Mercury Data Science has taken a tool it originally developed for COVID-19 research and applied it into new areas of research and innovation. Photo via Getty Images

Last fall, Houston-based Mercury Data Science released an AI-driven app designed to help researchers unlock COVID-19-related information tucked into biomedical literature. The app simplified access to data about subjects like genes, proteins, drugs, and diseases.

Now, a year into the coronavirus pandemic, Mercury Data Science is applying this technology to areas like agricultural biotech, cancer therapeutics, and neuroscience. It's an innovation that arose from the pandemic but that promises broader, long-lasting benefits.

Angela Holmes, chief operating officer of Mercury Data Science, says the platform relies on an AI concept known as natural language processing (NLP) to mine scientific literature and deliver real-time results to researchers.

"We developed this NLP platform as a publicly available app to enable scientists to efficiently discover biological relationships contained in COVID research publications," Holmes says.

The platform:

  • Contains dictionaries with synonyms to identify things like genes and proteins that may go by various names in scientific literature.
  • Produces data visualizations of relationships among various biological functions.
  • Summarizes the most important data points on a given topic from an array of publications.
  • Depends on data architecture to automate how data is retrieved and processed.

In agricultural biotech, the platform enables researchers to sift through literature to dig up data about plant genetics, Holmes says. The lack of gene-naming standards in the world of plants complicates efforts to search data about plant genetics, she says.


Angela Holmes is the COO of MDS. Photo via mercuryds.com


The platform's ability to easily ferret out information about plant genetics "allows companies seeking gene-editing targets to make crops more nutritious and more sustainable as the climate changes to have a rapid way to de-risk their genomic analyses by quickly assessing what is already known versus what is unknown," Holmes says.

The platform allowed one of Mercury Data Science's agricultural biotech customers to comb through scientific literature about plant genetics to support targeted gene editing in a bid to improve crop yields.

In the field of cancer therapeutics and other areas of pharmaceuticals, the platform helps prioritize drug candidates, Holmes says. One of Mercury Data Science's customers used the platform to extract data from about 2 terabytes (or 2 trillion bytes) of information to evaluate drug candidates. The information included drug studies, clinical trials, and patents. Armed with that data, Mercury Data Science's cancer therapy client signed agreements with new pharmaceutical partners.

The platform also applies to the hunt for biomarkers in neuroscience, including disorders such as depression, anxiety, autism and multiple sclerosis. Data delivered through the platform helps bring new neurobehavioral therapeutics to market, Holmes says.

"An NLP platform to automatically process newly published literature for more insight on the search for digital biomarkers represents a great opportunity to accelerate research in this area," she says.

Mercury Data Science has experience in the field of digital biomarkers, including work for one customer to develop a voice and video platform to improve insights into patients with depression and anxiety in order to improve treatment of those conditions.

The new platform — initially developed as a tool to combat COVID-19 — falls under the startup's vast umbrella of artificial intelligence and data science. Founded in 2017, Mercury Data Science emerged because portfolio companies of the Houston-based Mercury Fund were seeking to get a better handle on AI and data science.

Last April, Angela Wilkins, founder, co-CEO and chief technology officer of Mercury Data Science, left the company to lead Rice University's Ken Kennedy Institute. Dan Watkins, co-founder and managing director of the Mercury Fund, remains at Mercury Data Science as CEO.

The Ken Kennedy Institute fosters collaborations in computing and data. Wilkins replaced Jan Odegard as executive director of the institute. Odegard now is senior director of industry and academic partnerships at The Ion, the Rice-led innovation hub.

Wilkins "is an academic at heart with considerable experience working with faculty and students, and an entrepreneur who has helped build a successful technology company," Lydia Kavraki, director of the Ken Kennedy Institute, said in a news release announcing Wilkins' new role. "Over her career, Angela has worked on data and computing problems in a number of disciplines, including engineering, life sciences, health care, agriculture, policy, technology, and energy."

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Houston researcher builds radar to make self-driving cars safer

eyes on the road

A Rice University researcher is giving autonomous vehicles an “extra set of eyes.”

