That’s why a group of researchers from Columbia University and Stanford University developed an algorithm that can do just that, turning those cells into something that resembles your social graph. This lets researchers see how the various cells are related to each other so they know , for example, where to focus cancer treatment and what to track as that treatment progresses.

The idea of representing large or complex data as a graph is nothing new, but it has taken on more prominence thanks to the rise of social media and those ubiquitous social graphs that map out who’s connected to whom. As we highlighted recently, however, graph analysis is becoming more popular outside the realm of social networks, and is being applied to problems that are more complex than just figuring out simple relationships within a network. In cases such as medical research, especially, graphs can provide a very effective way of seeing how potentially hundreds of thousands of data points spanning perhaps hundreds of variables are similar to each other.

That’s exactly what the team at Columbia and Stanford has done with a new algorithm that they’ve demonstrated within the realm of mass cytometry. According to a press release announcing the research (which is available via paid download at Nature Biotechnology):

“The method, called viSNE (visual interactive Stochastic Neighbor Embedding), is based on a sophisticated algorithm that translates high-dimensional data (e.g., a dataset that includes many different simultaneous measurements from single cells) into visual representations similar to two-dimensional ‘scatter plots’ ….

“The viSNE software can analyze measurements of dozens of molecular markers. In the two-dimensional maps that result, the distance between points represents the degree of similarity between single cells. The maps can reveal clearly defined groups of cells with distinct behaviors (e.g., drug resistance) even if they are only a tiny fraction of the total population. This should enable the design of ways to physically isolate and study these cell subpopulations in the laboratory.”

I assume they say similar to scatter plots because the algorithm is analyzing data across more than two dimensions, although the resulting chart is essentially the same (i.e., data points with similar characteristics will form clusters).

The results of viSNE, showing cell densities in diagnosis and relapse samples.

Whether or not they’re technically similar, this research seems similar to what Ayasdi is doing with its new data-analysis software based on a technique called topological data analysis. In both cases, though, the algorithms aren’t necessarily concerned with how data points interact with one another (like in network graphs), but rather what similar characteristics the points share. Ayasdi’s software has been used in cancer research, too, including on datasets spanning hundreds of patients and tens of thousands of variables.

In theory — although not likely in practice considering the complexity of the datasets medical researchers are dealing with — these approaches are similar to clustering approaches that are also popular among data scientists working with web companies. In areas such as e-commerce or email management, for example, where there isn’t a strong social element, companies can broadly break customers into distinct groups based on their behavior or interests.

A sample cluster of MailChimp subscribers.

Of course, curing cancer is a slightly more compelling — and difficult — goal than targeted advertising. The algorithms have to be precise so as not to miss similarities hidden within the mass of data. In the case of viSNE, the researchers say they’ve been able to spot small groups of cells (like 20 out of tens of thousands) that might be able to survive chemotherapy and increase the likelihood of a recurring tumor.

But we probably shouldn’t bee too quick to discount the work that web companies do as somehow less valuable than that of cancers researchers, for example. The big data era arguably started with the web, and web companies have generated some of the most important data-analysis techniques and technologies around today (see, for example, Google’s Jeff Dean, with whom I’ll be speaking at our Structure conference next month). As medical researchers start generating more and more data via cytometry, genome sequencing and even electronic medical records, it will be critical for individuals in all fields to keep track of what data scientists in other fields are doing and figure out how that might apply to their own work.

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Compliance with the Health Insurance Portability and Accountability Act means that Box provides file redundancy to prevent data loss in a disaster, restrictions on employees’ access to documents, a breach-notification policy, data encryption and other features.

Beyond talking about meeting regulatory standards, Box is also promoting 10 new partner applications in its marketplace, including the drchrono iPad application for viewing electronic health records and the TigerText Software-as-a-Service (SaaS) for texting and sharing documents among health care providers.

