Learn Bioinformatics From Scratch Theory Practical

Best Bioinformatics course for Students, Academia and Industry Professionals to learn Bioinformatics and biological data
Learn Bioinformatics From Scratch Theory Practical
File Size :
4.78 GB
Total length :
7h 21m

Category

Instructor

Muhammad Dujana

Language

Last update

2/2023

Ratings

4.2/5

Learn Bioinformatics From Scratch Theory Practical

What you’ll learn

You will learn Basic Theory & Practical demonstration of Bioinformatics tools
You will learn how to explore databases, and align sequences (Pairwise and Multiple Sequences)
You will learn theory and practical to predict Genes and their regulatory elements
You will have good understanding about homology modeling for 3D structure prediction (Theory & Practical)
You will learn 3D structure Prediction using Threading Algorithm (Theory & Practical)
Secondary Structure Prediction of Globular and Transmembrane proteins (Theory & Practical)
Receptor-Ligand Docking and Analysis of Docking Data (Practical)
Phylogenetic tree (Theory)
Construction of Phylogenetic tree in (Practical)
This basic Bioinformatics course will laydown very strong foundation for their future learning.
We claim that so far there is not any comprehensive course like this on Udemy.

Learn Bioinformatics From Scratch Theory Practical

Requirements

In online teaching, it’s always hard to engage the students. Therefore we have designed this course keeping the psychology of students in view. Usually, students start to lose their interest when they are stuck in a complex concept that’s why We tried to move from simple to complex easily and understandably.
You need to know about the very basics of Biological macro-molecules. Do not worry if you do not know the details. For instance, if you just heard the name of DNA, RNA and Proteins and have a basic idea about their roles in life then it’s enough for you (School Level Information). You are welcome to this course. In every module of this course, we will take start from very scratch. We will assume that you know nothing about DNA, RNA, and Proteins except their names. We hope this technique will make it easy for you to understand the hardcore concepts of bioinformatics in a better way.
This is no coding in this course. Most of tools which we will use that’s available online

Description

This Bioinformatics course is going to game changer for you. Currently, there is an explosion of biological data. You need to develop your skills to handle the data in the era of this big biological data. It is humanly impossible to tackle the high biological data using conventional techniques. Here comes Bioinformatics. Bioinformatics is at the intersection of biology and computer science. Without this basic skill, you may not stand anywhere in research, academia and industry in the coming five to ten years. Keeping this need of time in view, we brought here a basic bioinformatics course for you.This course includes five modules(1) Databases(2) Alignment (3) Genomic Bioinformatics (4) Structural Bioinformatics (5) Evolutionary Bioinformatics  This course is a unique blend of theory and practical. You will learn basic theory then perform practical and afterwards attempt the quizzes to check your knowledge. There is a total of 93 Lectures among them, there are 19 practical tutorials. Furthermore, there are 12 Assignments and 5 quizzes in this course along with theory lectures. We assure you that after taking this course, your perspective will be very different for biological data.  Students will learn the basics of bioinformatics, starting from biological databases to protein-ligand docking.We hope this course will be worth your money and time.

Overview

Section 1: Module 1 Databases

Lecture 1 Definition of Databases

Lecture 2 Database Design

Lecture 3 Knowledge Discovery

Lecture 4 Biological Databases

Lecture 5 Take Home Key Points

Lecture 6 Practical -1: NCBI Nucleotide Database

Lecture 7 Practical-2: Protein Databank (PDB)

Section 2: Module 2 Sequence Alignment

Lecture 8 What is Sequence Alignment?

Lecture 9 Some Important Terms

Lecture 10 Types of Sequence Alignment

Lecture 11 What is Algorithms?

Lecture 12 Dot Matrix Algorithm; How Does It Work?

Lecture 13 Dot Matrix Algorithm; How to Interpret The Results?

Lecture 14 Dot Matrix Algorithm; Identification of Repeat Sequences

Lecture 15 Dot Matrix Algorithm; Advantages Vs Disadvantages

Lecture 16 Practical-3: DotMatcher for Qualitative Comparison of Sequence

Lecture 17 Dynamic Programming Method: How Does It Work?

Lecture 18 How to Transform Scoring Matrix to Alignment?

Lecture 19 Dynamic Programming; Some Important Terms to Understand

Lecture 20 Comparison Between DotMatrix and Dynamic Programming

Lecture 21 Practical-4: Global Pairwise Sequence Alignment Using DNA Sequences

Lecture 22 Practical-5: Pairwise Sequence Alignment Using Protein

Lecture 23 Practical-6: Local Pairwise Sequence

Lecture 24 Introduction to Database Searching; BLAST

Lecture 25 Type of Algorithms

Lecture 26 How Does Word Algorithm Work? (Part-1)

Lecture 27 How Does Word Algorithm Work? (Part-2)

Lecture 28 A Important Term For Word Algorithm

Lecture 29 Important Statistical Values to Evaluate the BLAST Results

Lecture 30 Different Type of BLAST Associated with NCBI Databases

Lecture 31 Practical -7: How to Use BLAST Program

Lecture 32 Optional: How to Use PSI-BLAST

Lecture 33 Multiple Sequence Alignment; An Introduction

Lecture 34 Algorithms for Multiple Sequence Alignment

Lecture 35 Progressive Sequence Alignment Algorithm

Lecture 36 Tools for Multiple Sequence Alignment

Lecture 37 Practical -8: How to Use CLUSTAL-W

Lecture 38 Practical -9: How to Use T-COFFEE

Section 3: Module 3: Genomic Bioinformatics

Lecture 39 Introduction of Module 3

Lecture 40 What is DNA?

