Канал: Danny Arends

Principal Component Analysis from Scratch

Principal Component Analysis from Scratch

Enrichment (or over-representation) Analysis from Scratch

Enrichment (or over-representation) Analysis from Scratch

Setting up a local Large Language Model (LLM)

Setting up a local Large Language Model (LLM)

Hi! I'm a bioinformatician, AMA!

Hi! I'm a bioinformatician, AMA!

RNA Sequencing - Read counts, RPKM, Volcano plot, and a Heatmap

RNA Sequencing - Read counts, RPKM, Volcano plot, and a Heatmap

RNA Sequencing - Building a FASTQ to BAM pipeline

RNA Sequencing - Building a FASTQ to BAM pipeline

RNA Sequencing - Setup and Prerequisites

RNA Sequencing - Setup and Prerequisites

Dutch German Friendship - Viewer Reward 4

Dutch German Friendship - Viewer Reward 4

Create an R package and Overview - Lecture 11 - Data analysis using R

Create an R package and Overview - Lecture 11 - Data analysis using R

Common idioms - Lecture 10 - Data analysis using R

Common idioms - Lecture 10 - Data analysis using R

Linear Mixed Models (LMM) - Lecture 9 - Data analysis using R

Linear Mixed Models (LMM) - Lecture 9 - Data analysis using R

Regression - Lecture 8 - Data analysis using R

Regression - Lecture 8 - Data analysis using R

Algorithms & Functions - Lecture 7 - Data analysis using R

Algorithms & Functions - Lecture 7 - Data analysis using R

Statistical testing - Lecture 6 - Data analysis using R

Statistical testing - Lecture 6 - Data analysis using R

R - Monkeypox Genetics

R - Monkeypox Genetics

Plots Plots Plots - Lecture 5 - Data analysis using R

Plots Plots Plots - Lecture 5 - Data analysis using R

Descriptive statistics - Lecture 4 - Data analysis using R

Descriptive statistics - Lecture 4 - Data analysis using R

Dealing with Data - Lecture 3 - Data analysis using R

Dealing with Data - Lecture 3 - Data analysis using R

Variables, Control structures & Functions - Lecture 2 - Data analysis using R

Variables, Control structures & Functions - Lecture 2 - Data analysis using R

History & Introduction - Lecture 1 - Data analysis using R

History & Introduction - Lecture 1 - Data analysis using R

YouTube Test Stream - Data analysis using the R language

YouTube Test Stream - Data analysis using the R language

30min PhD thesis - Correlated Trait Locus (CTL) mapping

30min PhD thesis - Correlated Trait Locus (CTL) mapping

The next R course - Your Feedback and Suggestions!

The next R course - Your Feedback and Suggestions!

Summary and Example Exam Questions (Bioinformatics S15E2)

Summary and Example Exam Questions (Bioinformatics S15E2)

Course Summary - (Bioinformatics S15E1)

Course Summary - (Bioinformatics S15E1)

Citations, Reference Managers, and Version Control (Bioinformatics S14)

Citations, Reference Managers, and Version Control (Bioinformatics S14)

Volcano plot in R - (Bioinformatics - Answers S12)

Volcano plot in R - (Bioinformatics - Answers S12)

DNA Metabarcoding of eDNA/eRNA (Bioinformatics S14E1)

DNA Metabarcoding of eDNA/eRNA (Bioinformatics S14E1)

Standards for Analysis (Bioinformatics S13E1)

Standards for Analysis (Bioinformatics S13E1)

An R package in 15 minutes (Bioinformatics S13E2)

An R package in 15 minutes (Bioinformatics S13E2)

Camera Trap Image Analysis at the Chinko Nature Reserve (Bioinformatics)

Camera Trap Image Analysis at the Chinko Nature Reserve (Bioinformatics)

Gene Ontology and mRNA visualization (Bioinformatics S12E2)

Gene Ontology and mRNA visualization (Bioinformatics S12E2)

Gene Expression Analysis (Bioinformatics S12E1)

