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Usama A. F. Khalil
By the end of this project, you will create a Python program using a jupyter interface that analyzes a group of viruses and plot a dendrogram based on similarities among them. The dendrogram that you will create will depend on the cumulative skew profile,...
Read more
By the end of this project, you will create a Python program using a jupyter interface that analyzes a group of viruses and plot a dendrogram based on similarities among them. The dendrogram that you will create will depend on the cumulative skew profile,...
Read more
By the end of this project, you will create a Python program using a jupyter interface that analyzes a group of viruses and plot a dendrogram based on similarities among them. The dendrogram that you will create will depend on the cumulative skew profile, which in turn depends on the nucleotide composition. You will use complete genome sequences for many viruses including, Corona, SARS, HIV, Zika, Dengue, enterovirus, and West Nile viruses.
Register for this course and see more details by visiting:
OpenCourser.com/course/qcoz9d/hierarchical
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Develops skills in coding, data analysis, and visualization, which are vital for diverse career paths
Uses real-world datasets and scenarios to make learning more engaging and applicable
Teaches Python, a widely used and versatile programming language
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Reviews summary
Difficult to understand lectures
This course has received mixed reviews, with the main complaint being that the lecturer is difficult to understand. One reviewer stated, "i cant understand the lecturer."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Hierarchical Clustering using Euclidean Distance with these
activities:
Python Programming Practice
Show steps
This course requires a strong foundation in Python programming. Practice writing Python code to improve your skills before taking the course
Browse courses on
Python Programming
Show steps
-
Solve Python coding problems on websites like HackerRank or LeetCode
-
Build small Python projects
-
Contribute to open source Python projects
Seek guidance from experts in the field
Show steps
Connects you with experienced professionals who can provide valuable advice and support, enriching your learning experience.
Show steps
-
Identify experts in the field of virus analysis and dendrogram creation
-
Reach out to potential mentors and request guidance
-
Schedule regular meetings or communication channels
Review of Genome Sequencing Techniques
Show steps
Before taking this course, you need to have a basic understanding of genome sequencing techniques. This knowledge will be essential for understanding the data that you will be analyzing in the course
Browse courses on
Genome Sequencing
Show steps
-
Read articles or books about genome sequencing
-
Watch videos about genome sequencing
-
Take an online course on genome sequencing
Ten other activities
Expand to see all activities and additional details
Show all 13 activities
Review Nucleotide composition and their analysis
Show steps
Review the concepts of nucleotide composition and their analysis to strengthen your foundational understanding in virology.
Browse courses on
Nucleotide Composition
Show steps
-
Revisit the structure and properties of nucleotides.
-
Explore different methods for analyzing nucleotide composition.
-
Practice analyzing nucleotide composition using online tools or software.
Review the basics of nucleotide composition
Show steps
Refreshes your understanding of nucleotide composition, which is essential for understanding cumulative skew profiles and dendrogram creation.
Browse courses on
Nucleotide Composition
Show steps
-
Review the structure and properties of nucleotides
-
Identify the different types of nucleotide bases
-
Calculate the nucleotide composition of a given DNA sequence
Engage in peer discussions on virus evolution
Show steps
Participate in peer discussions to exchange knowledge and perspectives on the evolution of viruses.
Show steps
-
Join online forums or discussion groups related to virology.
-
Engage in discussions on topics related to virus evolution.
-
Share your own knowledge and insights, and learn from others' perspectives.
Jupyter Notebook for Analyzing Virus Dendrograms
Show steps
Start a Jupyter notebook project that will test your ability to analyze virus dendrograms. This is a good way to demonstrate your proficiency with the techniques learned during this course
Browse courses on
Dendrograms
Show steps
-
Import libraries and load datasets
-
Write a function to calculate pairwise nucleotide composition distances
-
Create a distance matrix and calculate the cumulative skew profiles
-
Use a hierarchical clustering method to create a dendrogram
-
Visualize the dendrogram
Practice dendrogram construction
Show steps
Engage in repetitive exercises to solidify your understanding of dendrogram construction techniques.
Browse courses on
Phylogenetic Analysis
Show steps
-
Use online tools or software to construct dendrograms based on given data.
-
Interpret the results of dendrogram construction and identify patterns.
-
Compare different dendrogram construction methods and evaluate their strengths and weaknesses.
Practice creating dendrograms from cumulative skew profiles
Show steps
Provides hands-on practice with the core concepts of the course, allowing you to solidify your understanding of dendrogram creation and interpretation.
Browse courses on
Dendrograms
Show steps
-
Create a cumulative skew profile for a given DNA sequence
-
Use the cumulative skew profile to create a dendrogram
-
Interpret the dendrogram to identify relationships among viruses
Explore advanced bioinformatics tools
Show steps
Seek out and follow tutorials to enhance your proficiency in bioinformatics tools relevant to virology.
