Events
Past Event
WED@NICO SEMINAR: Rosemary Braun, Feinberg School of Medicine "Seeing the Forest and the Trees: Multi-scale Approaches for Analyzing *Omic Data"
Northwestern Institute on Complex Systems (NICO)
12:00 PM
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Lower Level Chambers Hall
Details
Seeing the Forest and the Trees: Multi-scale Approaches for Analyzing *Omic Data
Speaker:
Rosemary Braun - Assistant Professor, Feinberg School of Medicine
Talk Abstract:
Living processes are governed by complex networks of molecular interactions involving thousands of elements: genes, proteins, enzymes, non-coding RNAs, and other signaling molecules. These systems are finely tuned to produce precise biological effects, robust enough to tolerate intrinsic and extrinsic variability, and flexible enough to adapt to environmental changes, but aberrations in these systems can lead to disease.
Advances in high-throughput "*omic" assays now make it possible to probe these systems in genome-wide detail, providing unprecedented opportunity to investigate disease mechanisms by simultaneously profiling thousands molecular markers per sample. To date, however, most analyses of *omic data consider each marker independently and treat regulatory pathways as a "sum of their parts." By neglecting the network of interactions, such approaches can miss crucial multi--gene effects associated with disease.
This talk will present some recent techniques developed in our group to incorporate pathway information into the analysis of high--dimensional *omic data. By analyzing data at the systems level, our methods enable us to integrate disparate types of *omic data, make inferences about disease mechanisms, and distinguish sets of cumulatively deleterious alterations from those that compensate one-another to preserve the overall function of a pathway. We will show how these analyses can overcome the high variability of *omics data to yield results that are more reproducible across studies, and demonstrate how these methods can be used to identify novel therapeutic and diagnostic targets.
Live Stream:
To join the Meeting: bluejeans.com/8474912527
To join via Browser: bluejeans.com/8474912527/browser
Time
Wednesday, February 8, 2017 at 12:00 PM - 1:00 PM
Location
Lower Level Chambers Hall Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
Data Science Nights - MAY 2026 - Speaker: Xudong Tang, Computer Science and NICO
Northwestern Institute on Complex Systems (NICO)
5:30 PM
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M416, Technological Institute
Details
MAY MEETING: Thursday, May 28, 2026 at 5:30pm (US Central)
LOCATION:
ESAM Conference Room, Tech M416
2145 Sheridan Road, Evanston, IL 60208
AGENDA:
5:30pm - Meet and greet with refreshments
6:00pm - Talk with Xudong Tang, PhD Student, Computer Science, NICO, and the Human-AI Collaboration Lab, Northwestern University
TALK TITLE:
Human and Machine Perception of Voice Similarity
ABSTRACT:
Modern voice cloning systems generate synthetic speech that listeners frequently cannot identify as being synthetic. But a voice can sound natural without sounding like the intended person, and what determines whether a clone is heard as a particular person is an open question. Here we report a large-scale preregistered experiment in which we collected 92,239 responses from 175 participants on their perception of pairs of real recordings, voice clones, and continuously morphed voices drawn from 100 contemporary celebrities across 20 speaker groups. We find that voice clones do not reliably preserve perceived speaker identity, reducing same-speaker judgments by 12.7 percentage points even though the clones are produced by a state-of-the-art text-to-speech model, while leaving different-speaker judgments unchanged. Using continuously morphed stimuli, we find that speakers vary substantially in how much variation their perceived identity tolerates, and that this variation is not predicted by speaker demographics. Speaker embeddings account for 58.9\% (95\% CI = [55.7, 61.9]) of variance in identity judgments, which is more than acoustic features, social attributes, and clone status combined. Once all these observed features are accounted for, clone status adds no additional predictive power. These results shows that the perceptual impact of voice cloning is positional rather than categorical: we can model how listeners judge a voice by how close it falls to the perceptual boundary that defines each speaker's recognizable voice, applying the same criterion to real and synthetic speech alike.
DATA SCIENCE NIGHTS are monthly meetings featuring presentations and discussions about data-driven science and complex systems, organized by Northwestern University graduate students and scholars. Students and researchers of all levels are welcome! For more information: http://bit.ly/nico-dsn
FUTURE DATES:
Data Science Nights will return in September!
Time
Thursday, May 28, 2026 at 5:30 PM - 7:00 PM
Location
M416, Technological Institute Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
Spring 2026 Commencement
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All Day
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Spring 2026 Commencement
Time
Sunday, June 14, 2026
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Juneteenth - University Closed
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Juneteenth - University Closed
Time
Friday, June 19, 2026
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Independence Day (observed) - University Closed
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Independence Day (observed) - University Closed
Time
Friday, July 3, 2026
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Fall 2026 Classes Begin
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Fall 2026 Classes Begin
Time
Wednesday, September 23, 2026
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