Gene Expression Analysis (Bioinformatics S12E1)

Answers S11 - MSA Assignment in R (Bioinformatics)

Answers S11 - MSA Assignment in R (Bioinformatics)

Multiple Sequence Alignment (MSA) in R (Bioinformatics S11E2)

Multiple Sequence Alignment (MSA) in R (Bioinformatics S11E2)

Sequence Alignment, Scoring, and Analysis (Bioinformatics S11E1)

Sequence Alignment, Scoring, and Analysis (Bioinformatics S11E1)

Answers S10, PubMed, biomaRt, and BLAST - (Bioinformatics S11E0)

Answers S10, PubMed, biomaRt, and BLAST - (Bioinformatics S11E0)

SNP chip data, PCA, and biomaRt in R (Bioinformatics S10E3)

SNP chip data, PCA, and biomaRt in R (Bioinformatics S10E3)

Databases and biomaRt (Bioinformatics S10E2)

Databases and biomaRt (Bioinformatics S10E2)

Databases and biomaRt (Bioinformatics S10E1)

Databases and biomaRt (Bioinformatics S10E1)

Primer Design for RNA/DNA amplification (Bioinformatics S9E3)

Primer Design for RNA/DNA amplification (Bioinformatics S9E3)

Primer Design for RNA/DNA amplification (Bioinformatics S9E2)

Primer Design for RNA/DNA amplification (Bioinformatics S9E2)

Primer Design for RNA/DNA amplification (Bioinformatics S9E1)

Primer Design for RNA/DNA amplification (Bioinformatics S9E1)

Correlated Trait Locus (CTL) mapping (Bioinformatics S8Ex)

Correlated Trait Locus (CTL) mapping (Bioinformatics S8Ex)

QTL mapping and GWAS (Bioinformatics S8E2)

QTL mapping and GWAS (Bioinformatics S8E2)

QTL mapping and GWAS (Bioinformatics S8E1)

QTL mapping and GWAS (Bioinformatics S8E1)

Answers S6 - Pathway analysis (Bioinformatics S8E0)

Answers S6 - Pathway analysis (Bioinformatics S8E0)

Introduction into R - Regression (Bioinformatics S7E3)

Introduction into R - Regression (Bioinformatics S7E3)

Introduction into R - Basics 2 (Bioinformatics S7E2)

Introduction into R - Basics 2 (Bioinformatics S7E2)

Pufferfish - Viewer Reward 3

Pufferfish - Viewer Reward 3

Introduction into R - Basics 1 (Bioinformatics S7E1)

Introduction into R - Basics 1 (Bioinformatics S7E1)

Metabolome and pathways (Bioinformatics S6E3)

Metabolome and pathways (Bioinformatics S6E3)

Betta Mahachaiensis - Viewer Reward 2

Betta Mahachaiensis - Viewer Reward 2

Guinea pig - Viewer Reward 1

Guinea pig - Viewer Reward 1

Metabolites and Mass Spectrometry (Bioinformatics S6E2)

Metabolites and Mass Spectrometry (Bioinformatics S6E2)

Metabolome and Pathways (Bioinformatics S6E1)

Metabolome and Pathways (Bioinformatics S6E1)

Protein Homology and Phylogeny (Bioinformatics S5E4)

Protein Homology and Phylogeny (Bioinformatics S5E4)

Protein identification and structure (Bioinformatics S5E3)

Protein identification and structure (Bioinformatics S5E3)

From Amino Acid to Protein Structures (Bioinformatics S5E2)

From Amino Acid to Protein Structures (Bioinformatics S5E2)

Answers S4 and Protein lecture overview (Bioinformatics S5E1)

Answers S4 and Protein lecture overview (Bioinformatics S5E1)

The bioinformatics side of RNA (Bioinformatics S4E3)

The bioinformatics side of RNA (Bioinformatics S4E3)

RNA, Ribosomes, Splicing and Ribozymes (Bioinformatics S4E2)

RNA, Ribosomes, Splicing and Ribozymes (Bioinformatics S4E2)

