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Martin Aslett, Dr. Anna Protasio, Matthew Dorman, Dr. Christine Boinett, Dr. Pablo Tsukayama, Professor Nicholas Thomson, and Dr. Ulrike Böhme

Week 1 Week 2 Week 3 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 This course would benefit those interested in learning how to use tools to investigate bacterial genomes, and acquire bioinformatics skills to evaluate the role of microbial genes in disease. Using analytical tools to access and probe genomes, learners will find out how to perform comparative analyses of genes and their protein products. The course will be of interest to undergraduates, post-graduates, researchers, bioinformaticians, microbiologists, and healthcare professionals. The opportunity to use online computational tools to probe bacterial genomes will also be of interest to teachers and their 16-18-year-old science and computing students. Bacterial Genomes: From DNA to Protein Function using Bioinformatics is a recommended pre-requisite. Scientific terminology is explained. You can use the hashtag #FLaccess2analysis to talk about this course on social media.

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Week 1 Week 2 Week 3 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 This course would benefit those interested in learning how to use tools to investigate bacterial genomes, and acquire bioinformatics skills to evaluate the role of microbial genes in disease. Using analytical tools to access and probe genomes, learners will find out how to perform comparative analyses of genes and their protein products. The course will be of interest to undergraduates, post-graduates, researchers, bioinformaticians, microbiologists, and healthcare professionals. The opportunity to use online computational tools to probe bacterial genomes will also be of interest to teachers and their 16-18-year-old science and computing students. Bacterial Genomes: From DNA to Protein Function using Bioinformatics is a recommended pre-requisite. Scientific terminology is explained. You can use the hashtag #FLaccess2analysis to talk about this course on social media.

Topics Covered

  • Multi-FASTA files
  • Reference and draft bacterial genomes
  • Introduction to Artemis, an open source genome browser
  • Genome annotation
  • Genomic regions defined by GC (guanine-cytosine) content
  • Accessing and downloading whole genome sequences
  • Pathogenicity islands
  • Peer-reviewed project: Ecological niche adaptation between two
  • species
  • Pseudogenes in
  • species

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Reviews summary

Bacterial genomes: accessing and analyzing microbial data

According to learners, this course offers a solid foundation in bacterial genome analysis, particularly highlighting the hands-on experience with practical tools like Artemis. Students frequently praise the clear explanations and structured approach, making complex bioinformatics concepts accessible. While many found it highly relevant and useful for their work or studies, a few reviewers noted that having a strong background in biology and bioinformatics is beneficial for keeping pace. The course content is considered comprehensive for an introduction, covering key areas like annotation and pathogenicity islands effectively. Overall, it is viewed as a valuable and well-presented course for those entering the field or needing practical skills.
Content is highly applicable to professional work/study.
"The knowledge and skills gained are <span class="positive">directly applicable to my research in microbiology."
"Found the course content <span class="positive">highly relevant to current work in infectious diseases."
"This course is <span class="positive">incredibly useful for anyone working with microbial data; it filled gaps in my practical skills."
"The concepts covered have <span class="positive">immediate utility in my academic projects."
Provides a strong introductory base for the subject.
"This course gave me a <span class="positive">solid foundation in bacterial genomics analysis."
"It's an <span class="positive">excellent starting point for anyone interested in microbial genome data."
"I feel much more confident approaching bacterial genome data after taking this course; it provided <span class="positive">essential foundational knowledge."
"A <span class="positive">great introduction that covers the necessary basics effectively."
Instructors provide clear and understandable explanations.
"The material was <span class="positive">presented clearly and concisely, making it easy to follow complex topics."
"I found the explanations throughout the modules to be <span class="positive">very clear and well-articulated."
"Instructors did a <span class="positive">great job breaking down difficult concepts into manageable parts."
"The <span class="positive">clarity of the lectures significantly helped my learning process."
Gain valuable hands-on experience with bioinformatics tools.
"The course provided me with <span class="positive">excellent hands-on experience using practical tools to access and analyse bacterial genomes."
"Using Artemis was a <span class="positive">highlight, allowing me to <span class="positive">apply concepts directly to real data."
"I particularly valued the <span class="positive">practical exercises and demos; they really <span class="positive">solidified my understanding."
"The inclusion of <span class="positive">real-world tools and data made the learning <span class="positive">highly effective."
Prior knowledge in biology/bioinformatics is beneficial.
"While the course explains terminology, having some <span class="warning">prior background in biology or genetics is really helpful."
"I recommend having completed the suggested <span class="warning">prerequisite course or having a solid understanding of basic bioinformatics concepts."
"Some sections move <span class="warning">quite quickly and might be challenging without previous exposure to the field."

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Learners who complete Bacterial Genomes: Accessing and Analysing Microbial Genome Data 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.
Offers a fundamental understanding of bacterial molecular biology, covering topics such as bacterial genome structure and gene expression. It is suitable for students or researchers seeking a foundational knowledge of this field.
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.
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.
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.

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