Wolfram Computation Meets Knowledge

Education & Academic

A New Way to Ask Wolfram|Alpha Questions with Math Input

We are excited to talk about a feature we released this summer that we call Math Input. We’ve had many requests to add this feature to the site, and after a lot of hard work from multiple teams, we’re ready to share it with you. Head over to Wolfram|Alpha to see it for yourself:
Current Events & History

Newick Trees, Proximity Resources and Accessions Analyzing SARS-CoV-2 Genetic Sequences

While working with SARS-CoV-2 genetic data in the Wolfram Data Repository, we noticed that there was frequently only a relative handful of differences compared with the overall size of the sequences. This allowed us a number of interesting opportunities for further processing.
Current Events & History

John Snow & the Birth of Epidemiology Data Analysis & Visualization

In 1854, there was a major cholera outbreak in Soho, a neighborhood in London that Judith Summers described as full of “cow-sheds, animal droppings, slaughterhouses, grease-boiling dens and primitive, decaying sewers.” At the time, the cause of the outbreak was unknown because germ theory was still being developed and disease transmission was not well understood. Miasma theory was the dominant hypothesis, and it proposed that diseases, including cholera and the plague, were spread by foul gasses emitted from decomposing organic matter.
Computation & Analysis

From Plant Roots to Deep Space Wolfram Community Computational Explorations

For the past few months, Wolfram Community members have shared their computational explorations on topics ranging from computational art and games to original, published research. I’ll comment here on just a few of their many interesting examples. Please feel free to share your ideas with us at Wolfram Community, and let’s explore the world computationally.
Education & Academic

Using Neural Networks to Boost Student Learning in Chemistry

I attended the Wolfram Neural Networks Boot Camp 2020, and that inspired me to incorporate elements of data science and machine learning in my course. The helper functions for machine learning make it quite easy to experiment and introduce such applications to students. We chose to perform image recognition and classification problems that are routinely used to initiate the topics of both neural networks and machine learning.