Description:

Description:

NICO is hosting a lightning talk seminar each term as a part of our Wednesdays@NICO seminar series. Northwestern graduate students and postdoctoral fellows are invited to participate. To sign up for future lightning talks, please visit: https://bit.ly/2lRqSXK

Webinar:

Webinar link: https://northwestern.zoom.us/j/96018513447
Passcode: nico
ID: 960 1851 3447

Speakers:

Jaehyuk Park
Postdoctoral Fellow
Kellogg School of Managmeent, and
Northwestern Institute on Complex Systems

Emma Zajdela
PhD Candidate
Department of Engineering Sciences and Applied Mathematics
McCormick School of Engineering

Gary Nave
Postdoctoral Fellow
Department of Engineering Sciences and Applied Mathematics
McCormick School of Engineering

Sarah Ben Maamar
Postdoctoral Fellow
Department of Chemical and Biological Engineering
McCormick School of Engineering

Talk Titles and Abstracts:

Jaehyuk Park "People, Places, and Ties: Landscape of social places and their social network structures"

Due to their essential role as places for socialization, “third places”—social places where people casually visit and communicate with friends and neighbors—have been studied by a wide range of fields including network science, sociology, geography, urban planning, and regional studies. However, the lack of a large-scale census on third places kept researchers from systematic investigations. Here we provide a systematic nationwide investigation of third places and their social networks, by using Facebook pages. Our analysis reveals a large degree of geographic heterogeneity in the distribution of the types of third places, which is highly correlated with baseline demographics and county characteristics. Certain types of pages like “Places of Worship” demonstrate a large degree of clustering suggesting community preference or potential complementarities to concentration. We also found that the social networks of different types of social place differ in important ways: The social networks of ‘Restaurants’ and ‘Indoor Recreation’ pages are more likely to be tight-knit communities of pre-existing friendships whereas ‘Places of Worship’ and ‘Community Amenities’ page categories are more likely to bridge new friendship ties. We believe that this study can serve as an important milestone for future studies on the systematic comparative study of social spaces and their social relationships. This is joint work with Bogdan State (scie.nz), Monica Bhole (Facebook), Michael Bailey (Facebook), and Yong-Yeol Ahn (Indiana Univ.).

Emma Zajdela "Catalyzing Collaborations: A Model for the Dynamics of Team Formation at Conferences"

The COVID-19 pandemic has brought to the fore the importance of collaboration among scientists to address challenges of global significance. One of the main ways that new and innovative collaborations are catalyzed is by gathering scientists together at conferences.  In the U.S. alone, conferences amount to billions of dollars per year in terms of travel expenses, organizing costs, and loss of research time. In this lightning talk, I present a dynamical model for predicting the formation of scientific collaborations at conferences, inspired by the chemical process of catalysis. Specifically, the model tracks the probability that two participants at a conference will form a collaboration given their previous knowledge of each other and level of interaction throughout the conference. Model predictions are tested using data from two multi-year series of interactive conferences known as the Scialog Conferences, organized by the Research Corporation for Science Advancement over the period 2015-2020. We find that scientists who interact more intensely throughout the conference have a higher likelihood of forming a collaboration. Furthermore, we find that the likelihood of collaborating remains at a higher level even after the interaction between participants has ceased. Our findings may have an impact on stakeholders from public, private, and nonprofit sectors who wish to optimize future conferences to promote new collaborations.  

Gary Nave "Approximating attracting and repelling flow features with the trajectory divergence rate"

Within the flow of a fluid or a dynamical system, there are often attracting or repelling manifolds that provide an organizing “skeleton” to the flow. These structures have been shown to be barriers to transport of material moving within a flow. In this talk, I will introduce the trajectory divergence rate, which can serve to rapidly approximate attracting and repelling structures using only the vector field. By looking at the instantaneous growth rate of normal vectors, we measure the rate at which adjacent trajectories are coming together or moving apart. This diagnostic can be applied to, for example, slow manifolds, ocean flows, and limit cycle oscillations, and provides an intuitive understanding of the geometric organization of a flow. 

Sarah Ben Maamar "Comprehensive analysis of the reproducibility of RNAseq computational pipelines"

Sarah Ben Maamar, Reese Richardson, Sophia Liu, Luis Nunes A. Amaral.

Next generation sequencing technologies revolutionized biomedical research and became unavoidable due to their low costs, high amount of data generated and the wide variety of their applications. In particular, RNA-sequencing (RNA-seq) has become widely used in biological and biomedical fields as this technique allows the evaluation of gene expression levels in model organisms under different contexts. These contexts include the comparison of sick versus healthy cells; the effect of specific drugs on cells gene expression; monitoring of changes in gene expression over time; or the discovery of the potential role of an unknown gene when comparing different tissues. 

As the output of RNA-seq is complex and large, processing and analysis of such data requires the use of complex computational pipelines involving multiple steps and softwares to make the data comprehensible. RNA-seq computational pipelines vary according to the application and can have up to six steps, for which up to ten different softwares are available for each task. Each software also offers multiple parameters to better tune the analysis for each application and dataset. 

Despite the endless choices, there is currently no standardized pipeline agreed upon in the broad biomedical field. Thus, unless a computational pipeline used to process a dataset is thoroughly documented, it is almost impossible to reproduce the results obtained from a dataset after processing. 

In this work, we analyze the documentation and replicability associated to each step of RNA-seq computational pipelines used to study differential gene expression in the model bacteria Escherichia coli. We particularly assess the intrinsic bias introduced by the use of each software for each step as well as the bias associated to each parameter choice. Interestingly, we found two to three steps of RNA-seq computational pipeline are particularly undermining the comparability of the results between studies. We are currently in the process of quantifying the biases at each step of the different computational pipelines and this talk will present some of our results.

About the Speaker Series:

Wednesdays@NICO is a vibrant weekly seminar series focusing broadly on the topics of complex systems and data science. It brings together attendees ranging from graduate students to senior faculty who span all of the schools across Northwestern, from applied math to sociology to biology and every discipline in-between. Please visit: https://bit.ly/WedatNICO for information on future speakers.