Biopython from Udemy

The course content consists of two main parts. The first part deals with an introduction to python, the goal of which is to lay down the basics of algorithms and programming languages in general. The first part contains the following:

Install python, pycharm, and biopython.
Knowledge of basic syntax, which includes variables and line write methods in python.
Knowing the five variable types, which include number, string, list, tuple, and dictionary.
Knowing the operator types, including arithmetic, comparison, assignment, logical, membership, and identity.
Understanding decision-making strategies, including the use of "if .. else", "if .. elif .. else" and "nested if.".
Understanding loops, writing, and controlling while loop and for loop.

The second part is an introduction to biopython, which is a package based on python, so we will apply what was understood in the first part. The second part contains the following:

Dealing with the NCBI database through Entrez, requires an internet connection, and we will use einfo, espell, esearch, esummary, egquery, and efetch.
Working with files, writing, and converting files using seqio. dealing with the two most popular types of sequence files in terms of reading and writing in detail.
Working with sequences through python, they understand some functions such as slice, find, count, len, lower, upper, replace, split, join and strip.
Transcription of molecules as cell, transcription and reverse transcription of DNA and RNA respectively, DNA translation. manufacture of complement and reverse complement of DNA.
Simple basic analysis of sequences, including GC content, molecular weight, and six reading frames. search inside sequences using nt_search.
Pairwise alignment, understanding, and implementing both local and global alignment. work with results and understand matches and gaps.
Multiple sequence alignment, execute and read multiple sequence alignment and extract data for the phylogenetic tree.
Blast, sequence search in the NCBI database. build a local database and implement blast offline. dealing with results in detail.

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Provides a foundation for learners to understand algorithms and programming languages, addressing basic syntax, variable types, operators, decision-making, and loops

Guides learners through the NCBI database and its tools (einfo, espell, esearch, esummary, egquery, efetch) for data retrieval, facilitating biological data analysis

Provides practical experience working with files and sequence data using Biopython's seqio module, enhancing learners' proficiency in data manipulation and analysis

Covers fundamental sequence analysis techniques, including GC content, molecular weight, six reading frames, and sequence search using nt_search, empowering learners to extract meaningful insights from biological data

Introduces learners to pairwise alignment, explaining both local and global alignment strategies and enabling them to analyze and compare sequences

Exposes learners to multiple sequence alignment, a critical technique for uncovering evolutionary relationships and identifying conserved regions within sets of sequences

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 Biopython with these activities:

Connect with experts in the field of bioinformatics

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Establishing connections with experts can provide invaluable guidance and support throughout your bioinformatics journey.

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Attend industry events and conferences.
Reach out to professors, researchers, or professionals in the field.
Request informational interviews or mentorship opportunities.
Maintain relationships and seek ongoing guidance.

Create a comprehensive study guide

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Compiling a study guide will help you synthesize and organize course materials for effective exam preparation.

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Gather all course notes, assignments, and resources.
Identify key concepts, definitions, and formulas.
Organize the material into logical sections and subsections.
Summarize and condense information in a clear and concise manner.
Review the study guide regularly and test your understanding.

Solve Python coding challenges

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Engaging in practice drills will reinforce your understanding of Python syntax and algorithmic concepts.

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Register for an online coding platform.
Choose a set of coding challenges aligned with the course topics.
Attempt to solve the challenges independently.
Review solutions and discuss approaches with peers or instructors.

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Participate in online discussion forums

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Engaging in discussions will foster collaboration, clarify concepts, and expose you to diverse perspectives.

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Join online discussion forums related to the course topics.
Participate in discussions, asking questions and sharing insights.
Review and comment on others' posts.
Summarize key points and insights gained.

Follow tutorials on bioinformatics tools

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Tutorials will provide hands-on experience and supplement the course materials on bioinformatics tools and databases.

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Identify reputable online resources or tutorials.
Select tutorials relevant to the course content.
Follow the instructions and complete the exercises provided.
Document your findings and share insights with classmates.

