Bioinformatics For Everyone Beginner To Expert Guide 2023

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

What you'll learn

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

Primary Databases in Bioinformatics

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.

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

Requirements

Background knowledge of Biology and genetics

Knowledge of the composition and function of Proteins

Understanding Bioinformatics Basic Concepts

Description

Updated and to-the-point course. It's worth your money and time! This Course runs through segments of bioinformatics topics that you need to learn from the beginner stage to master the bioinformatics field.The Bioinformatics course is designed to provide a comprehensive overview of the field of bioinformatics, covering the key concepts, tools, and techniques used in the analysis and interpretation of biological data.The course begins with an Introduction to Bioinformatics, where students will learn about the history and development of the field and the role of bioinformatics in modern biology research. They will also explore the various applications of bioinformatics in areas such as genomics, transcriptomics, proteomics, and metabolomics.The course will then delve into the topic of Biological Databases, providing an overview of the different types of databases available, and how they are used to store and manage biological data. Students will learn how to navigate and search different databases, including NCBI, Ensembl, and UniProt.File Formats in Bioinformatics will be covered in the next section, where students will learn about the various file formats used in bioinformatics, such as FASTA, FASTQ, SAM/BAM, and VCF. They will also explore tools and techniques for working with these file formats, including conversion, manipulation, and parsing.Sequence Alignment and Tools will be covered in the next section, where students will learn about the principles of sequence alignment, and the different tools and algorithms used for sequence alignments, such as BLAST, ClustalW, and MUSCLE. They will also learn how to interpret and analyze the results of sequence alignment.Command Line Bioinformatics will be covered in the next section, where students will learn how to work with bioinformatics tools and software using the command line interface (CLI). They will explore basic UNIX commands, and learn how to navigate directories, create and edit files, and run bioinformatics tools from the command line.Bioinformatics and Genomics on GUI and CLI will be covered in the next section, where students will learn how to work with bioinformatics tools and software using graphical user interfaces (GUIs), as well as the command line interface (CLI). They will explore popular GUI-based bioinformatics tools, such as Geneious and CLC Bio, as well as CLI-based tools such as BWA and GATK.The course will conclude with Bioinformatics and Proteomics, where students will learn about the principles of proteomics, and the different tools and techniques used for protein identification, quantification, and analysis. They will also explore how bioinformatics is used to predict protein structure and function, and design drugs and therapies based on protein interactions.

Overview

Section 1: Introduction of Bioinformatics

Lecture 1 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: Biological Databases

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 Part

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

Section 3: File Formats in Bioinformatics

Lecture 24 Introduction of File Formats

Lecture 25 Explaining different File Formats

Lecture 26 Summary of File Formats

Section 4: Segment 3: Sequence Alignment and Tools

Lecture 27 Introduction of Sequence Alignment

Lecture 28 History of Sequence Alignment

Lecture 29 Alignment Methods

Lecture 30 Interpretation of Sequence Alignment

Lecture 31 Representation and Storing of Sequences

Lecture 32 Significance and Uses of Sequence Alignment

Lecture 33 Software Used for Sequence Alignment

Lecture 34 Pairwise Sequence Alignment

Lecture 35 Tools for Pairwise Sequence Alignment

Lecture 36 Multiple Sequence Alignment

Lecture 37 Tools for Multiple Sequence Alignment

Lecture 38 Clustal tool for alignment

Section 5: Command line bioinformatics

Lecture 39 Introduction and Why CLI in Bioinformatics

Lecture 40 CLI and GUI Explanation

Lecture 41 if we already have Graphical user interface system why we should use CLI?

Lecture 42 Short Practical with Programming Language

Lecture 43 Why Would You Use CLI over GUI?

Lecture 44 Foundation behind CLI Shell explanation

Lecture 45 Drawbacks of CLI and GUI

Lecture 46 Linux Introduction and Usage Over years

Lecture 47 Linux Distros

Lecture 48 Why Ubuntu Operating System

Lecture 49 WSL Explanation

Lecture 50 Linux Vs Unix

Lecture 51 (Practical) Making A Subsystem For Linux In Windows OS

Lecture 52 Linux File Handling Commands

Lecture 53 Accessing And Creating Files In Windows Os

Lecture 54 Basic Process Management Commands for Linux OS

Lecture 55 E-utilities on the Linux Command Line

Lecture 56 Installing NCBI through CLi

Lecture 57 Entrez Direct Functions

Lecture 58 Mrna And Protein Seq Retrieval

Lecture 59 Batch Retrieval of Protein Using Taxon Id

Lecture 60 Retrieving CDS From Reference Genome

Lecture 61 Explaining Different Commands

Section 6: Bioinformatics and Genomics on GUI

Lecture 62 Introduction of Course Section

Lecture 63 Next-generation sequencing

Lecture 64 Generations of Sequencing

Lecture 65 NGS Workflow

Lecture 66 SRA Database introduction

Lecture 67 SRA File

Lecture 68 Galaxy Server Intro to Goals

Lecture 69 Galaxy Server And Objects

Lecture 70 Getting Onto Galaxy

Lecture 71 Tools For NGS Data Analysis

Lecture 72 Getting SRA Runs from Databases And platform

Lecture 73 Ncbi Genome to Galaxy

Lecture 74 Getting Sra Runs To Galaxy

Lecture 75 Fastqc Tool To Dataset Generated Dataset

Lecture 76 Trimmomatic Tool On Dataset

Lecture 77 Alignment/genome Mapping

Lecture 78 Abundance Estimation Tool On Dataset

Lecture 79 From Values To Visuals (Heatmap)

Section 7: Bioinformatics and Genomics on CLI

Lecture 80 NGS Understanding

Lecture 81 Getting the SRA Reads

Lecture 82 Bioinformatics Pipeline

Lecture 83 Checking the Quality of Data

Lecture 84 Quality Trimming of data

Lecture 85 Aligners and Aligning Reads to genome

Lecture 86 SAM and Bam File Indexing and Sorting

Lecture 87 Feature Extraction

Lecture 88 Pipeline Code

Section 8: Variant Calling on Command line

Lecture 89 Introduction of Course Section

Lecture 90 Variants and Types

Lecture 91 Understanding the Metadata and Software's

Lecture 92 Getting Data From SRA Using SRA Toolkit

Lecture 93 Quality Control and Trimming

Lecture 94 Sam and Bcf Tools and Fixing NS and Calling Variants

Lecture 95 Alignment to Reference Genome

Lecture 96 Separation of SNP's and Indels Variants

Lecture 97 Visualizing Variants Using IGV and UCSC Browser

Lecture 98 Pipeline Code

Section 9: Bioinformatics And Proteomics

Lecture 99 Section Introduction

Lecture 100 Explaining Homology Modeling

Lecture 101 GUI based Modeling of Proteins

Lecture 102 Command Line based Protein Modeling

Lecture 103 De-Novo and Machine Learning Methods

Lecture 104 Phylogenetics Analysis

Lecture 105 Motifs and Domains analysis

Lecture 106 Protein Physical Parameters and Location Analysis

Lecture 107 Protein-Protein Interaction and Enrichment Analysis

Lecture 108 Proteins Pathway Analysis

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.