Cloud Gives DNA Compiler Wings

By Tiffany Trader

August 5, 2014

Imagine being able to turn bacteria into molecular factories, capable of producing everything from earth-friendly biofuels to personalized medicines? This is the promise of synthetic biology, which has made remarkable advances over the last decade, taking tools and concepts from physics, engineering and computer science to design new biological systems.

One of the foremost researchers in the field is Professor Howard Salis. An assistant professor at Penn State University, Salis developed a cloud-based software platform, called DNA Compiler, to support the efforts of synthetic biology researchers around the world.

In an interview with HPCwire, Salis explains that even the simplest bacterium has more moving parts than an automobile, but nature did not provide exact design specifications for how those living organisms function.

One of the primary goals of microbiology and genomics is to reverse-engineer these design specifications. In synthetic biology and in metabolic engineering, the objective is to forward engineer non-natural organisms in order to solve humanity’s problems.

“It’s a long-term goal of the world to reduce reliance on petrochemical feedstock and to manufacture chemicals at low-cost and renewably,” states Salis.

“In addition, if we know how an organism functions, we can treat diseases more efficiently, not just by trying to find a particular drug that happens to work, but by designing new drugs that harvest specific mechanisms that treat very specific diseases.”

Designing DNA sequences is computationally intensive. The number of possible mutations in a short DNA sequence is greater than the number of atoms in the universe. Salis’ group uses optimization algorithms to identify a DNA sequence that achieves a specific behavior.

“Even though DNA is a universal genetic code, a bacterium will interpret its DNA in one way, but a human cell, for example, will interpret its DNA differently,” explains Salis.

“There are very specific physical and chemical interactions in the cell that determine how an organism reads its DNA and expresses its gene.

“By knowing those physical and chemical interactions and developing quantitative models to predict the strength of those interactions, we can then design new DNA sequences that are interpreted by the organisms, thus writing new code, that will then execute some desired program – so it’s a compiler.”

The DNA compiler is a collection of biophysical models that are predicting the main steps in gene expression and how they all work together to control an organism’s behavior.

About four years ago, Salis and his team created a Web interface to the Compiler, but the site drew so many users that the local campus-based server was soon overloaded. The decision was made to offload the computation to Amazon compute clusters, allowing the underlying model to run its computations on nodes that are dynamically turned on in response to user submissions.

The stack includes a Web interface, written in Python, SQLAlchemy for the database connection, and some JAVA script to make it interactive. On the backend, there’s a front-facing server which makes a RESTFUL API to another server hosted on Amazon’s AWS EC2 computing cluster and S3 distributed storage. EC2 AutoScale groups facilitates dynamic scaling.

Salis said they considered other solutions, but when they signed on two years ago, it was pretty clear that Amazon had the best solution with the best documentation. The fact that Netflix was a primary customer helped allay reliability concerns.

The professor cites ease of operation and the ability to offload management responsibilities as some of the key motivations for moving to a cloud based-solution. Of course, the scalability has been a huge boon to users who no longer have to deal with long wait times and also enjoy faster compute times.

So far, more than 6,000 registered users from MIT, Harvard, Caltech, Stanford, Rice, Imperial College, and many more institutions, have used the DNA Compiler to engineer more than 50,000 DNA sequences.

Although computational methods are used to design synthetic organisms, Salis points out that the design of an organism is very different compared to the design of a semiconductor chip.

“Designing life will be more like designing a space shuttle than designing a chip,” says Salis. “A space shuttle has a lot of moving parts and is operating under extreme conditions. If something goes wrong, it can effect other things.”

At its current pace of progress, Salis predicts that biotech will have almost complete control over energy metabolism of cells in the next five years, leading to a much better capability to manufacture a large diversity of chemicals.

“Starting right now, if you had the financial resources, you could reengineer an entire organism with the sole purpose of manufacturing a biofield,” he states. “Every single nucleotide in that organism could be optimized for the sole purpose of manufacturing a biofield with very high production rates. That is very different compared to what people have done in the past which is to make small number of mutations to an existing microbe in order to improve production.”

A paper detailing the team’s research appears in a recent issue of the journal Molecular Systems Biology.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

China’s Expanding Effort to Win in Microchips

July 27, 2017

The global battle for preeminence, or at least national independence, in semiconductor technology and manufacturing continues to heat up with Europe, China, Japan, and the U.S. all vying for sway. A fascinating article ( Read more…

By John Russell

Hyperion: Storage to Lead HPC Growth in 2016-2021

July 27, 2017

Global HPC external storage revenues will grow 7.8% over the 2016-2021 timeframe according to an updated forecast released by Hyperion Research this week. HPC server sales, by comparison, will grow a modest 5.8% to $14.8 Read more…

By John Russell

Exascale FY18 Budget – The Senate Provides Their Input

July 27, 2017

In the federal budgeting world, “regular order” is a meaningful term that is fondly remembered by members of both the Congress and the Executive Branch. Regular order is the established process whereby an Administrat Read more…

By Alex R. Larzelere

HPE Extreme Performance Solutions

HPE Servers Deliver High Performance Remote Visualization

Whether generating seismic simulations, locating new productive oil reservoirs, or constructing complex models of the earth’s subsurface, energy, oil, and gas (EO&G) is a highly data-driven industry. Read more…

India Plots Three-Phase Indigenous Supercomputing Strategy

July 26, 2017

Additional details on India's plans to stand up an indigenous supercomputer came to light earlier this week. As reported in the Indian press, the Rs 4,500-crore (~$675 million) supercomputing project, approved by the Ind Read more…

By Tiffany Trader

Exascale FY18 Budget – The Senate Provides Their Input

July 27, 2017

In the federal budgeting world, “regular order” is a meaningful term that is fondly remembered by members of both the Congress and the Executive Branch. Reg Read more…

By Alex R. Larzelere

India Plots Three-Phase Indigenous Supercomputing Strategy

July 26, 2017

Additional details on India's plans to stand up an indigenous supercomputer came to light earlier this week. As reported in the Indian press, the Rs 4,500-crore Read more…

By Tiffany Trader

Tuning InfiniBand Interconnects Using Congestion Control

July 26, 2017

InfiniBand is among the most common and well-known cluster interconnect technologies. However, the complexities of an InfiniBand (IB) network can frustrate the Read more…

By Adam Dorsey

NSF Project Sets Up First Machine Learning Cyberinfrastructure – CHASE-CI

July 25, 2017

Earlier this month, the National Science Foundation issued a $1 million grant to Larry Smarr, director of Calit2, and a group of his colleagues to create a comm Read more…

By John Russell

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

Fujitsu Continues HPC, AI Push

July 19, 2017

Summer is well under way, but the so-called summertime slowdown, linked with hot temperatures and longer vacations, does not seem to have impacted Fujitsu's out Read more…

By Tiffany Trader

Researchers Use DNA to Store and Retrieve Digital Movie

July 18, 2017

From abacus to pencil and paper to semiconductor chips, the technology of computing has always been an ever-changing target. The human brain is probably the com Read more…

By John Russell

The Exascale FY18 Budget – The Next Step

July 17, 2017

On July 12, 2017, the U.S. federal budget for its Exascale Computing Initiative (ECI) took its next step forward. On that day, the full Appropriations Committee Read more…

By Alex R. Larzelere

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Just how close real-wo Read more…

By John Russell

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its a Read more…

By Tiffany Trader

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the cam Read more…

By John Russell

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Leading Solution Providers

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is the successor to Caffe, the deep learning framework developed by Berkeley AI Research and community contributors. Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of Read more…

By Alex Woodie

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This