Lecture 41 Where Is Our DNA is Located?

Lecture 42 What Is Role of DNA?

Lecture 43 What Does Gene Have?

Lecture 44 Algorithms for Gene Prediction-1

Lecture 45 Algorithms for Gene Prediction-2

Lecture 46 GC-Bias and Test Code; An Ab-initio Type of Algorithm

Lecture 47 Introduction of Markov Model (Part-1)

Lecture 48 Introduction of Markov Model (Part-2)

Lecture 49 Machine Learning and Gene Prediction

Lecture 50 Practical-10: Prediction of Prokaryotic Gene

Lecture 51 Practical-10.1 Prediction of Prokaryotic Regulatory Elements

Lecture 52 Practical-11 Prediction of Eukaryotic Gene

Section 4: Module 4: Structural Bioinformatics

Lecture 53 Introduction of Module 4

Lecture 54 What is Protein? (Part-1)

Lecture 55 What is Protein? (Part-2)

Lecture 56 Some Important Points

Lecture 57 Role of Amino Acids in 3D Structure

Lecture 58 Peptide Bond; A link between Amino Acids

Lecture 59 Double Bond like Character in Peptide Bond & Ramachandran Plot

Lecture 60 Forces Stabilizing The Protein Structure

Lecture 61 Secondary Structures of Proteins

Lecture 62 Practical 13: Visualization of Protein Structure in Pymol (Part-1)

Lecture 63 Why Protein Structure Prediction is So Important?

Lecture 64 Protein Secondary Structure Prediction Algorithms (Part-1)

Lecture 65 Protein Secondary Structure Prediction Algorithms (Part-2)

Lecture 66 Practical-15: Prediction of Globular Protein Secondary Structure

Lecture 67 Algorithm for Secondary Structure Prediction of Transmembrane Proteins

Lecture 68 Practical-16: Prediction of Transmembrane Helix Secondary Structure

Lecture 69 3D Structure Prediction Algorithms

Lecture 70 Homology Based Algorithm (Part-1)

Lecture 71 Homology Based Algorithm (Part-2)

Lecture 72 Homology Based Algorithm (Part-3)

Lecture 73 Homology Based Algorithm (Part-4)

Lecture 74 Model Validation & Draw back of Homology Based Algorithm

Lecture 75 Practical-17: Prediction of 3D structure Using Homology Modeling (Mdeller)

Lecture 76 Threading Algorithm for 3D Structure Prediction

Lecture 77 Practical-18: Prediction of 3D structure Using Threading Technique (I-TASSER)

Lecture 78 (Optional) Practical-18.1: Use of InterPro

Lecture 79 (Optional) Practical-20: How to Perform Docking Easily Using Vina

Lecture 80 (Optional) Practical-21: How to Analyze the Docking Data

Lecture 81 (Optional) Practical 3: ZINC Database for Drug Searching

Lecture 82 (Very Important) Practical Learn How to Use Alpha-Fold

Lecture 83 Update Another GOR-IV Server for Secondary Structure Predictions

Lecture 84 How to Make Publication Quality Images In Pymol? (Very Important)

Section 5: Module 5: Evolutionary Bioinformatics

Lecture 85 What is Evolution and Phylogenetics

Lecture 86 Some Important Terms To Understand Phylogenetic Tree

Lecture 87 Different Type of Phylogenetic Trees

Lecture 88 Steps To Construct Phylogenetic Tree

Lecture 89 Selection of Molecular Marker for Tree Construction

Lecture 90 Alignment for Tree Construction

Lecture 91 Evolutionary Model Selection

Lecture 92 Methods To Construct Tree

Lecture 93 Validation of Tree By Bootstrapping

Lecture 94 Practical -19: Building Phylogenetic Tree

Section 6: Module 6 (Optional)

Lecture 95 Practical-22: How to install Linux in Windows for Bioinformatics Analysis

Lecture 96 Practical-23: How to Install Gromacs in Windows

Lecture 97 Practical-24: How to Download Chemsketch

Lecture 98 Practical-25: Ligand Drawing and Making of Ligand 3D Structure

Section 7: Recent Updates In Bioinformatics

Lecture 99 Recent Update About Protein Databank

Lecture 100 How to Use AI to Do Literature Review Smartly

Beginners from Biological sciences,Data Science beginners who are interested in biological data

Course Information:

Udemy | English | 7h 21m | 4.78 GB
Created by: Muhammad Dujana

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