Biological data and sequences
Modern biology produces enormous amounts of data. Bioinformatics uses computers to store, search, and make sense of it.
What bioinformatics is
Bioinformatics combines biology, computer science, and statistics to analyse biological data, especially DNA, RNA, and protein sequences. It answers questions like what a gene does, how species are related, and which mutations cause disease.
DNA sequencing
Sequencing reads the order of bases in DNA. The Human Genome Project, completed in 2003, cost about 3 billion dollars and took 13 years. Today, high-throughput sequencers can read a human genome in about a day for a few hundred dollars, producing billions of short reads that must be assembled by computer.
Sequence formats
Sequences are stored as text strings: DNA as A, C, G, T; proteins as a 20-letter alphabet of amino acids. The FASTA format is a simple standard: a header line beginning with '>' followed by the sequence. Sequencing data with quality scores are often stored in FASTQ files.
Biological databases
Public databases share data worldwide. GenBank stores DNA sequences; UniProt stores protein sequences and functions; the Protein Data Bank (PDB) stores 3D protein structures. Researchers deposit data when they publish, so anyone can search and reuse it.
Genome assembly
Sequencers read short fragments, so computers assemble them by finding overlaps, like reconstructing a shredded book from many overlapping strips. Repetitive DNA makes this hard. Long-read technologies, reading tens of thousands of bases at once, finally gave a truly complete human genome in 2022.
Gene annotation
After assembly, annotation identifies where genes are and what they might do. Programs look for features like start and stop codons, splice sites, and similarity to known genes. Much annotation is predicted by computer and later checked by experiments.
Big data challenges
One human genome produces around 100 gigabytes of raw data. Projects sequencing millions of people require enormous storage and computing power. Bioinformaticians write programs, often in Python or R, and use cloud computing to process data efficiently.
Worked example
A FASTA record might be: a header line '>gene1 example' followed by 'ATGGCCATTGTAATG'. Counting bases: A = 4, T = 5, G = 4, C = 2, out of 15. GC content is (4 + 2) / 15 = 40%. GC content varies between species and regions of a genome, and is a simple first statistic computed for any sequence.
Key takeaways
Bioinformatics uses computing to analyse biological data. Sequencing has become fast and cheap since the Human Genome Project. Sequences are stored as text, often in FASTA format, in databases like GenBank, UniProt, and PDB. Genomes are assembled from overlapping reads and annotated to find genes. The data volumes are huge.
Flashcard
Computing applied to biological data
Check your understanding
A DNA sequence has 100 bases, of which 25 are G and 25 are C. What is its GC content?