It’s not as though Box has yet to take on business from health care companies, though. It’s got hundreds of paying health care customers, said Whitney Bouck, general manager of Box Enterprise. Customers include the Garden City Hospital and the Henry Ford Health System, both in Michigan, according to a Box statement. Still, Bouck said that because of the HIPAA compliance and application partnerships, the company expects a much higher annual revenue growth rate in the health care area than the companywide figure, which stands at 160 percent.

Adding creature comforts to entice customers in health care and other sectors is important for the cloud-storage contenders such as Box, Dropbox and at least a dozen other storage providers, all of which want to become the Dropbox of the enterprise. Box is following Salesforce.com, Microsoft and other cloud collaboration providers by connecting with apps catering to industries. At the same time, those software giants are adding Box-like cloud storage capabilities of their own.

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Healthcare IT in infancy

In 1969, just six weeks after NASA landed the first men on the moon, the first $20 bill was dispensed from an automated teller machine. IT systems have since revolutionized financial services, and as a result banks have since saved billions of dollars as consumers first used ATMs for deposits and withdrawals, and then started to pay their bills and make purchases online. According to a Bain & Co. brief, transaction costs have dropped from $4 at the teller window to just 8 cents when paying a bill via a smartphone.

From my perspective, healthcare IT is still just a few paces beyond where the financial services industry was in 1969.

Electronic health records (EHR), the backbone of health IT systems, are a perfect example of the health system effectively using technology to both improve care and reduce costs. For those healthcare systems that have proactively decided to digitize, EHRs are already proving to save lives and costs, from identifying redundant tests and dangerous drug interactions to revealing trends in treatment outcomes.

For example, we have used EHRs at Kaiser Permanente to analyze a database of 1.4 million members, and that led to the discovery that the widely used COX-2 pain reliever Vioxx was dangerous; the drug was eventually taken off the market. It took a large data set and the right tools to find this lifesaving information.

IT costs growing faster than healthcare

The following market research indicates that spending on health care IT will grow at an even faster rate than overall healthcare spending:

• According to Insight Research, health care IT spending will grow 9.7 percent annually between 2012 and 2017. That compares to an annual 6.4 percent growth rate in overall healthcare spending.
• Neal Patterson, founder and CEO of Cerner, the world’s largest stand-alone developer of healthcare IT (HIT) systems, told Forbes magazine in May 2012 that he expects HIT sales in the U.S. to double or even quadruple by 2020 – growing from $5 billion to $10 billion annually.

Opportunities for entrepreneurs

Investing in innovative health IT is a winning strategy for entrepreneurs. Here are three opportunities that I find particularly compelling:

Cloud computing 

Cloud computing is one disruptive technology that makes setting up and running an electronic health record faster, simpler and more affordable. Bain & Co. suggests that the move to cloud computing could cut costs from 30 percent to 40 percent compared to legacy IT systems. That’s a big selling point. The smartest new EHR vendors go the extra mile to guarantee, as Athena Health does, that their systems will allow a practice to qualify for Medicare Meaningful Use payments (a government incentive program for health care professionals).  This is a smart strategy for vendors, as it gives healthcare providers an income stream that will help defray the cost of adopting the technology.

Big data analytics

Here at Kaiser Permanente, the 1-2 terabytes of data we’ve collected every day since 2003 have resulted in a patient database that’s larger than the Library of Congress. Our system can analyze and leverage this massive dataset with a variety of tools: Predictive analytics, clinical decision support, data mining, and natural language processing, among them. What we have learned has changed the way we, and doctors around the world, practice medicine. Big data has already attracted the attention of major players like Dell, Intel, and Oracle.

But storage also offers fertile ground for exploration: Providers now dump nearly 90 percent of data they generate due to storage issues – literally trashing valuable information that could save lives.

Mobile health

Mobile capabilities offer incredible opportunities to advance the way healthcare is administered, chiefly through telemedicine (the delivery of care via telecommunication technologies like video) and telehealth (remotely provided preventive health services, such as patient education and e-mail consultation). It’s all about high-tech tracking and high-touch connection. Existing innovations include portable pulse oximeters that can send data on pulse and blood oxygen rate from a patient sitting at home to his doctor, in real time. According to BCC Research, these technologies were a $3.5 billion global market in 2011, and are expected to reach $9.7 billion by 2016.

