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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.

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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."

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    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 haven't picked any books for this reading list yet.
    Provides a detailed overview of machine learning methods used in bioinformatics. It covers topics such as supervised learning, unsupervised learning, and feature selection. It good resource for students and researchers who are interested in using machine learning methods to analyze biological data.
    Provides a detailed overview of deep learning methods used in bioinformatics. It covers topics such as convolutional neural networks, recurrent neural networks, and autoencoders. It good resource for students and researchers who are interested in using deep learning methods to analyze biological data.
    Provides a detailed overview of big data in bioinformatics. It covers topics such as data management, data analysis, and data visualization. It good resource for students and researchers who are interested in working with big data in bioinformatics.
    Provides a detailed overview of programming for bioinformatics using Python. It covers topics such as data structures, algorithms, and machine learning. It good resource for students and researchers who are interested in developing bioinformatics software.
    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.
    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.
    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.
    Focuses on the statistical foundations of bioinformatics, which are crucial for interpreting biological data. It covers probability, statistical inference, and their applications in bioinformatics analyses like sequence alignment and phylogenetic tree estimation. It is valuable for students and researchers needing a solid statistical background.
    Provides a broad introduction to bioinformatics with a strong emphasis on functional genomics. It covers a wide range of topics, including sequence analysis, gene expression, and systems biology, making it suitable for gaining a general understanding and exploring the applications of bioinformatics in modern biological research.
    Given the prevalence of R in bioinformatics, this book valuable resource for learning how to use R for biological data analysis. Written by one of the creators of R and a leading figure in the Bioconductor project, it covers various programming aspects and their applications in bioinformatics and computational biology problems.
    Focuses on essential data skills for bioinformatics, emphasizing reproducible research practices using open-source tools like the command line and R. It is highly practical and valuable for students and professionals who need to manage and analyze biological data effectively.
    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 a deep dive into the algorithms that are fundamental to many bioinformatics tasks, particularly in sequence analysis. It more theoretical text, well-suited for those with a computer science background seeking a rigorous understanding of the underlying algorithms.
    Offers a gentle introduction to bioinformatics for those with little or no prior experience. It explains core concepts in an accessible way and guides readers on using online resources and tools. It good starting point for beginners to get a general understanding of the field.
    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 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.
    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.
    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.
    Provides a detailed overview of statistical methods used in bioinformatics. It covers topics such as data analysis, machine learning, and statistical modeling. It good resource for students and researchers who are interested in using statistical methods to analyze biological data.

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