Bioinformatics Data Analysis: Master Python, R and Linux

سرفصل های دوره

Mastering Python, R, and Bash for Efficient Biological Data Processing and Analysis

1. Introduction

1. Introduction to bioinformatics scripting

2. Introduction to bash for bioinformatics

1. Introduction to linux (bash for bioinformatics)

2. Bash Basic Commands

3. Ncbi E-utilities on bash (Sequence Analysis)

4. Famous Bioinformatics Tools (Installation and Introduction)

5. Blast for Linux (Sequences Homology)

6. Sequence Alignment Analysis

7. Phylogenetic Analysis (Tree Construction)

8. GitHub Repository.html

3. GitHub for Bioinformatics (Not Compulsory)

1. Introducing GitHub

2. Profile and first Repository Setup

3. Bioinformatics Projects Hunting

4. Cloning and Forking Repositories

5. Collaborating on GitHub

6. GitHub for Project Mangement

4. CLI in Bioinformatics (Not Compulsory)

1. Introduction and Why CLI in Bioinformatics

2. CLI and GUI Explanation

3. if we already have Graphical user interface system why we should use CLI

4. Short Practical with Programming Language

5. Why Would You Use CLI over GUI

6. Foundation behind CLI Shell explanation

7. Drawbacks of CLI and GUI

8. Linux Introduction and Usage Over years

9. Linux Distros

10. Why Ubuntu Operating System

11. WSL Explanation

12. Linux Vs Unix

5. WSL as Linux Alternative on Windows

1. (Practical) Making A Subsystem For Linux In Windows OS

2. Linux File Handling Commands

3. Accessing And Creating Files In Windows Os

4. Basic Process Management Commands for Linux OS

5. E-Direct Introduction

6. Installing NCBI through CLi

7. Code Used in Lectures.html

8. Entrez Direct Functions

9. Mrna And Protein Seq Retrieval

10. Batch Retrieval of Protein Using Taxon Id

11. Retrieving CDS From Reference Genome

12. Explaining Different Commands

6. Bioinformatics Pipeline

1. Pipeline Explanation

7. NGS data Analysis on Bash

1. Introduction

2. Getting the SRA Reads

3. Checking the Quality of Data

4. Quality Trimming of data

5. Aligners and Aligning Reads to genome

6. SAM and Bam File Indexing and Sorting

7. Feature Extraction

8. Pipeline Code.html

8. Variant Calling analysis on Bash

1. Introduction

2. Variants and Types

3. Understanding the Metadata and Softwares

4. Getting Data From SRA Using SRA Toolkit

5. Quality Control and Trimming

6. Sam and Bcf Tools and Fixing NS and Calling Variants

7. Alignment to Reference Genome

8. Separation of SNPs and Indels Variants

9. Visualizing Variants Using IGV and UCSC Browser

10. Pipeline Code.html

9. Python Section

1. Introduction to Bioinformatics and Why Python

2. BioPython Introduction

3. GitHub Repository for Python.html

4. Setting up Coding Environment

5. Explaining the libraries for the course

6. Advance File Formats of Bioinformatics with BioPython

7. Sequence Analysis Using Biopython

8. Database RetrievalAccessing Using Biopython

9. Working With Genomes Using Biopython

10. Phylogenetic Tree Construction using Biopython

11. Proteomics Analysis Using Biopython

12. Machine Learning in Bioinformatics

10. R Section

1. Introduction to Bioinformatics and R Exploring the Intersection of Biology

2. Getting Started with R Installation and Variables Understanding

3. Working with R Packages Installing, Loading, and Exploring Bioinformatics

4. Differential Gene Expression Analysis with Deseq2 Preparing Data

5. Deseq2 Code Understanding

6. Converting Ensembl Gene IDs to Gene Symbols Using R Techniques and Packages

7. Visualizing Gene Expression Data Creating Stunning Plots with ggplot2

8. Introduction to Single-Cell RNA Sequencing (scRNA-seq) Data Analysis

9. Exploring scRNA-seq Code Cell Trajectories and Gene Expression Dynamics

10. GitHub Source Code for R.html

11. Microarray Data Analysis Using R

1. Introduction of Microarray

2. Microarray Databases

3. Microarray Analysis Using GEO2R

4. Microarray Analysis on R

5. Source Code for Microarray Section.html

12. Thank You for taking the Course

1. Thankyou Note.html

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تولید کننده: Udemy