Featured Research

from universities, journals, and other organizations

Computer can infer rules of the forest

Date:
July 25, 2013
Source:
Cornell University
Summary:
Researchers have devised a computer algorithm that takes intermittent samples -- for example, the number of prey and predating species in a forest once a year, or the concentration of different species in a chemical bath once an hour -- and infer the likely reactions that led to that result. They're working backward from traditional stochastic modeling, which they say could help unravel the hidden laws in fields as diverse as molecular biology to population ecology to basic chemistry.

A forest full of rabbits and foxes, a bubbling vat of chemical reactants, and complex biochemical circuitry within a cell are, to a computer, similar systems: Many scenarios can play out depending on a fixed set of rules and individual interactions that can't be precisely predicted -- chemicals combining, genes triggering cascades of chemical pathways, or rabbits multiplying or getting eaten.

Predicting possible outcomes from a set of rules that contain uncertain factors is often done using what's called stochastic prediction. What has eluded scientists for decades is doing the reverse: To find out what the rules were, simply by observing the outcomes.

Researchers led by Hod Lipson, associate professor of mechanical and aerospace engineering and of computing and information science at Cornell University, have published new insight into automated stochastic inference that could help unravel the hidden laws in fields as diverse as molecular biology to population ecology to basic chemistry.

Their study, published online July 22 in Proceedings of the National Academy of Sciences, describes a new computer algorithm that allows machines to infer stochastic reaction models without human intervention, and without any previous knowledge on the nature of the system being modeled.

With their algorithm, Lipson and colleagues have devised a way to take intermittent samples -- for example, the number of prey and predating species in a forest once a year, or the concentration of different species in a chemical bath once an hour -- and infer the likely reactions that led to that result. They're working backward from traditional stochastic modeling, which typically uses known reactions to simulate possible outcomes. Here, they're taking outcomes and coming up with reactions, which is much trickier, they say.

"This could be very useful if you wanted to learn the driving rules for not just foxes and rabbits, but any evolving system with interacting agents," Lipson said. "There is a whole lot of science that is based on this kind of modeling."

The researchers, including first author Ishanu Chattopadhyay, a Cornell postdoctoral associate, teamed with Anna Kuchina and Gurol Suel, molecular biologists at University of California, San Diego, to test their algorithms using real data. In one experiment, they applied the algorithm to a set of gene expression measurements of a model bacterium B. subtilis.

They gleaned similar insights by studying the fluctuating numbers of micro-organisms in a closed ecosystem; the algorithm came up with reactions that correctly identified the predators, the prey and the dynamical rules that defined their interactions.

Their key insight was to look at relative changes of the concentration of the interacting agents, irrespective of the time at which such changes were observed. This collective set of relative population updates has some important mathematical properties, which could be related back to the hidden reactions driving the system.

"We figured out that there's what's called an invariant geometry, a geometrical feature of the data set that you can uncover even from sparse intermittent samples, without knowing any of the underlying rules," Chattopadhyay said. "The geometry is a function of the rules, and once you find that out, there is a way to find out what the reactions are."

The bigger picture in this study is to give scientists better tools for taking massive amounts of data and coming up with simple, insightful explanations, Lipson said.

"This is a tool in a suite of emerging 'automated science' tools researchers can use if they have data from some experiment, and they want the computer to help them understand what's going on -- but in the end, it's the scientist who has to give meaning to these models," Lipson said.


Story Source:

The above story is based on materials provided by Cornell University. Note: Materials may be edited for content and length.


Journal Reference:

  1. I. Chattopadhyay, A. Kuchina, G. M. Suel, H. Lipson. Inverse Gillespie for inferring stochastic reaction mechanisms from intermittent samples. Proceedings of the National Academy of Sciences, 2013; DOI: 10.1073/pnas.1214559110

Cite This Page:

Cornell University. "Computer can infer rules of the forest." ScienceDaily. ScienceDaily, 25 July 2013. <www.sciencedaily.com/releases/2013/07/130725125418.htm>.
Cornell University. (2013, July 25). Computer can infer rules of the forest. ScienceDaily. Retrieved September 30, 2014 from www.sciencedaily.com/releases/2013/07/130725125418.htm
Cornell University. "Computer can infer rules of the forest." ScienceDaily. www.sciencedaily.com/releases/2013/07/130725125418.htm (accessed September 30, 2014).

Share This



More Computers & Math News

Tuesday, September 30, 2014

Featured Research

from universities, journals, and other organizations


Featured Videos

from AP, Reuters, AFP, and other news services

Apple Releases 'Shellshock' Fix Despite Few Affected Users

Apple Releases 'Shellshock' Fix Despite Few Affected Users

Newsy (Sep. 29, 2014) Apple released a security fix for the "Shellshock" vulnerability Monday, though it says only "advanced UNIX users" of OS X need it. Video provided by Newsy
Powered by NewsLook.com
Do Video Games Trump Brain Training For Cognitive Boosts?

Do Video Games Trump Brain Training For Cognitive Boosts?

Newsy (Sep. 29, 2014) More and more studies are showing positive benefits to playing video games, but the jury is still out on brain training programs. Video provided by Newsy
Powered by NewsLook.com
New Facebook Ad Platform Goes Where You Go On The Web

New Facebook Ad Platform Goes Where You Go On The Web

Newsy (Sep. 29, 2014) Called Atlas, the platform allows advertisers to place ads based on Facebook info on sites outside of Facebook. Video provided by Newsy
Powered by NewsLook.com
Google Tightens Requirements For Android Manufacturers

Google Tightens Requirements For Android Manufacturers

Newsy (Sep. 27, 2014) Phonemakers who want to use Google’s software in their devices will have to stick to more stringent requirements. Video provided by Newsy
Powered by NewsLook.com

Search ScienceDaily

Number of stories in archives: 140,361

Find with keyword(s):
Enter a keyword or phrase to search ScienceDaily for related topics and research stories.

Save/Print:
Share:

Breaking News:

Strange & Offbeat Stories


Space & Time

Matter & Energy

Computers & Math

In Other News

... from NewsDaily.com

Science News

Health News

Environment News

Technology News



Save/Print:
Share:

Free Subscriptions


Get the latest science news with ScienceDaily's free email newsletters, updated daily and weekly. Or view hourly updated newsfeeds in your RSS reader:

Get Social & Mobile


Keep up to date with the latest news from ScienceDaily via social networks and mobile apps:

Have Feedback?


Tell us what you think of ScienceDaily -- we welcome both positive and negative comments. Have any problems using the site? Questions?
Mobile: iPhone Android Web
Follow: Facebook Twitter Google+
Subscribe: RSS Feeds Email Newsletters
Latest Headlines Health & Medicine Mind & Brain Space & Time Matter & Energy Computers & Math Plants & Animals Earth & Climate Fossils & Ruins