Arquivo da tag: Modelagem

Go With the Flow in Flood Prediction (Science Daily)

Uncategorized, , , , , , ,

Dec. 3, 2012 — Floods have once again wreaked havoc across the country and climate scientists and meteorologists suggest that the problem is only going to get worse with wetter winters and rivers bursting their banks becoming the norm. A team based at Newcastle University and their colleagues in China have developed a computer model that can work out how the flood flow will develop and where flooding will be worst based on an understanding of fluid dynamics and the underlying topology of a region.

Writing in the journal Progress in Computational Fluid Dynamics,Newcastle civil engineer Qiuhua Liang and colleagues and Chi Zhang of Dalian University of Technology and Junxian Yin, China Institute of Water Resources and Hydropower Research in Beijing, explain how they have developed an adaptive computer model that could provide accurate and efficient predictions about the flow of water as a flood occurs. Such a model might provide environmental agencies and authorities with a more precise early-warning system for residents and businesses in a region at risk of flood. It could also be used by insurance companies to determine the relative risk of different areas within a given region and so make their underwriting of the risk economically viable.

The model is based on a numerical solution to the hydrodynamic equations of fluid flow . This allows the researchers to plot the likely movement of water during a dam break or flash flood over different kinds of terrain and around obstacles even when flood waves are spreading rapidly. The researchers have successfully tested their model on real-world flood data.

The team points out that flood disasters have become a major threat to human lives and assets. “Flood management is therefore an important task for different levels of governments and authorities in many countries”, the researchers explain. “The availability of accurate and efficient flood modelling tools is vital to assist engineers and managers charged with flood risk assessment, prevention and alleviation.”

Journal Reference:

  1. Chi Zhang, Qiuhua Liang, Junxian Yin. A first-order adaptive solution to rapidly spreading flood waves.Progress in Computational Fluid Dynamics, An International Journal, 2013; 13 (1): 1 DOI: 10.1504/PCFD.2013.050645

When Leaving Your Wealth to Your Sister’s Sons Makes Sense (Science Daily)

Uncategorized, , , ,

ScienceDaily (Oct. 16, 2012) — To whom a man’s possessions go when he dies is both a matter of cultural norm and evolutionary advantage.

In most human societies, men pass on their worldly goods to their wife’s children. But in about 10 percent of societies, men inexplicably transfer their wealth to their sister’s sons — what’s called “mother’s brother-sister’s son” inheritance. A new study on this unusual form of matrilineal inheritance by Santa Fe Institute reseacher Laura Fortunato has produced insights into this practice.

Her findings appear October 17 in the online edition of Proceedings of the Royal Society B.

“Matrilineal inheritance is puzzling for anthropologists because it causes tension for a man caught between his sisters and wife,” explains Fortunato, who has used game theory to study mother’s brother-sister’s son inheritance. “From an evolutionary perspective it’s also puzzling because you expect an individual to invest in his closest relatives — usually the individual’s own children.”

For decades research on the practice of matrilineal inheritance focused on the probabilities of a man being the biological father of his wife’s children — probabilities that lie on a sliding scale depending on the rate of promiscuity or whether polyandrous marriage (when a woman takes two or more husbands) is practiced.

Of special interest has been the probability value below which man is more closely related to his sister’s children than to his wife’s children. Below this “paternity threshold” a man is better off investing in his sister’s offspring, who are sure to be blood relatives, than his own wife’s children.

In her work modeling the evolutionary payoffs of marriage and inheritance strategies, Fortunato looked beyond the paternity threshold to see, among other things, what payoffs there were for men and women in different marital situations — including polygamy.

“What emerges is quite interesting,” says Fortunato. “Where inheritance is matrilineal, a man with multiple wives ‘wins’ over a man with a single wife.” That’s because wives have brothers, and those brothers will pass on their wealth to the husband’s sons. So more wives means more brothers-in-laws to invest in your sons.

The model also shows an effect for women with multiple husbands. The husband of a woman with multiple husbands is unsure of his paternity, so he may be better off investing in his sister’s offspring.

“A woman does not benefit from multiple husbands where inheritance is matrilineal, however,” Fortunato explains, “because her husbands will invest in their sisters’ kids.” Family structure determines how societies handle relatedness and reproduction issues, Fortunato says. Understanding these practices and their evolutionary implications is a prerequisite for a theory of human behavior.