No one can deny the stakes in health IT are high, but the rewards we stand to gain are even higher. Some rewards are financial. Reducing our overall healthcare expenditures would strengthen our economy and ease the financial burden of healthcare on individuals and family. But the biggest rewards are intangible: higher quality care enabled by health IT will provide better health outcomes, and a healthier population.

Phil Fasano is executive vice president and chief information officer of Kaiser Permanente, the nation’s largest not-for-profit health plan and health care provider, and author of Transforming Healthcare: The Financial Impact of Technology, Electronic Tools, and Data Mining.

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For the past two years, the EMR company, which was co-founded by the country’s CTO Todd Park (before his Washington, DC career), has tried to encourage more openness and innovation with hackathons and conferences through its “More Disruption Please” campaign. But this week, the company said it’s taking its biggest pro-developer step yet with an API (application programming interface) initiative launched in partnership with API management company Mashery.

“Our point of view is that the largest barrier to entry for a lot [health companies] is access to physicians and access to their work flow,” said Armbrester, the company’s director of business development. “What we really want to do is expose APIs and let people build things.”

Starting this week, developers and providers will be able to access APIs that connect to athenahealth’s network of 40,000 providers nationwide.  With access to doctors’ appointment data, patient’s medical history (anonymized , billing information and more, the company hopes developers will be able to create an ecosystem of apps on top of athenahealth’s EMR service in the same way that third-party developers have created apps on top of Facebook’s Open Graph.

Possible apps could help doctors with scheduling, sharing information with other practices, communicating with patients and getting patients to stick to their treatment plans, Armbrester said.

The next step, he added, is the creation of an Apple-like app store where physicians can pick and choose the apps most relevant to their needs. Other EMR providers, including Allscripts and Greenway, have also opened up their APIs to developers and created app marketplaces. But Armbrester said that unlike most traditional health care companies, athenahealth’s multi-tenant cloud-based architecture means that it can roll out application updates to all providers at once.

While the industry has been mostly slow to open up to third-party developers, others have started innovating from the outside. The SMART (Substitutable Medical Applications & Reusable Technology) Platforms Project, led by doctors at Harvard Medical School and Boston Children’s Hospital, is creating an ecosystem of apps that can be layered on top of existing EMRs. Once a vendor or hospital IT department implements a software container, hospitals can install SMART apps, which include interactive growth charts for pediatricians, and cardiovascular risk assessments for cardiologists. Last month, mobile API company Apigee said it was creating an API exchange that could be used in health care to help developers write one app that could be used across different hospitals and health organizations.

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As individuals, doctors probably don’t see enough of any given adverse reaction to notice patterns emerging. But as a collection, their notes on patients’ medical records can provide valuable insights, as a group of Stanford researchers recently discovered. Using “18 years of patient data from 1.8 million patients [consisting of] 19 million encounters, 35 million coded ICD-9 diagnoses, and >11 million unstructured clinical notes,” the team was able to accurately identify interactions by analyzing the free-form text that doctors had entered about patients’ symptoms, conditions and prescription regimens.

A key aspect to being able to predict adverse interactions is understanding the relationships among the different sets of terminologies used in different medical fields. It’s a lot easier to spot patterns across hospitals or even an individual patients’ records when you know that a radiologist writing X is the same, or related to, an oncologist writing Y. We covered an earlier collaboration between the study’s leader, Nigam Shah, and medical-data startup Apixio around this very topic in 2011.

How Shah’s team developed its patient-feature matrix

Shah and his team hope their work can complement the current process for tracking drug reactions, the FDA’s Adverse Event Reporting System. Whereas that system requires doctors and patients to manually alert the FDA of potential adverse side effects, their method could highlight potential problems that no one noticed or took the time to report. I’d consider this similar to some early research by social medical sites such as PatientsLikeMe, whose users are producing lots of data about their conditions, drugs, dosages and side effects that could produce correlations ripe for controlled experiments.

