Our very own Deryc Painter will defend his dissertation July 15. If you are interested to see what he has been up to over the last couple of years, you are welcome to attend his defense! The details:
Topic: Computational Interdisciplinarity: a study in the History of Science
When: July 15, 2019, at 10AM
Where: LSC 202
When: Fall 2019, Th 1:30-4:15
This fall semester, Deryc Painter, Ken Aiello, and Julia Damerow will be teaching the “Computational Humanities Lab.” The class will cover general introductions to computational methods for preparing and analyzing textual and network data in the context of research concerned with social, cultural, historical, linguistic, aesthetic, and interpretive questions. No prior programming knowledge is required, but you should have an interest in learning how to program.
For questions, please contact Julia Damerow at email@example.com.
Join us for the Digital Innovation Group workshop “Intro to Python” on May 8th and 9th, 2019! Did you always wanted to learn how to program with Python, but never got a chance? If so, this workshop might be exactly what you were looking for. We will teach you your first steps with the Python programming language, how to use the Python Ecosystem (pip, virtual environments, etc.), and will also introduce you to Git and GitHub. No prior programming knowledge required! Find out more.
Every week we will be grappling with data collection, management, and/or analysis. Using R we will explore topics from data science, statistics, and machine learning. R is widely used in statistics and data science and has a lot of modules for traditional statistics and modern machine learning algorithms. Find out more here.
On November 7, 2018, Ken Aiello successfully defended his dissertation titled “Systematic Analysis of the Factors Contributing to the Variation and Change of the Microbiome Concept.” He will continue his research as a postdoctoral researcher in the Global Biosocial Complexity Initiative. The Laubichler Lab congratulates Dr. Aiello on a job well done!
Want to know what Aiello’s dissertation is about? Read the abstract!
Mankind finds itself in the Anthropocene, the current geological epoch generally accepted by scholars and denoted by one species, our own, ascending to the role of major driver on Earth. The term Anthropocene was first-coined in the eponymous article by Paul Crutzen and Eugene Stoermer in the IGBP Global Newsletter . Later, Crutzen argues in "Geology of Mankind"  that human effects on the global ecosystem have accelerated and are now the primary influence on the global ecosystem. This human-domination over nature necessitates a new epochal designation; in contrast to the previous epoch, the Holocene, that designated the post-glacial geological period proposed by Sir Charles Lyell in Principles of Geology  in 1833 and adopted in 1885 by the International Geological Congress (IGC). Read the story here.
A research team led by Bryan Daniels with the direction of Sara Walker of the School of Earth and Space Exploration just published the paper "Criticality Distinguishes the Ensemble of Biological Regulatory Networks". Read the story here.
Tethne provides a variety of methods for working with text corpora and the output of modeling tools like MALLET. This tutorial focuses on parsing, modeling, and visualizing a Latent Dirichlet Allocation topic model, using data from the JSTOR Data-for-Research portal.
In this tutorial, we will use Tethne to prepare a JSTOR DfR corpus for topic modeling in MALLET, and then use the results to generate a semantic network like the one shown above.
In this visualization, words are connected if they are associated with the same topic; the heavier the edge, the more strongly those words are associated with that topic. Each topic is represented by a different color. The size of each word indicates the structural importance (betweenness centrality) of that word in the semantic network.
The Data Mining and Analytics Team focuses on extracting the dynamics of complex systems from real-world data.
We build unique and innovative data systems that capture in unprecedented detail the processes that lead to important scientific innovation. Combining expertise in data wrangling, network science, and advanced statistical modeling, we push at the interdisciplinary boundaries of the life sciences, medicine, clinical research, data science, and digital humanities.