Experts urged to ratify Minamata Convention to phase out mercury-added products পারদযুক্ত পণ্যের ব্যবহার বন্ধে মিনামাতা কনভেনশন অনুমোদনের আহ্বান সেন্টমার্টিন সৈকতে প্লাস্টিকের আগ্রাসন 72 birds die eating pesticide-treated masakalai Educate girls to save the planet শিশুর সর্দি-কাশি সারানোর ঘরোয়া উপায় 50 Books All Kids Should Read Before They’re 12 24 thousand under 5 children die of pneumonia in Bangladesh annually গ্রিনহাউস গ্যাস কমানোর লক্ষ্যে নানা উদ্যোগ Maldives: Eco-friendly product export destination for Bangladesh

Biophysicists use machine learning to understand, predict dynamics of worm behavior


Biophysicists have used an automated method to model a living system — the dynamics of a worm perceiving and escaping pain. The Proceedings of the National Academy of Sciences (PNAS)published the results, which worked with data from experiments on the C. elegans roundworm.

"Our method is one of the first to use machine-learning tools on experimental data to derive simple, interpretable equations of motion for a living system," says Ilya Nemenman, senior author of the paper and a professor of physics and biology at Emory University. "We now have proof of principle that it can be done. The next step is to see if we can apply our method to a more complicated system."

The model makes accurate predictions about the dynamics of the worm behavior, and these predictions are biologically interpretable and have been experimentally verified.

Collaborators on the paper include first author Bryan Daniels, a theorist from Arizona State University, and co-author William Ryu, an experimentalist from the University of Toronto.

The researchers used an algorithm, developed in 2015 by Daniels and Nemenman, that teaches a computer how to efficiently search for the laws that underlie natural dynamical systems, including complex biological ones. They dubbed the algorithm "Sir Isaac," after one of the most famous scientists of all time — Sir Isaac Newton. Their long-term goal is to develop the algorithm into a "robot scientist," to automate and speed up the scientific method of forming quantitative hypotheses, then testing them by looking at data and experiments.

For More: https://www.sciencedaily.com/releases/2019/03/190327123848.htm

Posted by on Apr 4 2019. Filed under Health. You can follow any responses to this entry through the RSS 2.0. You can leave a response or trackback to this entry

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