Show steps
-
Identify bioinformatics tools that specialize in virology research.
-
Follow online tutorials or workshops to learn how to use these tools.
-
Apply the tools to analyze real-world virology datasets.
Develop a Python program to analyze virus data and create a dendrogram
Show steps
Challenges you to apply your knowledge by creating a functional program that demonstrates your understanding of virus analysis and dendrogram creation.
Browse courses on
Python Programming
Show steps
-
Design the program's architecture and functionality
-
Implement the program using Python
-
Test and debug the program
-
Use the program to analyze virus data and create a dendrogram
Develop a visualization of virus relatedness
Show steps
Create a visual representation of the relatedness among different viruses to enhance your understanding of viral diversity.
Browse courses on
Data Visualization
Show steps
-
Gather data on the nucleotide sequences of different viruses.
-
Analyze the data to determine the relatedness among the viruses.
-
Choose an appropriate visualization technique to represent the relatedness data.
-
Create the visualization and interpret the results.
Mentor other students in the course
Show steps
Provides an opportunity to reinforce your understanding by helping others, while also contributing to the learning community.
Show steps
-
Identify students who need support
-
Offer assistance and guidance on course-related topics
-
Provide feedback and encouragement
Python Programming Practice
Show steps
This course requires a strong foundation in Python programming. Practice writing Python code to improve your skills before taking the course
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Solve Python coding problems on websites like HackerRank or LeetCode
- Build small Python projects
- Contribute to open source Python projects
Seek guidance from experts in the field
Show steps
Connects you with experienced professionals who can provide valuable advice and support, enriching your learning experience.
Show steps
Show steps
Show steps
- Identify experts in the field of virus analysis and dendrogram creation
- Reach out to potential mentors and request guidance
- Schedule regular meetings or communication channels
Review of Genome Sequencing Techniques
Show steps
Before taking this course, you need to have a basic understanding of genome sequencing techniques. This knowledge will be essential for understanding the data that you will be analyzing in the course
Browse courses on
Genome Sequencing
Show steps
Show steps
Show steps
- Read articles or books about genome sequencing
- Watch videos about genome sequencing
- Take an online course on genome sequencing
Ten other activities
Expand to see all activities and additional details
Show all 13 activities
Review Nucleotide composition and their analysis
Show steps
Review the concepts of nucleotide composition and their analysis to strengthen your foundational understanding in virology.
Browse courses on
Nucleotide Composition
Show steps
Show steps
Show steps
- Revisit the structure and properties of nucleotides.
- Explore different methods for analyzing nucleotide composition.
- Practice analyzing nucleotide composition using online tools or software.
Review the basics of nucleotide composition
Show steps
Refreshes your understanding of nucleotide composition, which is essential for understanding cumulative skew profiles and dendrogram creation.
Browse courses on
Nucleotide Composition
Show steps
Show steps
Show steps
- Review the structure and properties of nucleotides
- Identify the different types of nucleotide bases
- Calculate the nucleotide composition of a given DNA sequence
Engage in peer discussions on virus evolution
Show steps
Participate in peer discussions to exchange knowledge and perspectives on the evolution of viruses.
Show steps
Show steps
Show steps
- Join online forums or discussion groups related to virology.
- Engage in discussions on topics related to virus evolution.
- Share your own knowledge and insights, and learn from others' perspectives.
Jupyter Notebook for Analyzing Virus Dendrograms
Show steps
Start a Jupyter notebook project that will test your ability to analyze virus dendrograms. This is a good way to demonstrate your proficiency with the techniques learned during this course
Browse courses on
Dendrograms
Show steps
Show steps
Show steps
- Import libraries and load datasets
- Write a function to calculate pairwise nucleotide composition distances
- Create a distance matrix and calculate the cumulative skew profiles
- Use a hierarchical clustering method to create a dendrogram
- Visualize the dendrogram
Practice dendrogram construction
Show steps
Engage in repetitive exercises to solidify your understanding of dendrogram construction techniques.
Browse courses on
Phylogenetic Analysis
Show steps
Show steps
Show steps
- Use online tools or software to construct dendrograms based on given data.
- Interpret the results of dendrogram construction and identify patterns.
- Compare different dendrogram construction methods and evaluate their strengths and weaknesses.
Practice creating dendrograms from cumulative skew profiles
Show steps
Provides hands-on practice with the core concepts of the course, allowing you to solidify your understanding of dendrogram creation and interpretation.
Browse courses on
Dendrograms
Show steps
Show steps
Show steps
- Create a cumulative skew profile for a given DNA sequence
- Use the cumulative skew profile to create a dendrogram
- Interpret the dendrogram to identify relationships among viruses
Explore advanced bioinformatics tools
Show steps
Seek out and follow tutorials to enhance your proficiency in bioinformatics tools relevant to virology.