Journal Reference:

  1. Dr Laura Fortunato. The evolution of matrilineal kinship organization. Proceedings of the Royal Society B, October 17, 2012 DOI: 10.1098/rspb.2012.1926

Bits of Mystery DNA, Far From ‘Junk,’ Play Crucial Role (N.Y.Times)

Uncategorized, , , , , , , ,

By GINA KOLATA

Published: September 5, 2012

Among the many mysteries of human biology is why complex diseases like diabetes, high blood pressure and psychiatric disorders are so difficult to predict and, often, to treat. An equally perplexing puzzle is why one individual gets a disease like cancer or depression, while an identical twin remains perfectly healthy.

Béatrice de Géa for The New York Times. “It is like opening a wiring closet and seeing a hairball of wires,” Mark Gerstein of Yale University said of the DNA intricacies.

Now scientists have discovered a vital clue to unraveling these riddles. The human genome is packed with at least four million gene switches that reside in bits of DNA that once were dismissed as “junk” but that turn out to play critical roles in controlling how cells, organs and other tissues behave. The discovery, considered a major medical and scientific breakthrough, has enormous implications for human health because many complex diseases appear to be caused by tiny changes in hundreds of gene switches.

The findings, which are the fruit of an immense federal project involving 440 scientists from 32 laboratories around the world, will have immediate applications for understanding how alterations in the non-gene parts of DNA contribute to human diseases, which may in turn lead to new drugs. They can also help explain how the environment can affect disease risk. In the case of identical twins, small changes in environmental exposure can slightly alter gene switches, with the result that one twin gets a disease and the other does not.

As scientists delved into the “junk” — parts of the DNA that are not actual genes containing instructions for proteins — they discovered a complex system that controls genes. At least 80 percent of this DNA is active and needed. The result of the work is an annotated road map of much of this DNA, noting what it is doing and how. It includes the system of switches that, acting like dimmer switches for lights, control which genes are used in a cell and when they are used, and determine, for instance, whether a cell becomes a liver cell or a neuron.

“It’s Google Maps,” said Eric Lander, president of the Broad Institute, a joint research endeavor of Harvard and the Massachusetts Institute of Technology. In contrast, the project’s predecessor, the Human Genome Project, which determined the entire sequence of human DNA, “was like getting a picture of Earth from space,” he said. “It doesn’t tell you where the roads are, it doesn’t tell you what traffic is like at what time of the day, it doesn’t tell you where the good restaurants are, or the hospitals or the cities or the rivers.”

The new result “is a stunning resource,” said Dr. Lander, who was not involved in the research that produced it but was a leader in the Human Genome Project. “My head explodes at the amount of data.”

The discoveries were published on Wednesday in six papers in the journal Nature and in 24 papers in Genome Research and Genome Biology. In addition, The Journal of Biological Chemistry is publishing six review articles, and Science is publishing yet another article.

Human DNA is “a lot more active than we expected, and there are a lot more things happening than we expected,” said Ewan Birney of the European Molecular Biology Laboratory-European Bioinformatics Institute, a lead researcher on the project.

In one of the Nature papers, researchers link the gene switches to a range of human diseases — multiple sclerosis, lupus, rheumatoid arthritis, Crohn’s disease, celiac disease — and even to traits like height. In large studies over the past decade, scientists found that minor changes in human DNA sequences increase the risk that a person will get those diseases. But those changes were in the junk, now often referred to as the dark matter — they were not changes in genes — and their significance was not clear. The new analysis reveals that a great many of those changes alter gene switches and are highly significant.

“Most of the changes that affect disease don’t lie in the genes themselves; they lie in the switches,” said Michael Snyder, a Stanford University researcher for the project, called Encode, for Encyclopedia of DNA Elements.

And that, said Dr. Bradley Bernstein, an Encode researcher at Massachusetts General Hospital, “is a really big deal.” He added, “I don’t think anyone predicted that would be the case.”

The discoveries also can reveal which genetic changes are important in cancer, and why. As they began determining the DNA sequences of cancer cells, researchers realized that most of the thousands of DNA changes in cancer cells were not in genes; they were in the dark matter. The challenge is to figure out which of those changes are driving the cancer’s growth.

“These papers are very significant,” said Dr. Mark A. Rubin, a prostate cancer genomics researcher at Weill Cornell Medical College. Dr. Rubin, who was not part of the Encode project, added, “They will definitely have an impact on our medical research on cancer.”

