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Martin Aslett, Dr. Anna Protasio, Matthew Dorman, Dr. Christine Boinett, and Dr. Ulrike Böhme

• Bioinformatics tools, DNA and protein sequences • Retrieving DNA and protein sequences from repositories • Databases for protein annotation • Inferring function from sequence Most FutureLearn courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts. Find out more The course will be of interest to undergraduates, post-graduates, researchers, bioinformaticians, biomedical researchers, microbiologists, healthcare professionals and all those who are interested in learning about the underlying mechanisms of bacterial disease, DNA sequences and protein data, or how to use online analytical tools to probe genomes. The topics covered in this course are applicable to the genomes of all organisms. It is not essential to have previous knowledge or experience in bioinformatics. Scientific terminology is explained. The opportunity to use online computational tools in the context of bacterial genomes will also be of interest to teachers and their 16-18-year-old science and computing students. You can use the hashtag #FLsequence2function to talk about this course on social media.

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• Bioinformatics tools, DNA and protein sequences • Retrieving DNA and protein sequences from repositories • Databases for protein annotation • Inferring function from sequence Most FutureLearn courses run multiple times. Every run of a course has a set start date but you can join it and work through it after it starts. Find out more The course will be of interest to undergraduates, post-graduates, researchers, bioinformaticians, biomedical researchers, microbiologists, healthcare professionals and all those who are interested in learning about the underlying mechanisms of bacterial disease, DNA sequences and protein data, or how to use online analytical tools to probe genomes. The topics covered in this course are applicable to the genomes of all organisms. It is not essential to have previous knowledge or experience in bioinformatics. Scientific terminology is explained. The opportunity to use online computational tools in the context of bacterial genomes will also be of interest to teachers and their 16-18-year-old science and computing students. You can use the hashtag #FLsequence2function to talk about this course on social media.

Topics Covered

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    Reviews summary

    Foundational bioinformatics for bacterial genomes

    According to learners, 'Bacterial Genomes: From DNA to Protein Function Using Bioinformatics' offers a solid introduction to the field, particularly for those with a biology background but limited bioinformatics experience. Students consistently highlight the clear explanations of complex topics and the value of the practical exercises using online tools. These hands-on activities are seen as a major strength, reinforcing learning and allowing immediate application. While the course provides a strong foundation in bacterial genomics and protein function, some advanced learners found the depth to be too basic, preferring more extensive coverage or command-line tool usage. There were also occasional comments about the pacing and clarity of tool instructions.
    Highly relevant for biologists/microbiologists.
    "Highly recommended for biologists wanting to dip their toes into genomics analysis."
    "As a microbiologist, I found this course useful for understanding how bioinformatics can assist my research. The emphasis on bacterial genomes was perfect."
    "I really enjoyed the sections on protein function and annotation databases. The material feels current and relevant."
    Hands-on exercises are highly valuable.
    "...the practical exercises using online tools were incredibly helpful. I especially appreciated the step-by-step guidance."
    "The hands-on parts were the best, allowing me to apply what I learned immediately."
    "The practical exercises reinforced the learning. A solid foundation for further learning..."
    Excellent for those new to bioinformatics.
    "This course was a fantastic introduction to bioinformatics for someone with a biology background but no prior coding experience. The explanations were clear..."
    "Excellent course! The instructors explained complex topics in an easy-to-understand manner."
    "Very accessible course for someone with a biology background. The concepts were broken down well..."
    Instructions for tools could be clearer.
    "The instructions for the online tools could have been clearer, as I had to do a lot of troubleshooting myself."
    "I struggled with the pace. Sometimes it felt too fast... not as polished as I'd hoped."
    May be too basic for experienced researchers.
    "...I found some parts a bit superficial for an advanced researcher. If you're already familiar with the concepts, you might not gain much new insight."
    "I expected more depth, especially for advanced topics. The course felt too elementary for a researcher... not for me."
    "While it covered a broad range of topics, I felt some practical aspects, like command-line tools, were omitted. It's more conceptual than practical in depth."

    Career center

    Learners who complete Bacterial Genomes: From DNA to Protein Function Using Bioinformatics will develop knowledge and skills that may be useful to these careers:

