Acerca de este curso: This course introduces you to the basic biology of modern genomics and the experimental tools that we use to measure it. We'll introduce the Central Dogma of Molecular Biology and cover how next-generation sequencing can be used to measure DNA, RNA, and epigenetic patterns. You'll also get an introduction to the key concepts in computing and data science that you'll need to understand how data from next-generation sequencing experiments are generated and analyzed. This is the first course in the Genomic Data Science Specialization.
Creada por: Johns Hopkins University
Enseñado por: Steven Salzberg, PhD, Professor
Biomedical Engineering, Computer Science, and Biostatistics
Enseñado por: Jeff Leek, PhD, Associate Professor, Biostatistics
Bloomberg School of Public Health
| Información básica | Curso 1 de 8 en Genomic Data Science Specialization |
| Idioma | English |
| Cómo aprobar | Aprueba todas las tareas calificadas para completar el curso. |
| Calificaciones del usuario |
Programa
SEMANA 1
Overview
In this Module, you can expect to study topics of "Just enough molecular biology", "The genome", "Writing a DNA sequence", "Central dogma", "Transcription", "Translation", and "DNA structure and modifications".
8 videos, 2 lecturas
- Reading: Syllabus
- Reading: Pre-Course Survey
- Vídeo: What Is Genomics?
- Vídeo: What Is Genomic Data Science?
- Vídeo: Just Enough Cell Biology
- Vídeo: Important Molecules in Molecular Biology
- Vídeo: The Human Genome Project
- Vídeo: Molecular Biology Structures
- Vídeo: From Genes to Phenotypes
Calificado: Quiz 1: Overview and Molecular Biology
SEMANA 2
Measurement Technology
In this module, you'll learn about polymerase chain reaction, next generation sequencing, and applications of sequencing.
3 videos
- Vídeo: Next Generation Sequencing
- Vídeo: Applications of Sequencing
Calificado: Quiz 2: Measurement Technology
SEMANA 3
Computing Technology
The lectures for this module cover a few basic topics in computing technology. We'll go over the foundations of computer science, algorithms, memory and data structures, efficiency, software engineering, and computational biology software.
6 videos
- Vídeo: Algorithms
- Vídeo: Memory and Data Structures
- Vídeo: Efficiency
- Vídeo: Software Engineering
- Vídeo: What is Computational Biology Software
Calificado: Quiz 3: Computing Technology
SEMANA 4
Data Science Technology
In this module on Data Science Technology, we'll be covering quite a lot of information about how to handle the data produced during the sequencing process. We'll cover reproducibility, analysis, statistics, question types, the central dogma of inference, analysis code, testing, prediction, variation, experimental design, confounding, power, sample size, correlation, causation, and degrees of freedom.
10 videos, 2 lecturas
- Vídeo: What Went Wrong?
- Vídeo: The Central Dogma of Statistics
- Vídeo: Data Sharing Plans
- Vídeo: Getting Help with Statistics
- Vídeo: Plotting Your Data
- Vídeo: Sample Size and Variability
- Vídeo: Statistical Significance
- Vídeo: Multiple Testing
- Vídeo: Study Design, Batch Effects, and Confounding
- Reading: Course Project Instructions and Reading
- Reading: Post-Course Survey
Calificado: Quiz 4: Data Science Technology
Calificado: Course Project
Preguntas Frecuentes
Cómo funciona
Coursework
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Creadores
Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Tarifa
| Comprar curso | |
|---|---|
| Accede a los materiales del curso | Disponible |
| Accede a los materiales con calificación | Disponible |
| Recibe una calificación final | Disponible |
| Obtén un Certificado de curso para compartir | Disponible |
Calificaciones y revisiones
A nice overview of all the subfields that make up bioinformatics.
it was interesting course but the part of statistics was severely complicated and should be taught in simple language.
Good course - solid theory, would like to see more projects than tests though. All in all, worthwhile.
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good