In prostate cancer, for example, his group found mutations in important genes that are not readily attacked by drugs. But Encode, by showing which regions of the dark matter control those genes, gives another way to attack them: target those controlling switches.

Dr. Rubin, who also used the Google Maps analogy, explained: “Now you can follow the roads and see the traffic circulation. That’s exactly the same way we will use these data in cancer research.” Encode provides a road map with traffic patterns for alternate ways to go after cancer genes, he said.

Dr. Bernstein said, “This is a resource, like the human genome, that will drive science forward.”

The system, though, is stunningly complex, with many redundancies. Just the idea of so many switches was almost incomprehensible, Dr. Bernstein said.

There also is a sort of DNA wiring system that is almost inconceivably intricate.

“It is like opening a wiring closet and seeing a hairball of wires,” said Mark Gerstein, an Encode researcher from Yale. “We tried to unravel this hairball and make it interpretable.”

There is another sort of hairball as well: the complex three-dimensional structure of DNA. Human DNA is such a long strand — about 10 feet of DNA stuffed into a microscopic nucleus of a cell — that it fits only because it is tightly wound and coiled around itself. When they looked at the three-dimensional structure — the hairball — Encode researchers discovered that small segments of dark-matter DNA are often quite close to genes they control. In the past, when they analyzed only the uncoiled length of DNA, those controlling regions appeared to be far from the genes they affect.

The project began in 2003, as researchers began to appreciate how little they knew about human DNA. In recent years, some began to find switches in the 99 percent of human DNA that is not genes, but they could not fully characterize or explain what a vast majority of it was doing.

The thought before the start of the project, said Thomas Gingeras, an Encode researcher from Cold Spring Harbor Laboratory, was that only 5 to 10 percent of the DNA in a human being was actually being used.

The big surprise was not only that almost all of the DNA is used but also that a large proportion of it is gene switches. Before Encode, said Dr. John Stamatoyannopoulos, a University of Washington scientist who was part of the project, “if you had said half of the genome and probably more has instructions for turning genes on and off, I don’t think people would have believed you.”

By the time the National Human Genome Research Institute, part of the National Institutes of Health, embarked on Encode, major advances in DNA sequencing and computational biology had made it conceivable to try to understand the dark matter of human DNA. Even so, the analysis was daunting — the researchers generated 15 trillion bytes of raw data. Analyzing the data required the equivalent of more than 300 years of computer time.

Just organizing the researchers and coordinating the work was a huge undertaking. Dr. Gerstein, one of the project’s leaders, has produced a diagram of the authors with their connections to one another. It looks nearly as complicated as the wiring diagram for the human DNA switches. Now that part of the work is done, and the hundreds of authors have written their papers.

“There is literally a flotilla of papers,” Dr. Gerstein said. But, he added, more work has yet to be done — there are still parts of the genome that have not been figured out.

That, though, is for the next stage of Encode.

*   *   *

Published: September 5, 2012

Rethinking ‘Junk’ DNA

A large group of scientists has found that so-called junk DNA, which makes up most of the human genome, does much more than previously thought.

GENES: Each human cell contains about 10 feet of DNA, coiled into a dense tangle. But only a very small percentage of DNA encodes genes, which control inherited traits like eye color, blood type and so on.

JUNK DNA: Stretches of DNA around and between genes seemed to do nothing, and were called junk DNA. But now researchers think that the junk DNA contains a large number of tiny genetic switches, controlling how genes function within the cell.

REGULATION: The many genetic regulators seem to be arranged in a complex and redundant hierarchy. Scientists are only beginning to map and understand this network, which regulates how cells, organs and tissues behave.

DISEASE: Errors or mutations in genetic switches can disrupt the network and lead to a range of diseases. The new findings will spur further research and may lead to new drugs and treatments.

 

First Holistic View of How Human Genome Actually Works: ENCODE Study Produces Massive Data Set (Science Daily)

Uncategorized, , , , ,

ScienceDaily (Sep. 5, 2012) — The Human Genome Project produced an almost complete order of the 3 billion pairs of chemical letters in the DNA that embodies the human genetic code — but little about the way this blueprint works. Now, after a multi-year concerted effort by more than 440 researchers in 32 labs around the world, a more dynamic picture gives the first holistic view of how the human genome actually does its job.