A press release announcing the study’s publication highlights some of its future promise and current limitations:

“[T]he research team is working on refinements that will cull even more useful information from clinical notes, such as reports of reactions caused by drug combinations, the use of medications typically prescribed for one condition but found effective for treatment of a different health problem, or finding medical profiles of patients that fit a certain scenario. …

One downside is that most electronic health record systems are set up for patient care, not patient research, Goodman noted. In this study, the researchers mined a data system created for this kind of research, which isn’t widely available. The researchers used the Stanford Translational Research Integrated Database Environment, known as STRIDE.”

This is just one of many ways in which researchers are experimenting with big data concepts to help medical professionals make sense of more data than they could possibly analyze on their own. Other examples we’ve covered recently include an artificial intelligence model for prescribing safe, cost-effective treatments, the application of Google PageRank-like algorithms to map the spread of cancer cells throughout the body, and the use of graph data structures to organize highly complex sequencing data.

Feature image courtesy of Shutterstock user Maksym Dykha.

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An abundance of newly available information — from research and development data aggregated by pharmaceutical companies to digitized patient records to recently-released health information from the federal government and other public sources — combined with new technology has the potential to transform health. But, according to the report, to really “jujitsu” that data (as the country’s CTO Todd Park likes to say), the industry may need to shift its thinking and scale some obstacles first.

“Stakeholders will only benefit from big data if they take a more holistic, patient-centered approach to value, one that focuses equally on health-care spending and treatment outcomes,” McKinsey’s report said.

To do that, the analysis laid out a few guidelines, including:

• encouraging patients to take more active steps to improve their health
• developing an integrated approach to care in which all caregivers have access to the same information
• selecting health care providers based on skill sets, not job titles (for example, having nurses perform tasks traditionally doctor-required duties)
• looking for ways to improve value while improving care quality (for example through systems that tie provider reimbursement to patient outcomes)
• identifying new and innovative approaches to treatment and care delivery

With those approaches, McKinsey estimates that the use of big data could save health care stakeholders $300 to $450 billion in health care costs, or 12 to 17 percent of the $2.6 trillion baseline in U.S. health-related spending.

Already, big companies and emerging startups are leading the way in the smart use of data. At GigaOM’s recent Structure: Data conference, Aetna’s head of innovation Michael Palmer talked about how the company is using data to prevent diabetes and heart attacks. Startup Asthmapolis (which this week raised $5 million) is using GPS data collected via sensors attached to inhalers to help individuals, physicians and public health officials uncover asthma-related patterns.

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It’s not an organization you’d expect to see courting young tech founders and Silicon Valley venture capitalists. But if you’re a startup, particularly a health startup, get ready to see more of the nonprofit, which is on a mission to both bring more innovation to the 50+ crowd and sow some entrepreneurial seeds among people in that demographic.

To twenty-something startup founders, building services and products for silver-haired seniors might not seem as sexy as taking on messaging apps like Snapchat. But the AARP has some strong statistics on its side: every day, 10,000 more Baby Boomers join the 50+ demographic, which includes more than 100 million people, and, as a group, they spend $3.5 trillion a year.

Among policy wonks in D.C., addressing the needs of older Americans is seen as a burden, said Jody Holtzman, AARP’s SVP of thought leadership.  But for startups and investors? It’s an opportunity, he said. “You’d really have to be an idiot to turn your back on the only humongous growth market that exists,” he quipped.

The ‘Longevity Economy’

In 2011, the non-profit launched its “Innovation@50+” campaign at the DEMO startup conference, with scholarships for startups that either target the 50+ market or included a 50+ founder.  In April, it will host its second annual Health Innovation@50+ LivePitch event, in which selected startups pitch in front of investors and a voting crowd of AARP members.

But this year it also partnered with the Ewing Marion Kauffman Foundation for a startup training program for Baby Boomers, funded Oxford Economics research into what the AARP calls the “longevity economy” and, this October, will back a Bloomberg conference exploring the costs and opportunities associated with longer life expectancies.

