1.3 In Silico

Recently, the new term in silico has become a common reference to biological studies carried out in the computer, joining the traditional terms in vivo and in vitro to describe the location of experimental studies.

For nonbiologists, in vitro means "in glass," that is, in the test tube; in vivo means "in life," that is, in a living organism. The term in silico stems from the fact that most computer chips are made primarily of silicon. Personally, I prefer a term such as in algorithmo, since there are plenty of ways to compute that don't involve silicon, such as the intriguing processes of DNA computing, quantum computing, optical computing, and more.

The large amount of biological data available online has brought biological research to a situation somewhat similar to physics and astronomy. Those sciences have found that experiments in modern equipment produce huge amounts of data, and the computer isn't only invaluable but necessary for exploring the data. Indeed, it's become possible to simulate experiments entirely in the computer. For instance, an early use of computer simulation in physics was in modeling the acoustics of a concert hall and then experimenting with the results by changing the design of the hall—clearly a much cheaper way to experiment than by building dozens of concert halls!

A similar trend has been occurring in biology since computers were first invented, but this trend has sharply accelerated in recent years with the Human Genome Project and the sequencing of the DNA of many organisms. The experimental data that has to be collected, searched, and analyzed is often far too large for the unaided biologist, who is now forced to rely on computers to manage the information.

Beyond the storage and retrieval of biological data, it's now possible to study living systems through computer simulation. There are standard and accepted studies done routinely on computers that access the genes of humans and of several other organisms. When the sequence of some DNA is determined, it can be stored in the computer, and programs can be written to identify restriction sites, perform restriction digests and create restriction maps (see Chapter 9). Similarly, gene-finding programs can take sequenced DNA and identify putative exons and introns. (Not perfectly, as of this writing, and results differ for different organisms.) Models of cellular processes exist in which it is possible to study for example, the effect of a change in the regulation of a gene.

Today, microarray technology (incorporating glass slides spotted with thousands of samples that can be probed, usually with the aid of robotics) can assess the levels of expression of thousands of genes with one laboratory run. Computers are helping to unravel the complex interactions between genes. We hope to find, for example, all sets of genes related by virtue of their protein products as part of a biochemical pathway in the cell. Microarrays generate a large volume of data. This data needs to be stored, compared with other experimental data, and analyzed on the computer.

On my first day as a programmer at Bell Labs Research, my boss told me that his simulations could now be computed so fast—overnight—that it was creating a problem for him. There wasn't enough time to think about the last simulation! Nevertheless, and despite all the attendant headaches and pitfalls of computers, their use to simulate experiments is proving to be beneficial in biology.