William Noble, professor of genome sciences and computer science, in the data center at the William H. Foege Building. Noble, an expert on machine learning, and his team designed artificial intellience programs to analyze ENCODE data. These computer programs can learn from experience, recognize patterns, and organize information into categories understandable to scientists. The center houses systems for a wide variety of genetic research. The computer center has the capacity to store and analyze a tremendous amount of data, the equivalent of a 670-page autobiography of each person on earth, uncompressed.The computing resources analyze over 4 pentabytes of genomic data a year. (Credit: Clare McLean, Courtesy of University of Washington)

During the new study, researchers linked more than 80 percent of the human genome sequence to a specific biological function and mapped more than 4 million regulatory regions where proteins specifically interact with the DNA. These findings represent a significant advance in understanding the precise and complex controls over the expression of genetic information within a cell. The findings bring into much sharper focus the continually active genome in which proteins routinely turn genes on and off using sites that are sometimes at great distances from the genes themselves. They also identify where chemical modifications of DNA influence gene expression and where various functional forms of RNA, a form of nucleic acid related to DNA, help regulate the whole system.

“During the early debates about the Human Genome Project, researchers had predicted that only a few percent of the human genome sequence encoded proteins, the workhorses of the cell, and that the rest was junk. We now know that this conclusion was wrong,” said Eric D. Green, M.D., Ph.D., director of the National Human Genome Research Institute (NHGRI), a part of the National Institutes of Health. “ENCODE has revealed that most of the human genome is involved in the complex molecular choreography required for converting genetic information into living cells and organisms.”

NHGRI organized the research project producing these results; it is called the Encyclopedia of DNA Elements or ENCODE. Launched in 2003, ENCODE’s goal of identifying all of the genome’s functional elements seemed just as daunting as sequencing that first human genome. ENCODE was launched as a pilot project to develop the methods and strategies needed to produce results and did so by focusing on only 1 percent of the human genome. By 2007, NHGRI concluded that the technology had sufficiently evolved for a full-scale project, in which the institute invested approximately $123 million over five years. In addition, NHGRI devoted about $40 million to the ENCODE pilot project, plus approximately $125 million to ENCODE-related technology development and model organism research since 2003.

The scale of the effort has been remarkable. Hundreds of researchers across the United States, United Kingdom, Spain, Singapore and Japan performed more than 1,600 sets of experiments on 147 types of tissue with technologies standardized across the consortium. The experiments relied on innovative uses of next-generation DNA sequencing technologies, which had only become available around five years ago, due in large part to advances enabled by NHGRI’s DNA sequencing technology development program. In total, ENCODE generated more than 15 trillion bytes of raw data and consumed the equivalent of more than 300 years of computer time to analyze.

“We’ve come a long way,” said Ewan Birney, Ph.D., of the European Bioinformatics Institute, in the United Kingdom, and lead analysis coordinator for the ENCODE project. “By carefully piecing together a simply staggering variety of data, we’ve shown that the human genome is simply alive with switches, turning our genes on and off and controlling when and where proteins are produced. ENCODE has taken our knowledge of the genome to the next level, and all of that knowledge is being shared openly.”

The ENCODE Consortium placed the resulting data sets as soon as they were verified for accuracy, prior to publication, in several databases that can be freely accessed by anyone on the Internet. These data sets can be accessed through the ENCODE project portal (www.encodeproject.org) as well as at the University of California, Santa Cruz genome browser,http://genome.ucsc.edu/ENCODE/, the National Center for Biotechnology Information,http://www.ncbi.nlm.nih.gov/geo/info/ENCODE.html and the European Bioinformatics Institute,http://useast.ensembl.org/Homo_sapiens/encode.html?redirect=mirror;source=www.ensembl.org.

“The ENCODE catalog is like Google Maps for the human genome,” said Elise Feingold, Ph.D., an NHGRI program director who helped start the ENCODE Project. “Simply by selecting the magnification in Google Maps, you can see countries, states, cities, streets, even individual intersections, and by selecting different features, you can get directions, see street names and photos, and get information about traffic and even weather. The ENCODE maps allow researchers to inspect the chromosomes, genes, functional elements and individual nucleotides in the human genome in much the same way.”

The coordinated publication set includes one main integrative paper and five related papers in the journal Nature; 18 papers inGenome Research; and six papers in Genome Biology. The ENCODE data are so complex that the three journals have developed a pioneering way to present the information in an integrated form that they call threads.

