Bioinformatics Mastery: Your journey from beginner to Expert

سرفصل های دوره

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

1 - Introduction to Bioinformatics

1 - Course Introduction

2 - Introduction of Bioinformatics field

3 - History of Bioinformatics

4 - Components of bioinformatics

5 - Working in Bioinformatics

6 - Career Outlook for bioinformaticians

7 - Careers for bioinformaticians

8 - Applications of Bioinformatics

9 - Applications of Bioinformatics Pt2

2 - Bioinformatics Databases and File Formats

10 - Introduction of Biological Databases

11 - Types of Biological Databases

12 - Difference Between Primary and Secondary Databases

13 - Primary Databases

14 - Explaining Primary Databases

15 - Explaining Primary Databases pt2

16 - Explaining Primary Databases Last

17 - Introduction of Secondary Databases

18 - Explaining Secondary Databases

19 - Explaining Secondary Databases pt2

20 - Explaining Secondary Databases Pt3

21 - Explaining Secondary Databases Pt4

22 - Introduction of Literature Databases

23 - Explaining Literature Databases

24 - Introduction of File Formats

25 - Explaining different File Formats

26 - Summary of File Formats

3 - Plant Databases

27 - Plant database introduction

28 - Types Of Databases

29 - Brassica Database

30 - Phytozome

31 - Ensembl Plants

32 - Gsad Database

33 - NCBI Database

34 - Pgdjb Database

35 - Ptgbase Database

36 - Rdna Database

37 - Gdb Browser

4 - Sequence Alignment in Bioinformatics

38 - Introduction of Sequence Alignment

39 - History of Sequence Alignment

40 - Alignment Methods

41 - Interpretation of Sequence Alignment

42 - Representation and Storing of Sequences

43 - Significance and Uses of Sequence Alignment

44 - Software Used for Sequence Alignment

45 - Pairwise Sequence Alignment

46 - Tools for Pairwise Sequence Alignment

47 - Multiple Sequence Alignment

48 - Tools for Multiple Sequence Alignment

49 - Clustal tool for alignment

5 - Proteomics Using Bioinformatics

50 - Section Introduction

51 - Explaining Homology Modeling

52 - GUI based Modeling of Proteins

53 - Command Line based Protein Modeling

53 - protein.zip

54 - DeNovo and Machine Learning Methods

55 - Protein Structure Prediction

56 - Protein Visualization Analysis

57 - Phylogenetics Analysis

58 - Motifs and Domains analysis

59 - Protein Physical Parameters and Location Analysis

60 - ProteinProtein Interaction and Enrichment Analysis

61 - Proteins Pathway Analysis

6 - Linux in Bioinformatics Command Line Bioinformatics

62 - Introduction and Why CLI in Bioinformatics

63 - CLI and GUI Explanation

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

65 - Short Practical with Programming Language

66 - Why Would You Use CLI over GUI

67 - Foundation behind CLI Shell explanation

68 - Drawbacks of CLI and GUI

69 - Linux Introduction and Usage Over years

70 - Linux Distros

71 - Why Ubuntu Operating System

72 - WSL Explanation

73 - Linux Vs Unix

74 - Practical Making A Subsystem For Linux In Windows OS

75 - Linux File Handling Commands

76 - Accessing And Creating Files In Windows Os

77 - Basic Process Management Commands for Linux OS

78 - Eutilities on the Linux Command Line

79 - Installing NCBI through CLi

80 - Entrez Direct Functions

81 - Mrna And Protein Seq Retrieval

82 - Batch Retrieval of Protein Using Taxon Id

83 - Retrieving CDS From Reference Genome

84 - Explaining Different Commands

85 - Commands.html

7 - NGS Data Analysis using Galaxy and Linux

86 - Introduction of Course Section

87 - Nextgeneration sequencing

88 - Generations of Sequencing

89 - NGS Workflow

90 - SRA Database introduction

91 - SRA File

92 - Galaxy Server Intro to Goals

93 - Galaxy Server And Objects

94 - Getting Onto Galaxy

95 - Tools For NGS Data Analysis

96 - Getting SRA Runs from Databases And platform

97 - Ncbi Genome to Galaxy

98 - Getting Sra Runs To Galaxy

99 - Fastqc Tool To Dataset Generated Dataset

100 - Trimmomatic Tool On Dataset

101 - Alignmentgenome Mapping

102 - Abundance Estimation Tool On Dataset

103 - From Values To Visuals Heatmap

104 - Understanding NGS For Linux

105 - Getting the SRA Reads

105 - file.zip

106 - Bioinformatics Pipeline

107 - Checking the Quality of Data

108 - Quality Trimming of data

109 - Aligners and Aligning Reads to genome

110 - SAM and Bam File Indexing and Sorting

111 - Feature Extraction

112 - Pipeline Code.html

8 - Variant Calling Analysis Using Linux

113 - Introduction of Course Section

114 - Variants and Types

115 - Understanding the Metadata and Softwares

116 - Getting Data From SRA Using SRA Toolkit

117 - Quality Control and Trimming

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

119 - Alignment to Reference Genome

120 - Separation of SNPs and Indels Variants

121 - Visualizing Variants Using IGV and UCSC Browser

122 - Pipeline Code.html

9 - Python for Bioinformatics

123 - Introduction to Bioinformatics and Why Python

124 - BioPython Introduction

125 - GitHub Repository for Python.html

126 - Setting up Coding Environment

127 - Explaining the libraries for the course

128 - Advance File Formats of Bioinformatics with BioPython

129 - Sequence Analysis Using Biopython

130 - Database RetrievalAccessing Using Biopython

131 - Working With Genomes Using Biopython

132 - Phylogenetic Tree Construction using Biopython

133 - Proteomics Analysis Using Biopython

134 - Machine Learning in Bioinformatics

10 - R for Bioinformatics

135 - Introduction to Bioinformatics and R Exploring the Intersection of Biology

136 - Getting Started with R Installation and Variables Understanding

137 - Working with R Packages Installing Loading and Exploring Bioinformatics

138 - Differential Gene Expression Analysis with Deseq2 Preparing Data

139 - Deseq2 Code Understanding

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

141 - Visualizing Gene Expression Data Creating Stunning Plots with ggplot2

142 - Introduction to SingleCell RNA Sequencing scRNAseq Data Analysis

143 - Exploring scRNAseq Code Cell Trajectories and Gene Expression Dynamics

144 - GitHub Source Code for R.html

11 - Microarray Data Analysis Using R

145 - Introduction of Microarray

146 - Microarray Databases

147 - Microarray Analysis Using GEO2R

148 - Microarray Analysis on R

149 - Source Code for Microarray Section.html

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تولید کننده: Udemy