Cosima Caliendo

Discovery of Polygenic Adaptation Patterns in Chironomus Riparius.

As a PhD student in bioinformatics, I am currently working on a project that combines elements of bioinformatics and population genetics in cooperation with BiK-F Senckenberg. My research focuses on identifying rapid adaptation patterns in genomic data.
My work began with a wet lab experiment using Chironomus riparius, where I subjected populations to selection pressure over several generations. This initial study aimed to explore the feasibility of observing rapid adaptation in a controlled setting.
Building on these results, I am now developing computational approaches to identify rapid adaptation patterns in genomic data. My current work involves two main methods:

•⁠ ⁠A machine learning approach using Support Vector Machines (SVM)
•⁠ ⁠A statistical approach using Naive Bayesian classifiers

I am applying these algorithms to my experimental sequencing data to gain deeper insights into the mechanisms of adaptation.

Exploring the influence of mTOR on the synaptosome in the mouse brain.

I am cooperating with the Human Genetics Group of Prof. Dr. Susann Schweiger in evaluating and visualizing mass spectroscopy data of mouse brain tissue. This project explores the influence of mTOR on the synaptosome in the mouse brain. I am particularly interested in the challenge of linking large amounts of information meaningfully and presenting it using networks and graphs.

Coordination of Emergent Algorithmics Intelligence Research Project.

Currently, Iam the project coordinator of the of the Emergent AI Research Project, which deals with the interdisciplinary application of machine learning.

 

Publications