oaxino Posted March 29 Report Share Posted March 29 Complete Bioinformatics Practical Bootcamp From Zero To HeroPublished 3/2024MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHzLanguage: English | Size: 12.33 GB | Duration: 16h 52mThe Complete Hands-On Bioinformatics Practical Bootcamp Training for Students, Academia, and Industry ProfessionalsWhat you'll learnLearn Basic Theory & Practical demonstration of Bioinformatics techniques on both command line and graphical user interfaceLearn how to explore biological databases and retrieve data using databases and their toolsLearn how to align biological sequences using pairwise and multiple alignment method on both graphical user interface and command line interfaceLearn how to perform genomics analysis like prediction of genes, genome annotation, Intron and exon analysis, gene location and gene enrichment using bioinformaLearn how to perform evolutionary bioinformatics analysis also called phylogenetic analysis on both command line and graphical user interfaceLearn to perform proteomics bioinformatics analysis like motifs and domain finding, protein physical parameters, protein-protein interaction, protein enrichmentLearn about structural bioinformatics where you will learn homology modeling on GUI and CLI platforms also you will be able to predict 3D structure of proteinsLearn how to use command line in bioinformatics how to linux subsystem in windows learn some basic use of bash, perform database searching analysis using NCBI ELearn how to use transcriptomics data and for NGS and variant calling analysisLearn how to Use R for bioinformatics install packages make some interesting plots with ggplot2 get familiar with Single Cell RNA and perform Gene expression daLearn how to Use python for bioinformatics use biopython library for sequence analysis, working with genomes, phylogenetics, proteomics and machine learningBuild your very own pipeline for RNA-Seq and variant calling analysis by using LinuxBuild Codes for R and Python to perform Automation in bioinformatics analysisAll the codes and pipelines used in the course will be available to all the studentsRequirementsBasic knowledge of biology: Understanding of biological concepts such as genes, proteins, and genomes.Basic computer skills: Ability to navigate and use a computer, as well as familiarity with software installation.Basic understanding of statistics: Knowledge of basic statistical concepts used in bioinformatics analysis.Familiarity with programming concepts: Basic understanding of programming concepts such as variables, loops, and functions.Familiarity with the command line interface (CLI): Basic knowledge of using the command line for tasks such as file navigation and manipulation.DescriptionEmbark on a journey into the world of bioinformatics with our Complete Bioinformatics Practical Bootcamp from Zero to Hero! This comprehensive training bootcamp is designed for students, academia, and industry professionals looking to extend their understanding of biological data and excel in the field of bioinformatics.Explore the bioinformatics world through hands-on, practical demonstrations that bridge theory with real-world applications. Learn to navigate biological databases, align sequences, and analyze genomics data using cutting-edge tools and techniques. Dive into proteomics, structural bioinformatics, and evolutionary analysis to uncover the hidden secrets of life's building blocks.Our course is designed to equip you with the fundamental skills needed for becoming a excellent computational data analyst. You'll delve into ten key modules:Biological DatabasesSequence AlignmentGenomic BioinformaticsProteomic BioinformaticsEvolutionary BioinformaticsStructural BioinformaticsCommand Line Bioinformatics (Linux for bioinformatics)Transcriptomics BioinformaticsR language for BioinformaticsPython language for BioinformaticsThis unique blend of theory and practical application will empower you to handle biological data with confidence. With 103 lectures, including practical tutorials, 10 assignments, and 11 quizzes and a final project for making your own bioinformatics pipeline for RNA-Seq data analysis on bash, you'll gain a comprehensive understanding of bioinformatics tools and techniques.From biological databases to building your own pipeline for data analysis, you'll explore a variety of tools that are freely available and closely related to the course material. Some tools may require sign-up, but most will be accessible without any registration. All the codes used will be available to GitHub.By the end of this course, you'll see biological data in a whole new light. We believe this investment in your education will be both valuable and rewarding. Don't miss out on this opportunity to transform your bioinformatics skills.Sign up today and take the first step towards mastering bioinformatics!OverviewSection 1: Module 1: Introduction to Bioinformatics (Theory)Lecture 1 Introduction to BioinformaticsLecture 2 Goals, Scope and Applications of BioinformaticsSection 2: Module 2: Biological Databases (Theory and Practical)Lecture 3 Introduction to Databases and Bioinformatics DatabasesLecture 4 Types of DatabasesLecture 5 Practical: Primary Databases & NCBI DatabaseLecture 6 Practical: Embl DatabaseLecture 7 Practical: Ddbj DatabaseLecture 8 Practical: Secondary Databases and PDB DatabaseLecture 9 Practical: Uniprot DatabaseLecture 10 Practical: GEO DatabaseLecture 11 Derived Databases IntroductionLecture 12 Practical: Derived DatabasesLecture 13 Practical: Literature Specialized DatabasesLecture 14 GitHub RepositorySection 3: Module 3: Biological Sequence Alignment (Theory and Practical)Lecture 15 Introduction to Sequence Alignment and Pairwise AlignmentLecture 16 Practical: Pairwise Sequence AlignmentLecture 17 Introduction to Homology Searching and BlastLecture 18 Practical: Homology Searching and BlastLecture 