Imageomics Set to Revolutionize Understanding of Life

Imagingomics

Imageomics is an emerging scientific field that combines machine learning with biology to extract biological information from images of various life forms. Its goal is to understand the relationship between an organism’s phenotype (observable traits) and its genotype (genetic makeup).

Main summary

Imageomics, a new field of science, has made astonishing progress in the past year and is on the verge of making important discoveries about life on Earth, according to one of the discipline’s founders.

Imageomics: images as a source of information about life

Tanya Berger-Wolf, faculty director of the Institute for Translational Data Analysis at The Ohio State University, described the state of imageomics in a presentation Feb. 17, 2024, at the annual meeting of the American Association to Advance of the science.

“Imagomics is coming of age and is ready for its first major discoveries,” Berger-Wolf said in an interview before the meeting.

Imageomics is a new interdisciplinary scientific field focused on the use of machine learning tools to understand the biology of organisms, particularly biological traits, from images.

Those images can come from camera traps, satellites, drones and even the vacation photos tourists take of animals like zebras and whales, said Berger-Wolf, director of the Imageomics Institute at Ohio State, funded by the National Science Foundation. .

These images contain a large amount of information that scientists could not properly analyze and use before the development of artificial intelligence and machine learning.

The field is new (the Imageomics Institute was just founded in 2021), but big things are happening, Berger-Wolf told AAAS.

One important area of ​​study that is coming to fruition involves how phenotypes (the observable traits of animals that can be seen in images) relate to their genome, the DNA sequence that produces these traits.

“We are on the verge of understanding the direct connections between observable phenotype and genotype,” he said.

“We couldn’t do this without imageomics. It’s driving both artificial intelligence and biological science.”

Berger-Wolf cited new research on butterflies as an example of the advances imageomics is making. She and her colleagues are studying imitations: species of butterflies whose appearance is similar to that of a different species. One reason for mimicry is to resemble a species that predators, such as birds, avoid because its taste is unattractive.

In these cases, birds, like humans, cannot distinguish the species just by looking at them, although the butterflies themselves know the difference. However, machine learning can analyze images and learn the very subtle differences in color or other traits that differentiate types of butterflies.

“We can’t tell them apart because these butterflies didn’t evolve these traits for our benefit. They evolved to send signals to their own species and their predators,” he said.

“The signal is there, we just can’t see it. Machine learning can allow us to learn what those differences are.”

But more than that, we can use the imageomics approach to change the images of the butterflies and see how extensive the differences between the imitations must be to fool the birds. The researchers plan to print realistic images of the butterflies with subtle differences to see which ones real birds respond to.

It’s about doing something new with AI that hasn’t been done before.

“We’re not using AI to simply recapitulate what we know. We’re using AI to generate new scientific hypotheses that are actually testable. It’s exciting,” Berger-Wolf said.

Researchers are going even further with the imageomics approach to connect these subtle differences in the butterflies’ appearance to the actual genes that lead to those differences.

“There are many things we will learn in the coming years that will push imagingomics into new areas that we can only imagine now,” he said.

A key goal is to use this new knowledge generated by imageomics to find ways to protect threatened species and the habitats where they live.

“Imagomics will bring a lot of good things in the coming years,” Berger-Wolf said.

Presentations

Berger-Wolf’s AAAS presentation, titled “Imageomics: images as a source of information about life” It’s part of the session “Imageomics: Powering machine learning to understand biological traits.”

Imageomics: images as a source of information about life

Images are the most abundant source to document life. However, the traits of organisms, critical for understanding fundamental biology and evolution, cannot be easily extracted from them. Knowledge-guided machine learning and computer vision can turn massive collections of images into a database of high-resolution information about living organisms, enabling scientific discovery, conservation, and policy decisions.

Imageomics: Powering machine learning to understand biological traits

Analysis of integrated gene-environment products (traits) is critical to predicting the effects of environmental change or genetic manipulation and understanding the process of evolution. Biologists have characterized traits from observations and measurements of organisms. Today, images are the most abundant and readily available source of information about the world to document biodiversity and extract traits of organisms.

Imageomics is an approach that removes a key obstacle to advancing the understanding of how genes and environment affect the phenotypes of organisms while addressing key challenges in artificial intelligence (AI): explainability, inductive bias , novelty and recognition of the open world, by allowing computable features of images. Deep structured knowledge of species traits and evolution, in the form of ontologies, phylogenies, and other knowledge bases, uses massive stores of biological images to inform machine learning (ML) to generate biologically meaningful explanations.

Attribution/Source(s):

This peer-reviewed publication from our Imageomics section was selected for distribution by the editors of Disabled World because of its likely interest to our readers in the disability community. Although content may have been edited for style, clarity, or length, the article “Imagomics will revolutionize the understanding of life” was originally written by The Ohio State University and submitted for publication on 02/17/2024 (Editing update: 02/18/2024). If you require further information or clarification, you may contact The Ohio State University at osu.edu. Disabled World makes no warranties or representations in connection therewith.

📢 Discover related topics

👍 Share this information with:
𝕏.com Facebook Reddit

Page information, citations and disclaimer

Disabled World is an independent disability community founded in 2004 to provide disability news and information to disabled people, older people, their families and/or carers. Visit our homepage for informative reviews, exclusive stories, and how-tos. You can connect with us on social media like X.com and ours Facebook page.

Permanent link: Imageomics set to revolutionize understanding of life

Cite this page (APA): Ohio State University. (2024, February 17). Imageomics is set to revolutionize the understanding of life. Disabled world. Retrieved February 19, 2024 from www.disabled-world.com/assistivedevices/ai/imageomics/imageomics.php

Disabled World provides general information only. The materials presented are never intended to be a substitute for qualified professional medical care. Any third party offers or advertisements do not constitute an endorsement.