Current autonomous vehicles (AVs) can have an incomplete view of their surroundings, and challenges like pedestrian movement, low-light conditions and adverse weather only compound these visibility limitations.

Kun Woo Cho, a postdoctoral researcher in the lab of Rice professor of electrical and computer engineering Ashutosh Sabharwal, has developed EyeDAR to help address such issues and enhance the vehicles’ sensing accuracy. Her research was supported in part by the National Science Foundation.

The EyeDAR is an orange-sized, low-power, millimeter-wave radar that could be placed at streetlights and intersections. Its design was inspired by that of the human eye. Researchers envision that the low-cost sensors could help ensure that AVs always pick up on emergent obstacles, even when the vehicles are not within proper range for their onboard sensors and when visibility is limited.

“Current automotive sensor systems like cameras and lidar struggle with poor visibility such as you would encounter due to rain or fog or in low-lighting conditions,” Cho said in a news release. “Radar, on the other hand, operates reliably in all weather and lighting conditions and can even see through obstacles.”

Signals from a typical radar system scatter when they encounter an obstacle. Some of the signal is reflected back to the source, but most of it is often lost. In the case of AVs, this means that "pedestrians emerging from behind large vehicles, cars creeping forward at intersections or cyclists approaching at odd angles can easily go unnoticed," according to Rice.

EyeDAR, however, works to capture lost radar reflections, determine their direction and report them back to the AV in a sequence of 0s and 1s.

“Like blinking Morse code,” Cho added. “EyeDAR is a talking sensor⎯it is a first instance of integrating radar sensing and communication functionality in a single design.”

After testing, EyeDAR was able to resolve target directions 200 times faster than conventional radar designs.

While EyeDAR currently targets risks associated with AVs, particularly in high-traffic urban areas, researchers also believe the technology behind it could complement artificial intelligence efforts and be integrated into robots, drones and wearable platforms.

“EyeDAR is an example of what I like to call ‘analog computing,’” Cho added in the release. “Over the past two decades, people have been focusing on the digital and software side of computation, and the analog, hardware side has been lagging behind. I want to explore this overlooked analog design space.”

12 winners named at CERAWeek clean tech pitch competition in Houston

top teams

Twelve teams from around the country, including several from Houston, took home top honors at this year's Energy Venture Day and Pitch Competition at CERAWeek.

The fast-paced event, held March 25, put on by Rice Alliance, Houston Energy Transition Initiative and TEX-E, invited 36 industry startups and five Texas-based student teams focused on driving efficiency and advancements in the energy transition to present 3.5-minute pitches before investors and industry partners during CERAWeek's Agora program.

The competition is a qualifying event for the Startup World Cup, where teams compete for a $1 million investment prize.

PolyJoule won in the Track C competition and was named the overall winner of the pitch event. The Boston-based company will go on to compete in the Startup World Cup held this fall in San Francisco.

PolyJoule was spun out of MIT and is developing conductive polymer battery technology for energy storage.

Rice University's Resonant Thermal Systems won the second-place prize and $15,000 in the student track, known as TEX-E. The team's STREED solution converts high-salinity water into fresh water while recovering valuable minerals.

Teams from the University of Texas won first and second place in the TEX-E competition, bringing home $25,000 and $10,000, respectively. The student winners were:

Companies that pitched in the three industry tracts competed for non-monetary awards. Here are the companies named "most-promising" by the judges:

Track A | Industrial Efficiency & Decarbonization

Track B | Advanced Manufacturing, Materials, & Other Advanced Technologies

  • First: Licube, based in Houston
  • Second: ZettaJoule, based in Houston and Maryland
  • Third: Oleo

Track C | Innovations for Traditional Energy, Electricity, & the Grid

The teams at this year's Energy Venture Day have collectively raised $707 million in funding, according to Rice. They represent six countries and 12 states. See the full list of companies and investor groups that participated here.

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This article originally appeared on our sister site, EnergyCapitalHTX.com.