Answers S3 & RNA lecture overview (Bioinformatics S4E1)

Answers S3 & RNA lecture overview (Bioinformatics S4E1)

DNA, Sequencing, and Gene Structure (Bioinformatics S3E4)

DNA, Sequencing, and Gene Structure (Bioinformatics S3E4)

DNA, Sequencing, and Gene Structure (Bioinformatics S3E3)

DNA, Sequencing, and Gene Structure (Bioinformatics S3E3)

DNA, Sequencing, and Gene Structure (Bioinformatics S3E2)

DNA, Sequencing, and Gene Structure (Bioinformatics S3E2)

DNA, Sequencing, and Gene Structure (Bioinformatics S3E1)

DNA, Sequencing, and Gene Structure (Bioinformatics S3E1)

Phenotypes and Genetic Analysis (Bioinformatics S2E4)

Phenotypes and Genetic Analysis (Bioinformatics S2E4)

Phenotypes and Genetic Analysis (Bioinformatics S2E3)

Phenotypes and Genetic Analysis (Bioinformatics S2E3)

Phenotypes and Genetic Analysis (Bioinformatics S2E2)

Phenotypes and Genetic Analysis (Bioinformatics S2E2)

Phenotypes and Genetic Analysis (Bioinformatics S2E1)

Phenotypes and Genetic Analysis (Bioinformatics S2E1)

Your software stack: GitHub - ADVANCED (Bioinformatics S1E3)

Your software stack: GitHub - ADVANCED (Bioinformatics S1E3)

History & Introduction (Bioinformatics S1E2)

History & Introduction (Bioinformatics S1E2)

History & Introduction (Bioinformatics S1E1)

History & Introduction (Bioinformatics S1E1)

Fishy Data - Data Analysis using R - Part 3

Fishy Data - Data Analysis using R - Part 3

Fishy Data - Data Analysis using R - Part 2

Fishy Data - Data Analysis using R - Part 2

Fishy Data - Data Analysis using R - Part 1

Fishy Data - Data Analysis using R - Part 1

Data analysis using R - Summary lectures 1 to 10 - Lecture 11 (Part 3)

Data analysis using R - Summary lectures 1 to 10 - Lecture 11 (Part 3)

Data analysis using R - Common idioms - Lecture 11 (Part 2)

Data analysis using R - Common idioms - Lecture 11 (Part 2)

Data analysis using R - Generalized linear models - Lecture 11 (Part 1)

Data analysis using R - Generalized linear models - Lecture 11 (Part 1)

Data analysis using R - Linear mixed model example in the BFMI - Lecture 10 (Part 3)

Data analysis using R - Linear mixed model example in the BFMI - Lecture 10 (Part 3)

Data analysis using R - Mixed Models - Lecture 10 (Part 2)

Data analysis using R - Mixed Models - Lecture 10 (Part 2)

Data analysis using R - Answers to Assignment 9 - Lecture 10 (Part 1)

Data analysis using R - Answers to Assignment 9 - Lecture 10 (Part 1)

Data analysis using R - Answers and Regression Analysis - Lecture 9 (Part 1)

Data analysis using R - Answers and Regression Analysis - Lecture 9 (Part 1)

Data analysis using R - Introduction to regression - Lecture 9 (Part 2)

Data analysis using R - Introduction to regression - Lecture 9 (Part 2)

Data analysis using R - Block Designs - Lecture 8 (Part 3)

Data analysis using R - Block Designs - Lecture 8 (Part 3)

Data analysis using R - Create an R package - Lecture 8 (Part 2)

Data analysis using R - Create an R package - Lecture 8 (Part 2)

Data analysis using R - Answers to Assignment 7 - Lecture 8 (Part 1)

Data analysis using R - Answers to Assignment 7 - Lecture 8 (Part 1)

Data analysis using R - Function scope and recursion - Lecture 7 (Part 3)

Data analysis using R - Function scope and recursion - Lecture 7 (Part 3)

Data analysis using R - Algorithms and Design Patterns - Lecture 7 (Part 2)

