| FEATURES & INNOVATIONS |
of RNA, collectively known as the transcrip- tome, present in 10,000 cells and, working up to a rate of 3,000 cells a day on average, plan to profile a million cells in two years. “It is a formidable data analytics challenge,”
says Prabhakar. Such single-cell analysis, he explains, could be used to compare healthy states with diseased states, or even to classify and diagnose patients more precisely. “The big data, precision-medicine dream
is to build a database on a national scale,” says Prabhakar — one that includes genome sequence data, RNA extracts, patient medical records, and other demographic intelligence. “Once the database is large enough, we will start to see patterns.” To really succeed in that endeavor, the GIS
has to work closely with the high performance computing experts at the IHPC and the hard- core data scientists at I2
R. “We are the muscle
behind the analytics,” says bioinformatician Feng Mengling.
MIX AND MATCH While researchers at the GIS are more familiar with interpreting genomic sequences, researchers at I2
The A*STAR Centre for Big Data and Integrative Genomics is building reference genomes for the Chinese, Malay and Indian populations in Singapore.
to analyse hundreds of genomes, and scaling it up with innovative improvements to analyse 10,000 genomes efficiently,” says Chaolong Wang, a computational geneticist at the GIS in charge of data analytics for SG10K.
CELL SCALE Every human being is born with a unique set of DNA. And every cell in their body typically contains an identical copy of this genetic barcode. So what differentiates brain cells from fat cells? How can we account for variation among cells the way we do for variation among people? The answer, for some, is big data. Mixed into the cellular soup are noodles
of RNA that provide a snapshot of the genes being expressed. Every cell has a unique RNA expression profile, which researchers at c-BIG are beginning to characterize through the Cellular Human Bodymap (CellHuB) project. They have already sequenced every tiny snip
36 A*STAR RESEARCH
extracting and analyzing other heterogeneous clinical information. In 2014 Feng and his team at I2
R devel-
oped a tool to assess the benefits of red blood cell transfusions. When to administer such interventions for patients in intensive care has been a subject of controversy. Their statistical evaluation was based on clinical reports of close to 40,000 individuals admitted to hospitals in the United States between 2001 and 2008. Feng’s work found that blood transfusions doubled the chance of survival for older, sicker patients, but halved survival rates in younger, healthier patients. Feng is also working with several hospitals in
Singapore to help them anticipate when a patient might need to undergo intubation. “It is a small operation but still requires a bit of prep time. We are developing a deep learning predictive model that will give clinical care staff 12 hours to prepare for the procedure,” says Feng, referring to a type of artificial intelligence that enables computers to learn by recognizing patterns. Many of these systems have been inspired by the neural networks in the human brain. Under c-BIG, A*STAR plans to collaborate with the academic medical centers in Singapore
R have extensive experience in
UNWELCOME SUPERBUGS In the time it takes to sequence a single human, machines can sequence a hundred bacterial genomes. “Bacteria are cheaper to sequence, which means that we can collect thousands or even millions of genomes to get a really fine- grained view of how bacteria evolve in an envi- ronment,” says Nagarajan, who is doing exactly that as part of a joint project between c-BIG and the GIS Efficient Rapid Microbial Sequencing (GERMS) platform known as Resistance and Outbreak Tracking in Singapore (ROUTES). Nagarajan is building a tool that can study
the diversity and evolution of the hundreds of trillions of bacteria residing inside the human gut. More specifically, he is looking at how some ‘superbugs’ become resistant to a last-resort class of antibiotics known as car- bapenems. Killing almost half of the patients they infect, these superbugs are spreading fast, from New York to Israel, Greece and further east, but they have yet to cause serious trouble in the Singaporean stomach. Nagarajan wants to find out how these
bacteria are transmitted between individuals, what conditions make them feel more or less welcome in the gut, and how their presence affects the gut environment. His research could even lead to potential remedies, whether it be a bacteria that the new residents find repulsive or one that can kill them. “There is an arms race within bacteria, and a lot of groups are searching the genetic information of microbial communities for potential antibiotics.”
ISSUE 5 | OCTOBER – DECEMBER 2016
to integrate clinical and genomic data for the first time to form one large pool of information that scientists and clinicians can dip into. “Data analytics can offer physicians the evidence needed to make more effective decisions, which will benefit their patients,” says Feng. Meanwhile, researchers at the IHPC are
developing high-performance artificial intelli- gence tools and a collaborative platform needed to power c-BIG. “We are excited to contribute our expertise and technologies in high-perfor- mance computing and artificial intelligence to efficiently and intelligently analyse the vast trove of medical and genomic data,” says computer scientist Rick Goh Siow Mong at the IHPC. “Through this program, we hope to advance the study of how specific medicine can be administered based on the detected variability in an individual — this is no mean feat.”
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