There were times when computers were big as a building and it required a degree to program them too, until the computer revolution came along.
Can't see why the same thing wouldn't happen with biotech.
The biology revolution is coming, both sooner and later than you think. As one indicator, the price per base pair of DNA synthesis is following a Moore's Law, (http://singularity.com/charts/page73.html), but Fredster is right in that there are other factors at play. However, you could say the same with computers, with bandwidth, cpu, and storage all improving simultaneously.
A story that our TA in EE40 (Signals in Systems) at Berkeley really stuck with me: in the early days of personal computing, when you would go to Radio Shack to buy a set of transistors, you had to individually test each one, because they had a 50% chance of not performing to spec. Biology currently is in that stage, though multiplied by another order of magnitude.
You can't possibly compare biotech to the computing industry in terms of where accessibility to the former is headed. Equipment costs may go down and education may become more accessible in biotech, but the risks to humans and property associated with running an entire lab will ensure access to non-trivial equipment and materials is granted only to those who are capable.
Biological systems are chaotic (in the mathematical definition). The more we want to manipulate the more we're going to have to know, to higher precision at the very least for the safety of any patients. It's not unreasonable to think that this will be a significant barrier for some time. We sequenced the human genome over a decade ago and, quote honestly, have gotten very little out of it. We can draw some neat graphs and hand wave a whole bunch but the reality is we haven't produced much from information. There are still, what, only a handful of fully sequenced genomes? And alleles are munged together. We can do some SNP correlation studies but that doesn't really tell you much. There is a lot of BioTech search to come, just in genomics, and it's going to take some big steps before it becomes accessible to someone in their garage, IMO.
Just to pick you up on one thing, we have sequenced thousands upon thousands of genomes since the human genome project finished.
For example there is the 1000 genomes project [1], and a project I am working on is sequencing about 100 ovarian cancer tumor / normal pairs. Most of this sequencing is complete, its the bioinformatics that takes the time.
GWAS studies (studies of correlation between disease and common SNP's) have not told us much that is actionable, but have provided us with "low hanging fruit" for further study, which is valuable.
Its very early ways, but genomics will completely change the diagnosis and treatment of cancer over the next 10 years.
I'm curious what the world will look like when we are smart enough to become actionable with this information. Do we want to live in a world where someone in their garage can come up with a drug idea and send it to a PharmaFoundry to get their drug fabed and then sell it to people?
Correct me if I am wrong, but we have sequenced thousands of genomes but not human. We only have a handful where handful is < 1000) of full human genomes AFAIK. 1000 genomes isn't done yet AFAIK (their page on sequencing progress is down unfortunately). The human reference genome is a mishmash of multiple genomes. It also contains huge sections of chromosomes that are just N's (blank) because assemblers are unable to determine what goes there. On top of that, an actual human genome is not one genome. At they very least there are alleles which can be different from each other and in general there can be many genomes (cancer). Haploid sequencing is coming, hopefully soon, if SMRT really pans out but, in my opinion, to say our knowledge of even the sequence data in a human is adequate is a stretch (I'm not saying that you said that).
A story that our TA in EE40 (Signals in Systems) at Berkeley really stuck with me: in the early days of personal computing, when you would go to Radio Shack to buy a set of transistors, you had to individually test each one, because they had a 50% chance of not performing to spec. Biology currently is in that stage, though multiplied by another order of magnitude.