“Because ENCODE has generated so much data, we, together with the ENCODE Consortium, have introduced a new way to enable researchers to navigate through the data,” said Magdalena Skipper, Ph.D., senior editor at Nature, which produced the freely available publishing platform on the Internet.

Since the same topics were addressed in different ways in different papers, the new website, www.nature.com/encode, will allow anyone to follow a topic through all of the papers in the ENCODE publication set by clicking on the relevant thread at the Nature ENCODE explorer page. For example, thread number one compiles figures, tables, and text relevant to genetic variation and disease from several papers and displays them all on one page. ENCODE scientists believe this will illuminate many biological themes emerging from the analyses.

In addition to the threaded papers, six review articles are being published in the Journal of Biological Chemistry and two related papers in Science and one in Cell.

The ENCODE data are rapidly becoming a fundamental resource for researchers to help understand human biology and disease. More than 100 papers using ENCODE data have been published by investigators who were not part of the ENCODE Project, but who have used the data in disease research. For example, many regions of the human genome that do not contain protein-coding genes have been associated with disease. Instead, the disease-linked genetic changes appear to occur in vast tracts of sequence between genes where ENCODE has identified many regulatory sites. Further study will be needed to understand how specific variants in these genomic areas contribute to disease.

“We were surprised that disease-linked genetic variants are not in protein-coding regions,” said Mike Pazin, Ph.D., an NHGRI program director working on ENCODE. “We expect to find that many genetic changes causing a disorder are within regulatory regions, or switches, that affect how much protein is produced or when the protein is produced, rather than affecting the structure of the protein itself. The medical condition will occur because the gene is aberrantly turned on or turned off or abnormal amounts of the protein are made. Far from being junk DNA, this regulatory DNA clearly makes important contributions to human health and disease.”

Identifying regulatory regions will also help researchers explain why different types of cells have different properties. For example why do muscle cells generate force while liver cells break down food? Scientists know that muscle cells turn on some genes that only work in muscle, but it has not been previously possible to examine the regulatory elements that control that process. ENCODE has laid a foundation for these kinds of studies by examining more than 140 of the hundreds of cell types found in the human body and identifying many of the cell type-specific control elements.

Despite the enormity of the dataset described in this historic collection of publications, it does not comprehensively describe all of the functional genomic elements in all of the different types of cells in the human body. NHGRI plans to invest in additional ENCODE-related research for at least another four years. During the next phase, ENCODE will increase the depth of the catalog with respect to the types of functional elements and cell types studied. It will also develop new tools for more sophisticated analyses of the data.

Journal References:

  1. Magdalena Skipper, Ritu Dhand, Philip Campbell.Presenting ENCODE. Nature, 2012; 489 (7414): 45 DOI:10.1038/489045a
  2. Joseph R. Ecker, Wendy A. Bickmore, Inês Barroso, Jonathan K. Pritchard, Yoav Gilad, Eran Segal. Genomics: ENCODE explained. Nature, 2012; 489 (7414): 52 DOI:10.1038/489052a
  3. The ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome.Nature, 2012; 489 (7414): 57 DOI: 10.1038/nature11247

Researchers Produce First Complete Computer Model of an Organism (Science Daily)

Uncategorized, , , , , ,

ScienceDaily (July 21, 2012) — In a breakthrough effort for computational biology, the world’s first complete computer model of an organism has been completed, Stanford researchers reported last week in the journal Cell.

The Covert Lab incorporated more than 1,900 experimentally observed parameters into their model of the tiny parasite Mycoplasma genitalium. () (Credit: Illustration by Erik Jacobsen / Covert Lab)

A team led by Markus Covert, assistant professor of bioengineering, used data from more than 900 scientific papers to account for every molecular interaction that takes place in the life cycle of Mycoplasma genitalium, the world’s smallest free-living bacterium.

By encompassing the entirety of an organism in silico, the paper fulfills a longstanding goal for the field. Not only does the model allow researchers to address questions that aren’t practical to examine otherwise, it represents a stepping-stone toward the use of computer-aided design in bioengineering and medicine.

“This achievement demonstrates a transforming approach to answering questions about fundamental biological processes,” said James M. Anderson, director of the National Institutes of Health Division of Program Coordination, Planning and Strategic Initiatives. “Comprehensive computer models of entire cells have the potential to advance our understanding of cellular function and, ultimately, to inform new approaches for the diagnosis and treatment of disease.”

