Clemens B. Hug

Polypharmacology is an enduring and nearly universal property of kinase inhibitors

This paper shows that kinase inhibitors commonly target multiple kinases, independent of approval status, and highlights the need for better understanding of their polypharmacology.

Morphology-Aware Profiling of Highly Multiplexed Tissue Images using Variational Autoencoders

This paper introduces a method that combines autoencoders with segmentation to improve single-cell analysis of multiplexed tissue images by capturing morphology and reducing signal spillover.

Multimodal Spatial Profiling Reveals Immune Suppression and Microenvironment Remodeling in Fallopian Tube Precursors to High-Grade Serous Ovarian Carcinoma

This study uses spatial profiling to show immune suppression and microenvironment changes in fallopian tube precursors of high-grade serous ovarian cancer.

TYK2 as a novel therapeutic target in Alzheimer Disease

The paper identifies TYK2 as a potential therapeutic target for neurodegenerative diseases by linking cdsRNA-induced inflammation to interferon signaling and demonstrating protective effects of TYK2 inhibitors.

Sendai virus persistence questions the transient naive reprogramming method for iPSC generation

The paper questions the TNT method for iPSC generation by showing persistent Sendai virus expression in hiPSCs, altering reprogramming factor levels and ratios.

Multi range ERK responses shape the proliferative trajectory of single cells following oncogene induced senescence

The paper investigates how varying ERK activity levels influence proliferation in cells undergoing oncogene-induced senescence, finding intermediate ERK activity promotes maximal proliferation.

A community-based approach to image analysis of cells, tissues and tumors

The paper discusses computational challenges in analyzing multiplexed imaging data and outlines community-driven approaches to address them through workshops and hackathons.

Machine Learning Identifies Novel Candidates for DrugRepurposing in Alzheimer's Disease

The paper presents a machine learning framework to identify FDA-approved drugs for repurposing in Alzheimer's Disease by analyzing gene lists associated with disease severity and molecular mechanisms.

FAN-C: A Feature-rich Framework for the Analysis and Visualisation of C data

FAN-C simplifies Hi-C data analysis by providing a comprehensive tool with matrix generation, analysis, and visualization capabilities, compatible with common Hi-C formats.

Exploring the understudied human kinome for research and therapeutic opportunities

This paper refines the definition of the human kinome, identifies understudied kinases, and highlights their potential as drug targets through differential expression, essentiality, and mutation data.