Working With Genomes Using Biopython

Lecture 132 Phylogenetic Tree Construction using Biopython

Lecture 133 Proteomics Analysis Using Biopython

Lecture 134 Machine Learning in Bioinformatics

Section 10: R for Bioinformatics

Lecture 135 Introduction to Bioinformatics and R: Exploring the Intersection of Biology

Lecture 136 Getting Started with R: Installation and Variables Understanding

Lecture 137 Working with R Packages: Installing, Loading, and Exploring Bioinformatics

Lecture 138 Differential Gene Expression Analysis with Deseq2: Preparing Data

Lecture 139 Deseq2 Code Understanding

Lecture 140 Converting Ensembl Gene IDs to Gene Symbols: Using R Techniques and Packages

Lecture 141 Visualizing Gene Expression Data: Creating Stunning Plots with ggplot2

Lecture 142 Introduction to Single-Cell RNA Sequencing (scRNA-seq) Data Analysis

Lecture 143 Exploring scRNA-seq Code: Cell Trajectories and Gene Expression Dynamics

Lecture 144 GitHub Source Code for R

Section 11: Microarray Data Analysis Using R

Lecture 145 Introduction of Microarray

Lecture 146 Microarray Databases

Lecture 147 Microarray Analysis Using GEO2R

Lecture 148 Microarray Analysis on R

Lecture 149 Source Code for Microarray Section

Biologists and Life Scientists: Biologists, molecular biologists, geneticists, and researchers in the life sciences who want to enhance their skills in bioinformatics.,People generally interested in new research methodologies and would like to try them themselves!,Beginner Bioinformaticians looking to understand the process of Proteins,Beginner Bioinformatics Students,People interested in researching the effects of different pathologies on gene expression or even how gene expression changes over the course of a cell's growth curve.,People looking to carry out differential gene expression and gene ontology analysis.,People who want to carry out bioinformatic analysis without the need for complex code.,Researchers are Encouraged to take this Course.,Beginners Bioinformatics Students,Industry Professionals wants to learn Bioinformatics.