Show steps
Show steps
Show steps
- Identify bioinformatics tools that specialize in virology research.
- Follow online tutorials or workshops to learn how to use these tools.
- Apply the tools to analyze real-world virology datasets.
Develop a Python program to analyze virus data and create a dendrogram
Show steps
Challenges you to apply your knowledge by creating a functional program that demonstrates your understanding of virus analysis and dendrogram creation.
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Design the program's architecture and functionality
- Implement the program using Python
- Test and debug the program
- Use the program to analyze virus data and create a dendrogram
Develop a visualization of virus relatedness
Show steps
Create a visual representation of the relatedness among different viruses to enhance your understanding of viral diversity.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Gather data on the nucleotide sequences of different viruses.
- Analyze the data to determine the relatedness among the viruses.
- Choose an appropriate visualization technique to represent the relatedness data.
- Create the visualization and interpret the results.
Mentor other students in the course
Show steps
Provides an opportunity to reinforce your understanding by helping others, while also contributing to the learning community.
Show steps
Show steps
Show steps
- Identify students who need support
- Offer assistance and guidance on course-related topics
- Provide feedback and encouragement
Career center
Learners who complete Hierarchical Clustering using Euclidean Distance will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data scientists use data analysis and modeling techniques to solve business problems. They work on projects such as improving customer service, optimizing marketing campaigns, and predicting future trends. This course covers topics such as hierarchical clustering and Euclidean distance, which are relevant to data analysis in data science. By taking this course, you may be able to gain the skills and knowledge necessary to analyze data and solve business problems.
Machine Learning Engineer
Machine Learning Engineer
Machine learning engineers build and deploy machine learning models to solve business problems. They work on projects such as developing self-driving cars, improving medical diagnosis, and predicting customer behavior. This course covers topics such as hierarchical clustering and Euclidean distance, which are relevant to data analysis in machine learning. By taking this course, you may be able to gain the skills and knowledge necessary to analyze data and build machine learning models.
Bioinformatics Scientist
Bioinformatics Scientist
Bioinformatics scientists use computational tools and techniques to analyze and interpret biological data. They work on projects such as developing new drugs and treatments, understanding the genetic basis of disease, and improving crop yields. This course, which covers topics such as hierarchical clustering and Euclidean distance, could help you gain the necessary skills to analyze biological data. This could be a valuable asset in the field of bioinformatics.
Quantitative Analyst
Quantitative Analyst
Quantitative analysts use data analysis and modeling techniques to make investment decisions. They work on projects such as developing trading strategies, analyzing risk, and forecasting financial markets. This course covers topics such as hierarchical clustering and Euclidean distance, which are relevant to data analysis in quantitative finance. By taking this course, you may be able to learn the skills and knowledge necessary to analyze data and make investment decisions.
Actuary
Actuary
Actuaries use data analysis and modeling techniques to assess and manage risk. They work on projects such as pricing insurance policies, developing pension plans, and evaluating financial risks. This course covers topics such as hierarchical clustering and Euclidean distance, which are relevant to data analysis in actuarial science. By taking this course, you may be able to learn the skills and knowledge necessary to analyze data and assess risk.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to provide insights and make predictions. They work in a variety of fields, including finance, healthcare, and marketing. This course covers topics such as hierarchical clustering and Euclidean distance, which are relevant to data analysis in statistics. By taking this course, you may be able to learn the skills and knowledge necessary to analyze data and make informed decisions.
Data Engineer
Data Engineer
Data engineers design, build, and maintain data pipelines to support data analysis and machine learning. They work on projects such as developing data warehouses, streaming data pipelines, and data lakes. This course covers topics such as hierarchical clustering and Euclidean distance, which are relevant to data analysis in data engineering. By taking this course, you may be able to learn the skills and knowledge necessary to analyze data and build data pipelines.
Computational Biologist
Computational Biologist
Computational biologists use computer science, mathematics, and statistics to analyze and interpret biological data. They study the complex interactions of biological systems, such as DNA and proteins, using computational tools and techniques. The skills you gain in this course, such as analyzing and interpreting data using hierarchical clustering and Euclidean distance, would be valuable in computational biology. It could help you build a foundation for understanding the complex interactions of biological systems.
Epidemiologist
Epidemiologist
Epidemiologists investigate the patterns and causes of disease and injury in human populations. They use data analysis and modeling techniques to track and predict the spread of disease and identify risk factors. This course covers topics such as hierarchical clustering and Euclidean distance, which are relevant to data analysis in epidemiology. By taking this course, you may be able to learn the skills and knowledge necessary to analyze epidemiological data.
