Computers helped drive breakthrough in human genome sequencing

At a White House press conference Monday, the Human Genome Project public consortium
and Celera Genomics, a private firm, jointly reported that they had assembled working
drafts of the human genome sequence. The two groups' presence on the same podium marked
an apparent truce in what has been a desperate push to be first to announce a decoded
human gene sequence.

While representing a breakthrough in scientific learning, the genome detective work
also represents something of a breakthrough in modern computing techniques. Distributed
computing and database technology as well as advanced search software and other
technologies were employed to reach the goal of uncovering the basic plan for human
life.

The work to create a genetic blueprint for a human being revealed a total of 3.12
billion base pairs in the human genome. An assembled genome is described as one on
which the location and order of the letters of genetic code along the chromosomes are
known. Computers are relied on to uncover matches in DNA sequences that serve to
unravel the code.

Some observers suggest that the work is leading to the creation of a new field of
technology known as bioinformatics. They say that a new discipline is arising out of
the wedding of computer science and biology.

For its part, Celera has hooked up DNA sequencers with a supercomputing facility
featuring 800 interconnected Compaq Alpha-based computer systems, each of which is
capable of performing more than 250 billion sequence comparisons per hour. Celera has
an alliance with Oracle for database development.

"The whole project has been about information acquisition and storage," said Bruce
Birren, assistant director of the Whitehead Sequencing Center in Cambridge, Mass., a
key participant in the Human Genome Sequencing Consortium.

"We've read out the four-letter code that represents the book of life," Birren said,
referring to the four-letter code that corresponds to DNA's four basic chemical
components. "We've always studied one gene at a time, but our perspective is changed
because we now see the entire landscape. That takes computational ability."

There is substantial analytical work yet to do in the field, as researchers look to
establish possible links between specific genes and specific traits. That next stage of
work may be counted on to drive further computing advances, even as computing advances
drive genome mapping forward.

"Now we're moving into a phase where interpreting [genetic] information is
going to require new analytical tools," Birren said. Researchers are already using a
mix of different advanced software technologies -- including neural networks, fuzzy
logic, and data smoothing -- to uncover patterns in the genetic data.

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