“When a biologist met Python”

An adventure into the natural sciences using tools like Biopython, Bokeh, Networkx, Ecopy and more!

Maria Molina-Contreras

Algorithms Data Science Natural Science Scientific Libraries (Numpy/Pandas/SciKit/...) python

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Biology and computing are closer than we usually think, for example many algorithms are inspired in biology patterns, and complementary to that, researchers needs special algorithms to have a better understanding of our environment. Thus, there is a strong relation an dependency.
In the past years, Biology has been transformed into computational biology. Therefore
technological advances helps us to predict physical interactions between atoms and DNA, because we are being able to integrate information from biology into algorithms.

Python has become a popular programming language in biosciences because it has a clean syntax that makes it easy to read language. In addition to this, there are many modules (toolkits) extending to different biological domains, like metabolomics, structure analysis, phylogenomics, molecular biology and others. Python is currently improving researcher’s workflow, helping us to focus on the theory or experimental part, instead of fighting with old buggy applications.

This talk aims to be oriented to all audiences (with/without biological background) since we will go together through an amazing adventure into the natural sciences using tools like Biopython, Bokeh, Networkx, Ecopy and much more! Are you brave enough to follow me on this journey?

Type: Talk (30 mins); Python level: Beginner; Domain level: Beginner

Maria Molina-Contreras

Maria Jose works as a Data analyst/manager at ZAGENO based in Berlin. She is really passionate about Python and data science, specially machine learning. Maria got a doctorate in Biotechnology for investigating the molecular mechanisms modulating a syndrome in plants (with agronomic relevance). During those seven years she has developed her strong analytical skills.

Her goal is to make a difference in the world by using both her technical knowledge and data analyses experience.