--- title: Bioinformatics description: Bioinformatics combines biology, computer science, and statistics to analyze large biological datasets. Learners will understand how to use computational tools and algorithms to sequence genomes, analyze protein structures, and identify genetic variations. category: sciences subcategory: biotechnology difficulty: beginner, intermediate, advanced url: /subject/bioinformatics --- # Bioinformatics Bioinformatics combines biology, computer science, and statistics to analyze large biological datasets. Learners will understand how to use computational tools and algorithms to sequence genomes, analyze protein structures, and identify genetic variations. ## Available Resources 3 Books • 2 Courses • 7 Websites ## Websites ### 1. Galaxy Project Open web-based workbench where you run genomics tools such as alignment, variant calling, and RNA-seq through a browser, without command-line experience. Public servers supply the compute, and every analysis is recorded as a reproducible, shareable workflow history. **Difficulty:** Beginner | **Price:** Free **Link:** https://usegalaxy.org/ **Tags:** genomics, workflows, reproducibility, rna-seq, sequence-analysis ### 2. Biostars Question-and-answer site where working bioinformaticians troubleshoot tools, file formats, and pipeline errors. Searching the archive of answered threads is often faster than documentation for practical problems with BLAST, samtools, aligners, and genome annotation. **Difficulty:** Beginner | **Price:** Free **Link:** https://www.biostars.org/ **Tags:** bioinformatics, qa-forum, troubleshooting, genomics, community ### 3. Rosalind Problem-based platform for practising bioinformatics by writing code. Exercises begin with string manipulation on DNA sequences and build toward alignment, assembly, and phylogeny algorithms, each graded automatically against a generated dataset in whichever language you choose. **Difficulty:** Beginner | **Price:** Free **Link:** https://rosalind.info/ **Tags:** bioinformatics, algorithms, coding-practice, dna-sequences, problem-sets ### 4. ensembl.org Ensembl is a comprehensive genome browser and annotation resource offering high-quality genome assemblies, gene models, transcripts, regulatory features, and genetic variation across many species. It also provides comparative genomics tools, data downloads, and access via BioMart and APIs for querying and mining genomic data. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://ensembl.org **Tags:** websites, engineering-manufacturing, biotechnology ### 5. Expasy Bioinformatics resource portal of the SIB Swiss Institute of Bioinformatics, giving access to databases and tools for protein sequence analysis, proteomics, structure, enzymes and genomics. Users can locate and run standard analyses such as sequence alignment, protein identification and functional annotation. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://expasy.org **Tags:** protein-analysis, proteomics, sequence-analysis, bioinformatics-databases, functional-annotation ### 6. ncbi.nlm.nih.gov NCBI is a comprehensive biomedical database hub from the NIH that hosts major resources like PubMed, GenBank, Gene, Protein, and Genome. It also provides powerful search and analysis tools (Entrez, BLAST) and tutorials for learning bioinformatics. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://ncbi.nlm.nih.gov **Tags:** websites, engineering-manufacturing, biotechnology ### 7. RCSB Protein Data Bank US data centre for the Protein Data Bank, the global archive of experimentally determined 3D structures of proteins, nucleic acids and complexes. It offers search, interactive 3D viewers, validation reports and downloadable data for studying molecular structure and its relation to function. **Difficulty:** Intermediate | **Language:** English | **Price:** Free **Link:** https://rcsb.org **Tags:** protein-structure, structural-biology, molecular-visualization, structural-databases ## Courses ### 1. Introduction to Genomic Technologies This course introduces you to the basic biology of modern genomics and the experimental tools that we use to measure it. We'll introduce the Central Dogma of Molecular Biology and cover how next-generation sequencing can be used to measure DNA, RNA, and epigenetic patterns. You'll also get an introduction to the key concepts in computing and data science that you'll need to understand how data from next-generation sequencing experiments are generated and analyzed. This is the first course in the Genomic Data Science Specialization. **Difficulty:** Beginner | **Price:** Free **Link:** https://www.coursera.org/learn/introduction-genomics **Tags:** genomics, next-generation-sequencing, molecular-biology, genomic-data-science ### 2. Foundations of Computational and Systems Biology (MIT 7.91J) **Author:** Christopher Burge, David Gifford, Ernest Fraenkel Computational biology fundamentals: nucleic acid and protein sequence alignment, motif finding, structural modeling and prediction, and network models of biological systems. Includes 22 lecture videos, slides, programming assignments and projects, preparing learners to apply algorithms to genomic and protein data. **Difficulty:** Advanced | **Price:** Free **Link:** https://ocw.mit.edu/courses/7-91j-foundations-of-computational-and-systems-biology-spring-2014/ **Tags:** computational-biology, sequence-alignment, motif-finding, protein-structure-prediction, network-modeling, systems-biology ## Books ### 1. Bioinformatics Data Skills **Author:** Vince Buffalo Practical guide to the Unix-centred toolchain real genomics work runs on: shell pipelines, awk and sed, Git, R, samtools, and BEDTools. Teaches reproducible project organisation and data handling rather than the biology or the algorithms themselves. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/1449367372?tag=edmonddante07-20 **Tags:** books, engineering-manufacturing, biotechnology ### 2. Bioinformatics Algorithms: An Active Learning Approach **Author:** Phillip Compeau, Pavel Pevzner Introduces the core algorithms of computational biology, including genome assembly, sequence alignment, motif finding, and phylogeny, by opening each chapter with a biological question and deriving the method from it. Paired with programming challenges on Rosalind. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/0990374610?tag=edmonddante07-20 **Tags:** books, engineering-manufacturing, biotechnology ### 3. Python for Bioinformatics **Author:** Sebastian Bassi Teaches Python to biologists from scratch, then applies it to sequence parsing with Biopython, regular expressions, database access, and web services. Includes chapters on graphics, XML handling, and building small tools for laboratory data. **Difficulty:** Intermediate | **Language:** English | **Price:** Paid **Link:** https://www.amazon.com/dp/1584889292?tag=edmonddante07-20 **Tags:** books, engineering-manufacturing, biotechnology --- *This content is part of Dantes.io - Your Treasure Map to Knowledge* *Curated by humans at Dantes.io. Personal study use welcome; republishing this curation requires permission (team@dantes.io).* View this page online: https://dantes.io/subject/bioinformatics