Several research groups are tackling highly complex biological systems by designing experiments that give unambiguous information even though the system is complex. Two important tools used by several of these groups are selective drugs and selective analytical tools. For example, if you have a sensor that can be put into a living rat brain and report on the concentration of a neurotransmitter, dopamine, in response to specific stimuli, then an enormous amount can be learned about how the brain works.
Similarly, drugs that alter a particular biological process can be used to deduce the molecular mechanism of a related process using whole cell approaches. Global information about proteomes or targeted proteomics analyses focusing on specific posttranslational modifications are being applied to understand cellular pathways involved in aging, immunosenescence, and neurodegenerative disease.
Some processes are so complex or inaccessible that the general behavior of the system is understandable only through computation. The complexities of finding drugs for viruses, and the related problem of biological evolution are studied here using computational methods common to statistical mechanics.