A neuronal network based on artificial intelligence (AI), unique in its kind, can quickly analyze and interpret millions of cells of a patient sample, predicting molecular changes in the tissue. This could identify facilitate the design of personalized treatments for diseases such as cancer.
The Nichecompass, which occurs in the magazine ‘Nature Genetics‘Use a visual database that combines space genomic data on cell types, where they are and how they communicate.
Created by researchers from the Wellcome Sanger Institutethe iHelmholtz Munich’s health nstitutothe University of Würzburg and its collaborators as part of the Human cellular atlas initiativeit is the first system of AI capable of measuring and interpreting a range of data from the social network of a cell to recognize and analyze different cellular neighborhoods.
In the study published by ‘Nature Genetics’ it is detailed how can discover changes in the fabrics of Patients with breast and lung cancer. Nichacompss, says its authors, can identify how certain people can respond differently to treatments, all in an hour, through the power of AI.
Social Network
Each cell in the human body communicates with its surroundings and is part of a network of interactions, identifying by characteristics such as proteins on its surface. Space and single -cell genomic technologies have improved the understanding of the body, allowing the creation of detailed cellular atlas of tissues and organs. These ATLAS contain information about cell types, their location and how genetic changes affect their interactions. Although they provide data on cell networks, it is difficult to interpret and quantify these social interactions.
Nichacompass is a deep -learning AI model based on cell to cell to cell. This means that he learns how the different cells communicate through their networks and then align them with similar cells of cells, creating neighbors inside the tissues through shared characteristics.
From this, Nichacompss You can interpret the data, which allows researchers and clinicians to ask data about data and better understand health conditions. For example: “How do cancer cells communicate with the surrounding environment in patients with lung cancer?”
Using Nichacompss, the researchers combined data from 10 patients with lung cancer and could see the similarities and differences between individuals. The similarities help to inform our general understanding of cancer, as well as to highlight transcriptional changes that could be useful to point to new treatments. In comparison, the differences highlight new possible ways for personalized medicine.
The team also used Nichacompss in breast cancer fabrics, demonstrating its effectiveness in different types of cancer.
They also applied this network to a Mouse cerebral space atlas with 8.4 million cellsand was able to quickly and precisely identify sections of the brain and create a visual resource of the entire organ. This demonstrates how it can be applied to the space atlas of complete organs generated by researchers around the world.
Carlos Talavera-Lópezmain co -author at the University of Würzburg, highlights that, using Nichacompss, they observed how immune cells interact differently with tumors in patients with lung cancer. “This advance allowed to identify a patient whose cancer responded differently from the immune system, which could help develop personalized treatments in the future.”
For its part, Mohammad Lotfollahiof the Wellcome Sanger Institute, explains that, like people share information on their social networks, cells communicate through their characteristics, forming local networks. «Nichacompss is the First model of AI capable of interpreting these networkswhich could directly impact the life of patients, by identifying the origin of health problems and predicting how they could respond to treatments ».
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