Develop a data visualization for sequence analysis

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Creating a data visualization will enhance your ability to interpret and communicate complex sequence analysis results.

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Choose a dataset from the NCBI or other public databases.
Analyze the data and identify patterns or trends.
Select an appropriate data visualization tool.
Create a visually appealing and informative visualization.
Share your visualization and explain your findings.

Build a local BLAST database

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Constructing a local BLAST database will provide hands-on experience with advanced sequence analysis techniques.

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Acquire sequence data from the NCBI or other databases.
Format the data into a FASTA file.
Use the BLAST+ command-line tools to create the local database.
Run BLAST searches against your local database.
Interpret and analyze the search results.

Contribute to a bioinformatics open-source project

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Contributing to open-source projects will enhance your understanding of bioinformatics tools and best practices.

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Identify a bioinformatics open-source project that aligns with your interests.
Familiarize yourself with the project's codebase and documentation.
Identify areas where you can contribute improvements or new features.
Submit your contributions for review and merge.
Participate in discussions and collaborate with other contributors.

Career center

Learners who complete Biopython will develop knowledge and skills that may be useful to these careers:

Bioinformatics Scientist

A Bioinformatics Scientist uses computer programming and mathematical algorithms to analyze biological data, particularly DNA and amino acid sequences, to help understand the structure, function, and evolution of living organisms. This course will teach you the programming languages necessary to acquire and analyze this biological data.

See salaries and explore the career path for Bioinformatics Scientist

Computational Biologist

A Computational Biologist applies computer science and informatics to the study of biological systems. The development of sequencing technologies such as Next-Generation Sequencing (NGS) has resulted in the explosion of biological data. The primary objective of NGS data analysis is to identify the different variants present in a DNA sample. This course will teach you how to use Python for biological data analysis.

See salaries and explore the career path for Computational Biologist

Biostatistician

A Biostatistician uses statistics to design and analyze studies, and to interpret and communicate the results of those studies. Biostatisticians make significant contributions to the biomedical research process, and can hold positions in both academia and industry. This course will teach you how to use Python to perform statistical analysis on biological data.

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Data Scientist

A Data Scientist uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course will teach you how to use Python to analyze both biological and non-biological data.

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Database Administrator

A Database Administrator designs, implements, and maintains databases to store and manage data. This course will teach you how to use Python to manage biological databases.

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Research Scientist

A Research Scientist conducts research in a specific field of science, typically with the goal of advancing knowledge in that field. This course will teach you how to use Python to analyze data and generate new knowledge in the field of biology.

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Science Teacher

A Science Teacher teaches science to students at the elementary, secondary, or post-secondary level. This course will teach you how to use Python to teach biology to students.

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Technical Writer

A Technical Writer creates and maintains technical documentation, such as user manuals, white papers, and training materials. This course will teach you how to use Python to write technical documents about biological topics.

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Science Writer

A Science Writer writes about science for a general audience. This course will teach you how to use Python to analyze data and generate new knowledge in the field of biology.

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Science Editor

A Science Editor edits scientific articles and books. This course will teach you how to use Python to analyze data and generate new knowledge in the field of biology.

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Science Communicator

A Science Communicator communicates science to a general audience. This course will teach you how to use Python to analyze data and generate new knowledge in the field of biology.

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Science Policy Analyst

A Science Policy Analyst analyzes and develops policies related to science and technology. This course will teach you how to use Python to analyze data and generate new knowledge in the field of biology.

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Science Lobbyist

A Science Lobbyist advocates for science and technology policies. This course will teach you how to use Python to analyze data and generate new knowledge in the field of biology.

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Science Fundraiser

A Science Fundraiser raises money for scientific research and education. This course will teach you how to use Python to analyze data and generate new knowledge in the field of biology.

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Science Journalist

A Science Journalist writes about science for a general audience. This course will teach you how to use Python to analyze data and generate new knowledge in the field of biology.

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Biopython

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