Title: Diversity in animal response to environmental change
Seminar information:
Data Science Coast to Coast Seminar Series
Hosted by the Academic Data Science Alliance
May 19, 2021
3pm
https://academicdatascience.org/resources/coast2coastseminar
The DS C2C seminar series, hosted jointly by seven academic data science institutes, provides a unique opportunity to foster a broad-reaching data science community
In the first half of 2021, we will host five seminars, each featuring one faculty member and one postdoctoral fellow from two universities. Each speaker will give a 20-minute talk about ongoing projects and motivating issues, followed by 20 minutes of discussion with the audience. These seminars will be the launching point for follow-on research discussion meetings which will hopefully lead to fruitful collaborative research
Session information: Biodiversity
Virtual presentation:
Slide deck:
- PDF version: STRIGG_C2C2021.pdf
- Powerpoint version: STRIGG_C2C2021.pptx
Abstract: How will ecosystems tolerate the climate and ocean change occurring now and predicted for the future? To begin addressing this question, we can subject different animals to different anthropogenic pressures and evaluate their responses. We can more sensitively and comprehensively assess responses by performing molecular surveys using omics technologies (e.g. genomics, proteomics, metabolomics, etc.), which allow us to more clearly see the cellular processes that underlie environmental tolerance and intolerance. This data can also help us compare between species since all species have these general molecules (DNA, proteins, metabolites) in common. I'm going to present data from different studies on marine invertebrates exposed to different environmental conditions, and describe how I used multiple data science approaches to distill large omics datasets into dominant biological pathways associated with environmental tolerance and intolerance. After summarizing responses across species and conditions, I will propose future directions and data science applications for the wealth of environmental omics data being generated.