1/ If you're interested in learning #bioinformatics as a #novice, you're in the right place! Bioinformatics is a field that combines biology, computer science, and statistics to analyse large scale biological data. Here are some resources to get you started:-
2/ First, you'll need to learn some basic biology. #KhanAcademy has a comprehensive series of videos on biology that can help you understand the fundamentals. Check it out here: khanacademy.org/science/biology
4/ Once you have some programming skills, you can start learning bioinformatics-specific tools and techniques. The #Rosalind Project is a great resource for learning bioinformatics through problem-solving. Check it out here: rosalind.info/problems/locat…
5/ Another great resource for learning bioinformatics is the Bioinformatics Workbook, a free online textbook that covers a wide range of topics. Check it out here: bioinformaticsworkbook.org
6/ Finally, there are many online courses and tutorials that can help you learn bioinformatics. Some popular ones include Coursera's Bioinformatics Specialization and the @EBItraining online courses. Check them out here: coursera.org/specialization…ebi.ac.uk/training/onlin…
7/ Learning #bioinformatics can be challenging, but it's also incredibly rewarding. With these resources, you can start your journey into this exciting and novel field. Good luck, and happy learning! If you find this thread useful, follow me for more updates on #bioinfo learning
• • •
Missing some Tweet in this thread? You can try to
force a refresh
1/ Are you a bioinformatics researcher looking for powerful tools to analyse your data? Check out @Bioconductor ! Here are some of my favorite packages for #bioinformatics analyses.
2/ First up: #DESeq2 by @mikelove. This package provides a method for differential gene expression analysis of RNA-seq data. It's widely used and highly cited in the field, and it's perfect for identifying genes that are differentially expressed between samples.
3/ Next, I recommend #edgeR. Like DESeq2, edgeR is a package for differential gene expression analysis of RNA-seq data. It's particularly useful for smaller sample sizes and can detect differential expression with greater sensitivity.
1/ If you're new to #bioinformatics and looking to start learning, there are a ton of great resources out there to help you get started. Here are some sites, #Github repos, and books to check out:
2/ First up, the website Bioinformatics.org has a ton of resources for learning bioinformatics, including tutorials, forums, and #software tools. Check it out here: bioinformatics.org