Data analysis using R - Algorithms and Design Patterns - Lecture 7 (Part 2)

Data analysis using R - Answers to Assignment 6 - Lecture 7 (Part 1)

Data analysis using R - Answers to Assignment 6 - Lecture 7 (Part 1)

Data analysis using R - (Non-)parametric statistical testing - Lecture 6 (Part 3)

Data analysis using R - (Non-)parametric statistical testing - Lecture 6 (Part 3)

Data analysis using R - Microarray analysis and statistical testing - Lecture 6 (Part 2)

Data analysis using R - Microarray analysis and statistical testing - Lecture 6 (Part 2)

Data analysis using R - Answers to Assignment 5 - Lecture 6 (Part 1)

Data analysis using R - Answers to Assignment 5 - Lecture 6 (Part 1)

Data analysis using R - Phylogenetic trees and custom plots - Lecture 5 (Part 2)

Data analysis using R - Phylogenetic trees and custom plots - Lecture 5 (Part 2)

Data analysis using R - Plots Plots Plots - Lecture 5 (Part 1)

Data analysis using R - Plots Plots Plots - Lecture 5 (Part 1)

Data analysis using R - Plotting descriptive statistics - Lecture 4 (Part 3)

Data analysis using R - Plotting descriptive statistics - Lecture 4 (Part 3)

Data analysis using R - Descriptive univariate statistics - Lecture 4 (Part 2)

Data analysis using R - Descriptive univariate statistics - Lecture 4 (Part 2)

Data analysis using R - Answers Assignment 3 - Lecture 4 (Part 1)

Data analysis using R - Answers Assignment 3 - Lecture 4 (Part 1)

Data analysis using R - Manage your (big) data - Lecture 3 (Part 3)

Data analysis using R - Manage your (big) data - Lecture 3 (Part 3)

Data analysis using R - Books, loading text and binary data - Lecture 3 (Part 2)

Data analysis using R - Books, loading text and binary data - Lecture 3 (Part 2)

Data analysis using R - Learn about data in R - Lecture 3 (Part 1)

Data analysis using R - Learn about data in R - Lecture 3 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 10 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 10 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 11 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 11 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 11 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 11 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 11 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 11 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 12 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 12 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 12 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 12 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 12 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 12 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 13 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 13 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 13 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 13 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 13 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 13 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 10 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 10 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 10 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 10 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 9 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 9 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 9 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 9 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 9 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 9 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 8 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 8 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 8 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 8 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 8 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 8 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 7 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 7 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 7 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 7 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 7 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 7 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 6 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 6 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 6 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 6 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 6 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 6 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 5 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 5 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 5 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 5 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 5 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 5 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 4 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 4 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 4 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 4 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 4 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 4 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 3 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 3 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 3 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 3 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 3 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 3 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 2 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 2 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 2 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 2 (Part 3)

Bioinformatics for plant and animal sciences - Lecture 2 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 2 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 1 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 1 (Part 2)

Bioinformatics for plant and animal sciences - Lecture 1 (Part 1)

Bioinformatics for plant and animal sciences - Lecture 1 (Part 1)

Data analysis using R - Advanced functions - Lecture 2 (Part 3)

Data analysis using R - Advanced functions - Lecture 2 (Part 3)

Data analysis using R - Writing Functions - Lecture 2 (Part 2)

Data analysis using R - Writing Functions - Lecture 2 (Part 2)

Data analysis using R - Answers, Branching, and Looping - Lecture 2 (Part 1)

Data analysis using R - Answers, Branching, and Looping - Lecture 2 (Part 1)

Data analysis using R - Data types, variables, and reusable code - Lecture 1 (Part 3)

Data analysis using R - Data types, variables, and reusable code - Lecture 1 (Part 3)

Data analysis using R - Your first R script - Lecture 1 (Part 2)

Data analysis using R - Your first R script - Lecture 1 (Part 2)

Data analysis using R - Course overview - Lecture 1 (Part 1)

Data analysis using R - Course overview - Lecture 1 (Part 1)