Some of the startups it has supported have gone on to attract attention from other accelerators and venture capitalists: Carelinx, for example, the winner of its Live Pitch event last year, went on to join the Startup Health Academy, and NeuroTrack, which graduated from health accelerator Rock Health, recently took the health prize at the SXSW startup accelerator.

Overcoming the youth bias

When the AARP first launched its campaign, Holtzman said, they were the ones making cold calls to health tech accelerators. Now, he says, they’re on the receiving end of that communication. In the not so far off future, as it looks for additional ways to encourage innovation to benefit those over 50, it’s possible that the AARP could sponsor an entire class at one of the new incubators for health startups.

Its efforts are being aided by growing interest in general digital health startups, many of which target senior needs. But getting venture capitalists to embrace older entrepreneurs could be a different kind of challenge. A couple of years ago, investor Vinod Khosla said at a conference that “people over 45 basically die in terms of new ideas.” And, judging from all the recent college grads (and college dropouts) that get venture funding, he’s obviously not the only investor to favor younger favors.

“The bad news is that most traditional VCs have a youth bias that they will state very overtly,” said Steve Jurvetson, managing director at venture firm Draper Fisher Jurvetson. “You always wonder if that’s a self-fulfilling prophecy or if it’s something about the nature of those businesses.”

Are younger founders really more successful?

Despite Silicon Valley’s preference for young entrepreneurs, the research may not be on their side. A 2008 study led by columnist and Singularity University vice president of innovation and research Vivek Wadhwa looked at 502 successful engineering and tech companies. It found that the average and median age of successful founders was 39 and that twice as many founders were older than 50 as were younger than 25. It also found that there were twice as many founders over 60 as under 20.

Jurvetson has long talked up the value of the 50+ demographic and his firm has invested in several companies with applications for, and/or led by, those who are 50+. Posit Science, for example, provides brain-training software that can be used as part of elder care (as well as for anyone hoping to sharpen their mind), and its co-founder and chief scientific officer, Michael Merzenich, was over 50 when it launched. Other companies include Rethink Robotics, founded by 58-year-old Rodney Brooks, and Synthetic Genomics, founded by 66-year-old Craig Ventner and 81-year-old Hamilton Smith.

According to the AARP, hundreds of new startups are founded by seniors — one of the first startups to benefit from its DEMO scholarship, called OhMyMeds, was co-founded by a 71-year-old (it later went out of business). And it makes sense that after decades in a given industry, older professionals would have the experience and perspective to start their own business. To date, the majority do so without ever looking for venture capital. But, in the future, it’s possible senior startup founders could find that they have another source of investment: the AARP.

“I hope that down the road, we’d be in a position to invest or invest in funds looking at opportunities in the space,” Holtzman said. “But we’re not there yet.”

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Speaking with my colleague Ki Mae Heussner at GigaOM’s Structure:Data conference on Wednesday, Aetna’s head of innovation, Michael Palmer, opened up about the Innovation Labs’ initiatives, the challenges they face and the neat opportunities ahead.

The Innovation Labs has focused on a few conditions since starting last year, including cancer, heart disease and metabolic syndrome. There are five telling signs to metabolic syndrome, including a large waist circumference and high blood pressure. Metabolic syndrome is a sort of gateway for diabetes, cardiovascular issues and other conditions, so Aetna wants to prevent patients from getting metabolic syndrome in the first place. It has started using data on 18 million of its customers’ employees to tell doctors which of the five signs of metabolic syndrome their patients are likely to get in the next year, Palmer said.

Aetna appears to want to pull in more kinds of data for patients and physicians to examine to provide better care. Asked if Aetna will start working in genomic data, Palmer said the Aetna Innovation Labs are running a pilot with some companies to allow patients to get their own genetic information and receive genetic counseling. “That will drive a wellness program driven around genomics,” he said.

And social information from patients could provide much-needed feedback to show how effective a medication is in real time, for that patient and for others. “Some companies are doing that,” Palmer said, referring to incorporating social streams into health care. “The challenge is, a lot of HIPAA laws prevent the ability to connect those two in a way that would be ultimately useful,” he said.

