2 A Practical Guide to Cancer Systems Biology
Figure 1. The relationship between bioinformatics and omics data. Systems biology is
the first to generate biological big data — such as genome, transcriptome, proteome, and
metabonome — and then analyzes the data using a bioinformatics approach. In this way,
we can discover disease biomarkers and drugs as well as elucidate molecular regulations in
living organisms.
can we find important information in a sea of biological data? This is a
challenge that bioinformatics can tackle.
2.1. Genome
A genome is a complete set of genes or genetic material in a cell or
organism. The study of genomes is known as “genomics”, and it aims
to explore the DNA content and structure as well as the function and
evolution of genomes. From the data in National Center for Biotechnology
Information (NCBI, https://www.ncbi.nlm.nih.gov/genome/browse/), 4,
eukaryote and 95,217 prokaryote genomes have been sequenced. The size of
the human genome is over three billion base pairs which are organized into
22 paired chromosomes and the XX or XY chromosome. The human genome
contains coding and non-coding DNA. Coding DNA can be transcribed into
mRNAs and further translate into proteins; however, non-coding DNA can
be transcribed into RNAs but cannot be encoded into proteins.
The Cancer Genome Atlas (TCGA), previously known as the Human
Cancer Genome Project, has generated comprehensive, multidimensional
maps of the key genomic changes in 33 different tumor types in 11,
patients (https://cancergenome.nih.gov/). TCGA dataset has a total of 2.
PB of genomic data which were generated not only by microarrays but also
by using next generation sequencing techniques. These data are publicly
available.