DR Nicholas Abad

Research interest

Currently, my work focuses on the following topics:

Utilizing genomic, transcriptomic, and chromatin accessibility data to identify and categorize functional promoter mutations within large pan-cancer datasets
Developing interactive software tools that facilitate efficient analysis and prioritization of candidate promoter mutations for in vitro validation, benefiting clinicians, bioinformaticians, and biologists.
Predicting gene expression levels based solely on short DNA fragments
Giving lectures and preparing activities for the ML seminar for Masters Students

Curriculum vitae

2012-2016: Bachelor of Science in Mathematics (University of San Francisco, CA, USA)
2017-2018: Master of Science in Data Science (Lancaster University, Lancashire, UK)
2018-2020: Data Scientist / Machine Learning Engineer (fedger.io and Alexander Thamm GmbH, Cologne, DE)


Poster Presentations

Nicholas Abad, Chen Hong, Irina Glas, Sabine Karlous, Benedikt Brors, Cindy Körner, Lars Feuerbach. Identifying Functional,
Non-Coding Somatic Single Nucleotide Variants through the REMIND-Cancer Bioinformatics Pipeline.
Poster presented at German Conference on Bioinformatics (GCB) 2022; 6-8 September 2022; Halle (Saale), Saxony-Anhalt, Germany

personal website