Aside from regulatory compliance, patients simply might not want to share as much data as insurers and doctors want them to, as it could get out to the wider public. Keeping health data out of employers’ hands, for example, is playing out right now, as Ki Mae mentioned, with media outlets reporting on Wednesday that CVS employees provide health information or pay up. But Palmer said Aetna has been working with large patient data sets for many years, though, and is cognizant of complying with HIPAA laws.

It’s ironic, but Aetna — and probably others in the health care community — finds a challenge in getting people to work on their own health. Companies want to see that, so their employees will stay healthier and work more, Palmer said.

Toward that end, Aetna is looking to work with other companies, mainly small startups, on what Palmer called “medication adherence” — texting, calling or otherwise contacting patients about taking their medications and doing other things to improve their health. It’s not easy, though, because, as Palmer said, what works for some patients doesn’t necessarily work for others.

Check out the rest of our Structure:Data 2013 coverage here, and a video embed of the session follows below:

A transcription of the video follows on the next page

Go to page 2 (of 2) on GigaOM .

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To help give hospitals and health care providers more clarity around the good, bad and ugly in mobile health apps, New York-based Happtique has been working on a certification program for mobile apps and on Wednesday plans to release its final set of standards.

“One of the things I hear all the time when I’m dealing with providers and institutions is ‘hey, there are so many apps out there, how do we know which ones have just even been looked at by clinicians? … Or within [a category] ‘how do we decide which ones that we’ll use or recommend to patients?’,” said Ben Chodor, CEO of Happtique. “They just need somewhere to turn where at least these apps have been peer-reviewed and scanned so we know that they’re safe.”

In the past year, Happtique has enlisted experts and patient advocates to serve on its standards committee, and it’s met with hospital and medical associations and government agencies to hear their feedback. Last July, it released a draft of its standards to give developers, care providers and other health care professionals the opportunity to comment.

The final standards released Wednesday cover not only technical performance, including operability, privacy and security, but content standards. For example, they encompass issues like the credibility of an app’s information and sources, the fairness of its description and claims, compliance with rules and regulations and advertising disclosures.

Chodor said they’re intended to give health care providers and consumers a Good Housekeeping-like “seal of approval” to look for, as well as provide app developers a set of guidelines to build to and a way to show customers their value.

The Food and Drug Administration is still expected to hand down its own guidelines — and Happtique says its standards will shift to follow federal regulations. But the FDA will only cover some mobile apps, leaving others in a gray area still helped by an industry standard, Chodor said, adding that Happtique could also be a feeder to the FDA.

Still, even though mobile health could certainly be helped by standards, some argue that Happtique’s plan is unfolding a little too early because there aren’t enough good apps worth filtering out. And, in the vast and quickly growing world of mobile health, Happtique will have to establish itself as a trusted, known name. But its pedigree and partnerships will likely serve it well — not only did it grow out of the hospital community (it was incubated in the venture arm of the Greater New York Hospital Association), it’s signed on impressive clients, including Mount Sinai Hospital, Hospital for Special Surgery and St. Lukes Houston.

While Happtique’s final guidelines will be released Wednesday, it won’t start taking submissions from developers until this spring. At that time, app developers interested in certification will pay $2,500 to $3,000 and then it will go to third-party partners for review. The Association of American Medical Colleges and the Commission on Graduates for Foreign Nursing Schools (CGFNS), a credentialing authority for healthcare professionals, will review the content and Intertek will scan for technical performance.

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If a group of Silicon Valley luminaries have their way, scientists working on some of the world’s most intractable diseases will be like superheroes for future generations.  On Wednesday, Apple Chairman Art Levinson, Google co-founder Sergey Brin, 23andMe co-founder (and wife of Brin) Anne Wojcicki, Facebook CEO Mark Zuckerberg, Zuckerberg’s wife Priscilla Chan and investor Yuri Milner announced a new Breakthrough Prize recognizing achievement in life sciences research. Administered through a new Breakthrough Prize in Life Sciences Foundation, the prize will be awarded to five individuals or teams annually but this year 11 inaugural recipients received $3 million each.

