Erratum: Loss of epigenetic information as a cause of mammalian aging (Cell (2023) 186 (2)(305–326. e27),(S0092867422015707),(10.1016/j. cell. 2022.12. 027))

Regression convolutional neural network models implicate peripheral immune regulatory variants in the predisposition to Alzheimer’s disease

AI-designed DNA sequences regulate cell-type-specific gene expression

RERconverge expansion: using relative evolutionary rates to study complex categorical trait evolution

Spatial, transcriptomic, and epigenomic analyses link dorsal horn neurons to chronic pain genetic predisposition

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Over the last several decades, the genetic revolution has showed us that much of human biology, even complex behavior, is encoded in our genome. Most of the variation in genome sequence that influences neurological disease predisposition and behavioral ability occurs in the vast regulatory regions between genes. The goal of the Pfenning laboratory is to build a set of computational and experimental genomic tools to study how sequence differences in those regions influence neurons, neural circuits, disease predisposition, and behavior. By understanding the genetic mechanisms underlying neural function, we seek to uncover the cell type-specific basis of Alzheimer’s disease and addiction, as well as gain insights into how speech production ability evolved in the human lineage.

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 Pfenning Lab

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Similar genetic elements underlie vocal learning in mammals

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Associate Professor, Ray and Stephanie Lane Computational Biology Department

What if AI could help design gene therapies so precise they eliminate chronic pain while leaving other senses completely intact? And what if the secret to treating Parkinson's Disease lies hidden in the genome of a mouse?

In this episode, we explore groundbreaking advances in genetic medicine with Andreas Pfenning, Associate Professor in Carnegie Mellon University's Computational Biology Department and School of Computer Science. Professor Pfenning discusses research in his experimental lab, and how AI is revolutionizing gene therapy by making treatments more targeted while reducing toxic side effects.

The conversation covers Pfenning's work developing precision gene therapies for chronic pain originating in the spine, where AI helps identify exactly which spinal cord cells transmit pain signals while preserving normal touch and movement functions. The episode also explores KGWAS (Knowledge Graph Genome-Wide Association Study), an AI-powered tool developed at CMU in partnership with other research institutions, that helps identify genetic problems that can cause rare diseases or disorders.

Pfenning shares insights from his collaboration on the ambitious Vertebrate Genomes Project, which aims to map genomes from more than 500 vertebrate species. This massive international effort is revealing surprising genetic similarities across species that could unlock new treatments for human diseases including Parkinson's, Alzheimer's, and other neurological disorders.

The discussion also highlights how machine learning is accelerating the path from laboratory discovery to clinical applications, with promising results already emerging in Parkinson's disease treatment trials.

Learn more about CMU Expert Andreas Pfenning's work that matters: https://www.cmu.edu/news/experts/andreas.pfenning

Unlocking the Future of Gene Therapy

Robots and artificial intelligence are transforming the healthcare industry, from drug development to surgical procedures to personalized healthcare plans. 








In this, the first of a two-part episode, we'll take a big picture look at these transformational technologies and meet a leader in the emerging field of soft robotics, the creation of robots and wearable devices that look, feel, and move more like humans.  And we'll meet a co -founder of a fast-growing healthcare technology company and find out why their AI-powered technology is making life better for doctors and patients one doctor-patient visit at a time. We will also discuss how the use of robots and AI in healthcare raises regulatory and ethical considerations. 



In part two, coming up in two weeks, we'll do a deep-dive on companion robots, and how they are helping the elderly overcome their loneliness, manage illnesses such as Alzheimers and dementia, and improve their health and well-being. 








Joining us in part one are three experts in robotics and health care: Dr Christopher Müller, Director of the Statistical Department for the International Federation of Robotics; Carmel Majidi, Professor of Mechanical Engineering at Carnegie Mellon University; and Zach Lipton, the Raj Reddy Associate Professor of Machine Learning at Carnegie Mellon University and Chief Technology Officer and Chief Scientist of ABridge.

AI Care Part 1: Robots and AI Transforming Healthcare

What if a robot could be a compassionate companion - an antidote to loneliness as we age – and in some cases – help those suffering from dementia?








Loneliness among the elderly has become something of an epidemic.  According to a recent national survey, about 37 % of American adults aged 50 to 80 experienced loneliness, and about 34% of respondents said they felt socially isolated. Companion robots have the potential to alleviate loneliness and improve the well-being of these older adults as well as help those suffering from memory loss from dementia or Alzheimer’s. They can converse about daily activities, connect to new friends around the country, lead workout sessions, suggest and place calls to loved ones, provide gentle reminders for taking medicines, play music, suggest what's for dinner, and even host live bingo games. 








In this episode, which is Part 2 of a two-part episode on robots and health care, we discuss the challenges and opportunities for developing companion robots to help the elderly with loneliness.  We also meet ElliQ, an AI-powered companion robot that is already being used in thousands of older adults' homes. The future of companion robots may involve using softbotic technologies to create anthropomorphic features and lifelike physical interaction.








Joining us in part two are four experts in robotics and the elderly: Carmel Majidi, Professor of Mechanical Engineering at Carnegie Mellon University; Selma Šabanović, Professor of Informatics and Cognitive Science and Director of R-House Lab at Indiana University Bloomington; David Crandall, Professor of Computer Sciences and Director of the Luddy Artificial Intelligence Center at Indiana University Bloomington; and Assaf Gad, VP Strategy and GM for Intuition Robotics. 

AI Care Part 2: Companion Robots Help the Elderly Feel Less Lonely

What if paleontologists could create robot replicas of dinosaurs to better understand them – and how they moved – and in turn learn more about us?








In this episode, we’re talking about the intersection of paleontology, robotics, and artificial intelligence. That includes paleobionics… an emerging field at Carnegie Mellon University – that uses robotics and soft robotics to help scientists better understand how dinosaurs and other extinct organisms might have moved.  Not only could this lead to new discoveries about dinosaur behavior and evolution, it also could provide new understandings on how we, as humans, move while helping engineers design more agile robots that move better through our world.  We’ll meet some of the scientists building these new robots based on fossil records of extinct organisms such as the pleurocystid, an ancient ancestor of the starfish and sea urchin, and the gorgonopsid, a strange dinosaur that’s part mammal, part reptile. 








And could paleobionic scientists someday build a working, life size Tyrannosaurus Rex?  Let’s find out.  








Joining us are: Dr. Aja Mia Carter, postdoctoral researcher working with Carnegie Mellon University’s Robomechanics Lab; Carmel Majidi, Professor of Mechanical Engineering at CMU; and Aaron Johnson, Associate Professor of mechanical engineering and robotics at CMU and faculty for the University's Robomechanics Lab. 

Paleobionics: Dinosaurs Are Back

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