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

“آشنایی با متدولوژی Six Sigma” به سبد خرید شما اضافه شد. مشاهده سبد خرید

179,000 تومان

افزودن به سبد خرید

خرید دانلودی فوری

در این روش نیاز به افزودن محصول به سبد خرید و تکمیل اطلاعات نیست و شما پس از وارد کردن ایمیل خود و طی کردن مراحل پرداخت لینک های دریافت محصولات را در ایمیل خود دریافت خواهید کرد.

تولید کننده: Udemy