19 Introduction to Multiple Sequence AlignmentLecture 20 Practical: Multiple Sequence AlignmentLecture 21 GitHub RepositorySection 4: Module 4: Genomics Bioinformatics (Theory and Practical)Lecture 22 Introduction to Genomics for BioinformaticsLecture 23 Introduction to Gene PredictionLecture 24 Practical: Prediction of Prokaryotic and Eukaryotic GenesLecture 25 Practical: Genome Annotation and visualizationLecture 26 Practical: Intron and Exon AnalysisLecture 27 Practical: Gene location on Chromosome AnalysisLecture 28 Practical: Gene Enrichment AnalysisLecture 29 GitHub RepositorySection 5: Module 5: Evolutionary Bioinformatics (Theory and Practical)Lecture 30 Introduction to PhylogeneticsLecture 31 Procedure and Tools for Constructing Phylogenetic TreesLecture 32 Practical: Phylogenetic Trees ConstructionLecture 33 Practical: Annotating Phylogenetic Trees for Publications and ResearchLecture 34 GitHub RepositorySection 6: Module 6: Proteomics Bioinformatics (Theory and Practical)Lecture 35 Course Introduction and Sequences AnalysisLecture 36 Practical: Phylogenetic AnalysisLecture 37 Practical: Motifs and Domains analysisLecture 38 Practical: Protein Physical Parameters and Location AnalysisLecture 39 Practical: Protein-Protein Interaction and Enrichment AnalysisLecture 40 Practical: Proteins Pathway AnalysisLecture 41 Practical: Protein Structure PredictionLecture 42 Practical: Proteins Visualization AnalysisSection 7: Module 7: Structural Bioinformatics (Theory and Practical)Lecture 43 Introduction to Structural BioinformaticsLecture 44 Explaining Homology ModelingLecture 45 Practical: GUI based Modeling of ProteinsLecture 46 Practical: Command Line based Protein ModelingLecture 47 Practical: Performing Protein Prediction through ML and De novo MethodsLecture 48 GitHub RepositorySection 8: M8: Command Line Bioinformatics (Linux for Bioinformatics) Theory and PracticalLecture 49 Introduction to Linux and Command line in bioinformaticsLecture 50 Practical: Making Subsystem for Linux in Windows OSLecture 51 Practical: Bash Basic CommandsLecture 52 Practical: Ncbi E-utilities on bash (Sequence Analysis)Lecture 53 Practical: Famous Bioinformatics Tools (Installation and Introduction)Lecture 54 Practical: Blast for Linux (Sequences Homology)Lecture 55 Practical: Sequence Alignment AnalysisLecture 56 Practical: Phylogenetic Analysis (Tree Construction)Lecture 57 GitHub RepositorySection 9: Module 9: Transcriptomics Bioinformatics (Theory and Practical)Lecture 58 Introduction to Transcriptomics and RNA-SeqLecture 59 Understanding Bioinformatics PipelinesLecture 60 What is SRA Database and SRA-toolkitLecture 61 Practical: Getting the SRA Reads for RNA-Seq DataLecture 62 Practical: Checking the Quality of DataLecture 63 Practical: Quality Trimming of dataLecture 64 Practical: Aligners and Aligning Reads to genomeLecture 65 Practical: SAM and Bam File Indexing and SortingLecture 66 Practical: Feature ExtractionLecture 67 Introduction to Variant Calling for BioinformaticsLecture 68 Variants and TypesLecture 69 Understanding the Metadata and Software'sLecture 70 Practical: Getting Data From SRA Using SRA ToolkitLecture 71 Practical: Quality Control and TrimmingLecture 72 Practical: Alignment to Reference GenomeLecture 73 Practical: Sam and Bcf Tools and Fixing NS and Calling VariantsLecture 74 Practical: Separation of SNP's and Indels VariantsLecture 75 Practical: Visualizing Variants Using IGV and UCSC BrowserLecture 76 GitHub RepositorySection 10: Module 10: The Final ProjectLecture 77 Final Project InstructionsSection 11: Module 11: R for Bioinformatics (Theory and Practical)Lecture 78 Introduction to Bioinformatics and RLecture 79 Practical: Getting Started with R: InstallationLecture 80 Practical: Working with R Packages: Installing and Loading PackagesLecture 81 Differential Gene Expression Analysis with Deseq2: Preparing DataLecture 82 Practical: Deseq2 Code UnderstandingLecture 83 Practical: Converting Ensembl Gene IDs to Gene SymbolsLecture 84 Practical: Visualizing Gene Expression Data: Creating Stunning PlotsLecture 85 Introduction to Single-Cell RNA Sequencing (scRNA-seq) Data AnalysisLecture 86 Practical: Exploring scRNA-seq Code: Cell Trajectories and Gene ExpressionLecture 87 GitHub RepositorySection 12: Module 11: Microarray Data Analysis (Theory and Practical)Lecture 88 Introduction of MicroarrayLecture 89 Microarray DatabasesLecture 90 Practical: Microarray Analysis Using GEO2RLecture 91 Practical: Microarray Analysis on RLecture 92 GitHub RepositorySection 13: Module 12: Python Section (Theory and Practical)Lecture 93 BioPython IntroductionLecture 94 Practical: Setting up Coding EnvironmentLecture 95 Explaining the libraries for the courseLecture 96 Practical: Advance File Formats of Bioinformatics with BioPythonLecture 97 Practical: Sequence Analysis Using BiopythonLecture 98 Practical: Database Retrieval/Accessing Using BiopythonLecture 99 Practical: Working With Genomes Using BiopythonLecture 100 Practical: Phylogenetic Tree Construction using BiopythonLecture 101 Practical: Proteomics Analysis Using BiopythonLecture 102 Practical: Machine Learning in BioinformaticsLecture 103 GitHub RepositoryStudents: Undergraduate or graduate students studying biology, bioinformatics, or related fields who want to enhance their bioinformatics skills.,Professionals: Working professionals in the fields of biology, genetics, or biotechnology who want to learn bioinformatics for their research or career advancement.,Researchers: Scientists and researchers who want to incorporate bioinformatics into their research projects.,Data Analysts: Professionals working with biological data who want to learn bioinformatics tools and techniques for data analysis.,Enthusiasts: Individuals with a keen interest in biology and bioinformatics who want to explore the field and learn new 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