The research was partially funded by an NIH Director’s Pioneer Award from the National Institutes of Health Common Fund.

From information to understanding

Biology over the past two decades has been marked by the rise of high-throughput studies producing enormous troves of cellular information. A lack of experimental data is no longer the primary limiting factor for researchers. Instead, it’s how to make sense of what they already know.

Most biological experiments, however, still take a reductionist approach to this vast array of data: knocking out a single gene and seeing what happens.

“Many of the issues we’re interested in aren’t single-gene problems,” said Covert. “They’re the complex result of hundreds or thousands of genes interacting.”

This situation has resulted in a yawning gap between information and understanding that can only be addressed by “bringing all of that data into one place and seeing how it fits together,” according to Stanford bioengineering graduate student and co-first author Jayodita Sanghvi.

Integrative computational models clarify data sets whose sheer size would otherwise place them outside human ken.

“You don’t really understand how something works until you can reproduce it yourself,” Sanghvi said.

Small is beautiful

Mycoplasma genitalium is a humble parasitic bacterium known mainly for showing up uninvited in human urogenital and respiratory tracts. But the pathogen also has the distinction of containing the smallest genome of any free-living organism — only 525 genes, as opposed to the 4,288 of E. coli, a more traditional laboratory bacterium.

Despite the difficulty of working with this sexually transmitted parasite, the minimalism of its genome has made it the focus of several recent bioengineering efforts. Notably, these include the J. Craig Venter Institute’s 2008 synthesis of the first artificial chromosome.

“The goal hasn’t only been to understand M. genitalium better,” said co-first author and Stanford biophysics graduate student Jonathan Karr. “It’s to understand biology generally.”

Even at this small scale, the quantity of data that the Stanford researchers incorporated into the virtual cell’s code was enormous. The final model made use of more than 1,900 experimentally determined parameters.

To integrate these disparate data points into a unified machine, the researchers modeled individual biological processes as 28 separate “modules,” each governed by its own algorithm. These modules then communicated to each other after every time step, making for a unified whole that closely matched M. genitalium‘s real-world behavior.

Probing the silicon cell

The purely computational cell opens up procedures that would be difficult to perform in an actual organism, as well as opportunities to reexamine experimental data.

In the paper, the model is used to demonstrate a number of these approaches, including detailed investigations of DNA-binding protein dynamics and the identification of new gene functions.

The program also allowed the researchers to address aspects of cell behavior that emerge from vast numbers of interacting factors.

The researchers had noticed, for instance, that the length of individual stages in the cell cycle varied from cell to cell, while the length of the overall cycle was much more consistent. Consulting the model, the researchers hypothesized that the overall cell cycle’s lack of variation was the result of a built-in negative feedback mechanism.

Cells that took longer to begin DNA replication had time to amass a large pool of free nucleotides. The actual replication step, which uses these nucleotides to form new DNA strands, then passed relatively quickly. Cells that went through the initial step quicker, on the other hand, had no nucleotide surplus. Replication ended up slowing to the rate of nucleotide production.

These kinds of findings remain hypotheses until they’re confirmed by real-world experiments, but they promise to accelerate the process of scientific inquiry.

“If you use a model to guide your experiments, you’re going to discover things faster. We’ve shown that time and time again,” said Covert.

Bio-CAD

Much of the model’s future promise lies in more applied fields.

CAD — computer-aided design — has revolutionized fields from aeronautics to civil engineering by drastically reducing the trial-and-error involved in design. But our incomplete understanding of even the simplest biological systems has meant that CAD hasn’t yet found a place in bioengineering.

Computational models like that of M. genitalium could bring rational design to biology — allowing not only for computer-guided experimental regimes, but also for the wholesale creation of new microorganisms.

Once similar models have been devised for more experimentally tractable organisms, Karr envisions bacteria or yeast specifically designed to mass-produce pharmaceuticals.

Bio-CAD could also lead to enticing medical advances — especially in the field of personalized medicine. But these applications are a long way off, the researchers said.

“This is potentially the new Human Genome Project,” Karr said. “It’s going to take a really large community effort to get close to a human model.”

Stanford’s Department of Bioengineering is jointly operated by the School of Engineering and the School of Medicine.