Network Analysis to (Improve Stem) Cell Differentiation

Background Stem cells are a type of cells that can differentiate into other cell types as well as self-renew, which makes them of interest for many different medical applications. Please read https://stemcells.nih.gov/info/basics/stc-basics for a basic introduction to stem cells. The field of systems biology focuses on investigating complex biological processes instead of single entities, which often focuses on computationally modeling and analyzing the data as networks/ graphs. Such networks are for example protein protein interaction networks, regulation network or gene gene co-expression networks. ...

May 21, 2024

Prediction of Drug Induced Gene Expression Perturbations through Drug Target and Protein-Protein Interaction Information

Background Transcriptomics provide insights into gene expression and with it the ability to analyze one of the fundamental processes of life - the translation from gene to protein. Single Cell RNA sequencing (scRNAseq) is a technology that measures transcriptomics on the single cell level. However, biological data is highly complex, variability and noisy, making it challenging to analyze and work with. The goal of the project is to evaluate if deep learning can infer gene expression profiles of specific conditions (exposures) by only receiving prior information about an exposure, such as a drug’s known gene targets as well as a general protein-protein interaction network. The aim is to evaluate the model based on its zero-shot performance (e.g. unseen drugs). ...

May 21, 2024

Transfer learning & Training of (Explainable) Deep Learning Model for Single Cell Transcriptomics

Background Transcriptomics provide insights into gene expression and with it the ability to analyse one of the fundamental processes of life - the translation from gene to protein. single Cell RNA sequencing (scRNAseq) is a technology that measures transcriptomics on the single cell level. However, biological data is highly complex, variability and noisy, making it challenging to analyse and wo. By building on pre-trained general scRNAseq deep learning model we want to fine-tune and train the model task specific. Examples of existing models are Geneformer https://www.nature.com/articles/s41586-023-06139-9 or scGPT https://www.nature.com/articles/s41592-024-02201-0. If the student decides that existing models are not suitable there is also the option to build/train from scratch. ...

May 21, 2024

Sugar translation tool

Background Polysaccharides, also commonly known as sugars, are one of the main molecules in living beings, and they present a complex structure that may include a variety of residues and ramifications. There exists more than 4 systems that represent these structures, but in some cases it cannot be 1-1 translated. Some science backgrounds may be more used to one of these naming systems, which prevents transcommunication between fields. Also, due to the complexity of the polysaccharides it is not straightforward to understand the systems for newcomers. ...

November 15, 2023