Speaking at a presentation event Wednesday at the University of California, San Francisco Wojcicki said that given her father’s position as a Stanford University physicist she grew up appreciating the work of scientists, but that society generally tends to overlook their contributions.

“To me it always seemed like it was a real tragedy -– we all go to the doctor, we’ve all taken Tylenol and Advil and some of us have been sicker and have had to take other medications,” she said.  “But do you ever think about who actually invented that? Does anyone know the names of those people?”

Zuckerberg emphasized that the while the prize was meant to recognize researchers at the top of their fields, it’s also intended to inspire future scientists.

“I think that our society needs more heroes who are scientists and researchers and engineers. You guys are doing all of the amazing work and the thing that we can do from the sidelines is build institutions that celebrate and reward and recognize all of the real work,” he said. “The things that we talk about in the media and the things the market rewards has a big influence on what the next generation of people growing up will choose to do and I think it’s really important that a lot of the smartest people go and choose to solve these problems and go into these lines of work.”

To ensure that the ones making the top contributions are the ones deciding who gets recognition, winners will help select future recipients of the prize. Also, anyone can nominate a candidate online and there are no age restrictions.

Here are the first 11 winners (language from the Breakthrough Prize in Life Sciences Foundation):

Cornelia I. Bargmann
Torsten N. Wiesel Professor and Head of the Lulu and Anthony Wang Laboratory of Neural Circuits and
Behavior at the Rockefeller University. Howard Hughes Medical Institute Investigator.

For the genetics of neural circuits and behavior, and synaptic guidepost molecules.

David Botstein
Director of the Lewis-Sigler Institute for Integrative Genomics and the Anthony B. Evnin Professor of
Genomics at Princeton University.

For linkage mapping of Mendelian disease in humans using DNA polymorphisms.

Lewis C. Cantley
Margaret and Herman Sokol Professor and Director of the Cancer Center at Weill Cornell Medical
College and New York-Presbyterian Hospital.

For the discovery of PI 3-Kinase and its role in cancer metabolism.

Hans Clevers
Professor of Molecular Genetics at Hubrecht Institute.

For describing the role of Wnt signaling in tissue stem cells and cancer.

Titia de Lange
Leon Hess Professor, Head of the Laboratory of Cell Biology and Genetics, and Director of the Anderson
Center for Cancer Research at the Rockefeller University.

For research on telomeres, illuminating how they protect chromosome ends and their role in genome
instability in cancer.

Napoleone Ferrara
Distinguished Professor of Pathology and Senior Deputy Director for Basic Sciences at Moores Cancer
Center at the University of California, San Diego.

For discoveries in the mechanisms of angiogenesis that led to therapies for cancer and eye diseases.

Eric S. Lander
President and Founding Director of the Eli and Edythe L. Broad Institute of Harvard and MIT. Professor of
Biology at MIT. Professor of Systems Biology at Harvard Medical School.

For the discovery of general principles for identifying human disease genes, and enabling their
application to medicine through the creation and analysis of genetic, physical and sequence maps of the
human genome.

Charles L. Sawyers
Chair, Human Oncology and Pathogenesis Program at Memorial Sloan-Kettering Cancer Center. Howard
Hughes Medical Institute Investigator.

For cancer genes and targeted therapy.

Bert Vogelstein
Director of the Ludwig Center and Clayton Professor of Oncology and Pathology at the Johns Hopkins
Sidney Kimmel Comprehensive Cancer Center. Howard Hughes Medical Institute Investigator.

For cancer genomics and tumor suppressor genes.

Robert A. Weinberg
Daniel K. Ludwig Professor for Cancer Research at MIT and Director of the MIT/Ludwig Center for
Molecular Oncology. Member, Whitehead Institute for Biomedical Research.

For characterization of human cancer genes.

Shinya Yamanaka
Director of Center for iPS Cell Research and Application, Kyoto University
Senior Investigator, Gladstone Institutes, San Francisco

For induced pluripotent stem cells.

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