Medical Scientist
Medical Scientist
Medical scientists conduct research to understand the causes and treatments of disease. They use a variety of techniques, including data analysis, to study the human body and develop new treatments. This course covers topics such as hierarchical clustering and Euclidean distance, which are relevant to data analysis in medical research. By taking this course, you may be able to gain the skills and knowledge necessary to analyze medical data.
Public Health Analyst
Public Health Analyst
Public health analysts use data analysis and modeling techniques to identify and address public health problems. They work on projects such as preventing the spread of disease, improving nutrition, and reducing environmental hazards. This course covers topics such as hierarchical clustering and Euclidean distance, which are relevant to data analysis in public health. By taking this course, you may be able to learn valuable skills to apply to public health work.
Software Engineer
Software Engineer
Software engineers design, develop, and maintain software systems. They work on a variety of projects, from developing mobile apps to building enterprise software. This course covers topics such as hierarchical clustering and Euclidean distance, which are relevant to data analysis in software engineering. By taking this course, you may be able to learn the skills and knowledge necessary to analyze data and develop software systems.
Research Scientist
Research Scientist
Research scientists conduct research to understand the world around us. They use a variety of techniques, including data analysis, to study everything from the human body to the stars. This course covers topics such as hierarchical clustering and Euclidean distance, which are relevant to data analysis in research. By taking this course, you may be able to learn valuable skills to apply to research work.
Biostatistician
Biostatistician
Biostatisticians apply statistical methods to address scientific questions in biology and medicine. Through the use of data analysis, they can enhance the interpretation of biological and medical data. This course covers topics such as hierarchical clustering and Euclidean distance, which are relevant to statistical analysis. By taking this course, you may be able to gain a solid understanding of these concepts, which could be an asset in the field of biostatistics.
Data Analyst
Data Analyst
Data analysts take complex data and turn it into easy-to-understand formats, using statistical analysis and modeling techniques. The ability to read and analyze data is an important skill for data analysts and, by taking this course, you may be able to learn valuable skills to apply to data science work. The program uses Python, a commonly used programming language for data analysis.
For more career information including salaries, visit:
OpenCourser.com/course/qcoz9d/hierarchical
Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Hierarchical Clustering using Euclidean Distance.
An advanced textbook that provides a thorough overview of molecular evolution and phylogenetics. Discusses advanced methods for phylogenetic analysis, including hierarchical clustering and Bayesian inference.
Save
A comprehensive textbook that covers both bioinformatics and phylogenetics. Includes detailed explanations of hierarchical clustering and other methods for phylogenetic analysis, as well as discussions of sequence analysis and genome annotation.
Save
An advanced textbook that provides a comprehensive overview of bioinformatics methods for studying evolution. Includes in-depth coverage of phylogenetic analysis, including hierarchical clustering and other methods for constructing phylogenetic trees.
In-depth coverage of algorithms fundamental to bioinformatics, with a focus on sequence analysis. Includes comprehensive sections on multiple sequence alignment, phylogenetic trees, and clustering techniques.
A textbook that provides a comprehensive overview of statistical methods used in bioinformatics. Includes coverage of hierarchical clustering and other methods for analyzing biological data, as well as discussions of model selection and data interpretation.
This well-regarded textbook moves from an introduction to bioinformatics to advanced topics in data analysis. It includes a comprehensive chapter on phylogenetic analysis, covering hierarchical clustering and other methods.
A classic textbook that provides a comprehensive overview of phylogenetic inference. Discusses hierarchical clustering and other methods for constructing phylogenetic trees, and evaluates their strengths and weaknesses.
Save
A classic textbook that provides a comprehensive overview of phylogenetic analysis. Discusses hierarchical clustering and other methods for constructing phylogenetic trees, and evaluates their strengths and weaknesses.
This comprehensive textbook provides formal algorithms and explanations for biological sequence analysis, including dendrogram construction from pairwise distance matrices. Considered one of the foundational works of bioinformatics.
Save
Introduces the theoretical basis of phylogenetics and discusses methods for inferring phylogenies from molecular data. Covers neighbor-joining, which is closely related to hierarchical clustering and useful for analyzing large datasets.
A technical reference detailing mathematical methods for sequence comparison. Discusses advanced methods for handling alignment, including evolutionary models of change, multiple sequence alignment, and phylogenetic tree construction.
A practical guide to building and interpreting phylogenetic trees. Provides clear explanations of hierarchical clustering and other methods for phylogenetic analysis, using examples and case studies.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/qcoz9d/hierarchical
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Time
1 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Usama A. F. Khalil
Good to know
Develops skills in coding, data analysis, and visualization, which are vital for diverse career paths
Uses real-world datasets and scenarios to make learning more engaging and applicable
Teaches Python, a widely used and versatile programming language
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