The Laubichler Lab

The Manfred Laubichler Lab at ASU studies evolutionary novelties from genomes to knowledge systems, the structure of evolutionary theory and the evolution of knowledge by means of computational approaches. Projects in the lab create new methods, tools and digital infrastructures for the history and philosophy of science.

Tutorial: Generating and Visualizing Topic Models with Tethne and MALLET

Published: December 15, 2017

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.

This tutorial was developed for the course Introduction to Digital & Computational Methods in the Humanities (HPS), created and taught by Julia Damerow and Erick Peirson.

Living organisms find a critical balance

Published: October 4, 2018

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

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The Data Mining and Analytics Team

Published: August 30, 2017

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.

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New Publication in Biomedical Research

Published: August 28, 2017

On March 30th, 2017, Manfred Laubichler, Julia Damerow and Erik Pierson published a paper titled The diversity of experimental organisms in biomedical research may be influenced by biomedical funding.

Contrary to concerns of some critics, we present evidence that biomedical research is not dominated by a small handful of model organisms. An exhaustive analysis of research literature suggests that the diversity of experimental organisms in biomedical research has increased substantially since 1975. . .

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