    Reading list

    We've selected 50 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 Bacterial Genomes: From DNA to Protein Function Using Bioinformatics.
    Comprehensive reference guide to R, covering topics such as data manipulation, visualization, and modeling. It great resource for anyone who wants to learn more about the R language itself.
    Gathers hundreds of battle-tested recipes covering network programming, memory management, data structures, and functional decorators for veteran application developers.
    Delivers the canonical blueprint for numeric analysis from the creator of pandas, thoroughly detailing NumPy structures, data cleaning, and high-speed transformations.
    Introduces clean architecture, domain-driven design, and event-driven microservices to Python developers, demonstrating repository patterns and dependency inversion.
    Offers a unique approach to learning bioinformatics algorithms through active problem-solving. It is an excellent resource for both biology and computer science students, bridging the gap between biological challenges and algorithmic solutions. It is often used as a textbook and provides hands-on learning opportunities.
    Demystifies programming for practical utility, guiding beginners through real-world automation projects including web scraping, spreadsheet generation, and file audits.
    Is widely considered a foundational text in bioinformatics, offering a comprehensive overview of core concepts, particularly sequence and genome analysis. It is highly valuable for gaining a broad understanding and is often used as a textbook in academic settings. While not the most recent, its clear explanations and breadth of coverage make it an essential reference.
    Focuses on static typing, structural subtyping, and defensive design techniques, demonstrating how modern type annotations prevent regressions in enterprise codebases.
    Provides a comprehensive overview of protein structure and function, covering topics such as protein folding, protein-ligand interactions, and protein dynamics. It is written in a clear and concise style, and it is suitable for both undergraduate and graduate students.
    Provides a comprehensive overview of bioinformatics algorithms. It covers a wide range of topics, including sequence analysis, gene expression analysis, and protein structure prediction. It valuable resource for anyone who works with biological data.
    Provides a practical guide to the analysis of genes and proteins. It covers a wide range of topics, including sequence analysis, gene expression analysis, and protein structure prediction. It valuable resource for anyone who works with genes and proteins.
    Provides a detailed guide to DNA sequencing protocols, including sample preparation, library preparation, and sequencing analysis. It valuable resource for researchers who are new to DNA sequencing or who want to improve their sequencing skills.
    Unpacks professional testing methodologies using pytest, explaining fixture management, parameterized tests, coverage tracking, and automated CI test execution.
    A classic in the field, this book delves into the probabilistic models that are fundamental to sequence analysis. It provides a rigorous treatment of topics like hidden Markov models and their applications. is essential for those seeking a deeper theoretical understanding and key reference for researchers.
    Investigates advanced software craft, detailing packaging distribution, bytecode internals, scaling architectures, and maintainability across large distributed systems.
    Bridges volumetric point cloud analysis with Python, teaching LiDAR processing, spatial meshing, and 3D machine vision using modern scientific computing toolchains.
    Presents a welcoming, foundational ramp into computational logic and programming, establishing syntax literacy, object modeling, and error handling for total beginners.
    Covers the fundamental concepts and algorithms in sequence analysis, with a focus on biological applications.
    Provides a solid introduction to the field of bioinformatics, covering a wide range of topics from sequence analysis to genomics and data mining. It is well-suited for beginners and provides a good foundation for further study. The clear explanations and practical examples make it a valuable resource for those new to the subject.
    Provides 50 focused exercise routines and guided breakdowns designed to build instinctive muscle memory across collections, functional pipelines, algorithms, and file I/O.
    Teaches the essential data science skills for analyzing large-scale biological data. Provides hands-on guidance on using open-source tools and best practices for reproducible and robust research.
    Focuses on algorithmic techniques for sequence analysis and bioinformatics, providing practical examples and implementations.
    Tackles the full lifecycle of shipping models into production, covering feature store development, container packaging, drift detection, and continuous retraining.
    Covers machine learning methods specifically tailored for bioinformatics applications, including sequence analysis.
    Save
    Provides a practical guide to DNA sequencing, including choosing the right sequencing technology, preparing samples, and analyzing data. It valuable resource for researchers who are new to DNA sequencing or who want to improve their sequencing skills.
    Provides a comprehensive overview of molecular biology, including a chapter on protein structure and function. It is written in a clear and concise style, and it is suitable for both undergraduate and graduate students.
    Provides a practical introduction to R for data science. It covers topics such as data manipulation, visualization, and modeling. It great resource for anyone who wants to learn more about using R for data science.
    Provides a comprehensive overview of R for data science, covering topics such as data manipulation, visualization, and modeling. It great resource for anyone who wants to learn more about using R for data science.
    This practical guide focuses specifically on utilizing NCBI databases and performing sequence alignments using tools like BLAST. It is highly relevant for anyone working with biological sequence data and provides step-by-step guidance with examples.
    Connects systems engineering with offensive network reconnaissance, detailing raw packet manipulation, Windows process injection, and reverse shell programming.
    Focuses on statistical methods relevant to modern biological data analysis, particularly in the context of high-throughput experiments. It is valuable for researchers and students who need to apply statistical rigor to their bioinformatics analyses.
    This cookbook provides practical recipes for performing various bioinformatics tasks using R and Bioconductor. It valuable resource for those who want to apply R programming to solve specific problems in areas like RNA-Seq analysis, genomics, and data visualization.
    Examines computational molecular biology through a programmer lens, illustrating genomic sequence alignment, phylogenetic modeling, and biochemical laboratory automation.
    While not solely a bioinformatics book, this text provides a comprehensive introduction to systems biology, a field closely related to bioinformatics that focuses on understanding biological systems as a whole. It is valuable for gaining a broader perspective on how bioinformatics contributes to systems-level analysis.
    Provides an introduction to the computational aspects of bioinformatics, covering programming concepts and algorithms relevant to biological data analysis. It is suitable for those with a computing background looking to apply their skills to bioinformatics problems.
    While not solely focused on bioinformatics, this book is highly relevant for anyone working with biological data, which often requires command-line processing. It teaches essential data manipulation skills using command-line tools, which are fundamental for efficient bioinformatics workflows.
    Although not exclusively focused on bacterial genomes, this book provides a comprehensive overview of bacterial physiology and metabolism, including discussions on bacterial genome structure and function.
    Provides a comprehensive overview of the biology of proteins, including chapters on the structure of proteins, the function of proteins, and the evolution of proteins. It is written in a clear and concise style, and it is suitable for both undergraduate and graduate students.

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