Systems Science Friday Noon Seminar Series
Loading...
Date
2-15-2018
Abstract
Data Science is a relatively new interdisciplinary field, taking concepts from statistics and machine learning to produce predictive models. However, Systems Science concepts (such as feature-feature interactions and dynamics) have been largely underutilized in Data Science. In this talk, I'd like to start a discussion of specific ways that Systems Science can inform Data Science. I will start with examples of network analysis in my research that have led to better predictive models, and end with a discussion about the interpretability of black box predictors such as neural networks. I believe that Systems Science approaches can enhance Data Science by providing a deeper understanding of interactions between features and interpretability.
Biographical Information
I am an Assistant Professor in the Division of Bioinformatics and Computational Biology in the Department of Medical Informatics and Clinical Epidemiology at OHSU (BCB/DMICE). My research focus is on the Systems Biology of Complex Diseases, especially within cancer. I use integrative modeling approaches (such as network analysis and graphical models) across OMICs types to achieve this. I am also an active participant in the Portland Data Science community, especially the R programming community. More information at http://laderast.github.io/
Subjects
Big data, System theory, System analysis, Neural networks, Machine learning
Disciplines
Computer Sciences | Data Science | Medicine and Health Sciences
Persistent Identifier
https://archives.pdx.edu/ds/psu/33261
Rights
© Copyright the author(s)
IN COPYRIGHT:
http://rightsstatements.org/vocab/InC/1.0/
This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
DISCLAIMER:
The purpose of this statement is to help the public understand how this Item may be used. When there is a (non-standard) License or contract that governs re-use of the associated Item, this statement only summarizes the effects of some of its terms. It is not a License, and should not be used to license your Work. To license your own Work, use a License offered at https://creativecommons.org/
Recommended Citation
Laderas, Ted, "How are Data Science and Systems Science Connected?" (2018). Systems Science Friday Noon Seminar Series. 81.
https://archives.pdx.edu/ds/psu/33261