In recent years machine learning has made extensive progress in modeling many aspects of
mass spectrometry data. We brought together proteomics data generators, repository …

Much of the complexity within cells arises from functional and regulatory interactions among
proteins. The core of these interactions is increasingly known, but novel interactions …

Proteins cooperate, regulate and bind each other to achieve their functions. Understanding
the complex network of their interactions is essential for a systems-level description of …

Understanding protein-protein interactions (PPIs) and the pathways they comprise is
essential for comprehending cellular functions and their links to specific phenotypes …

In this current era, the identification of both known and novel cell types, the representation of
cells, predicting cell fates, classifying various tumor types, and studying heterogeneity in …

Drugs targeting genes linked to disease via evidence from human genetics have increased
odds of approval. Approaches to prioritize such genes include genome-wide association …

Single‑cell RNA sequencing (scRNA‑Seq) provides detailed insight into gene expression at
the individual cell level, revealing hidden cell diversity. However, scRNA‑Seq data pose …

The three most prevalent malignant skin tumors are basal cell carcinoma (BCC), squamous
cell carcinoma (SCC), and cutaneous melanoma (CM). While BCC and SCC generally …

This thesis explores how bioinformatics advances the study of complex diseases by
providing system-level models that capture intricate gene-protein interactions. Traditional …

In recent years machine learning has made extensive progress in modeling many aspects of
mass spectrometry data. We brought together proteomics data generators, repository …