presenting at AIMMS festival
Halima Mouhib and Evert Bosdriesz gave an introduction of our group at the AIMMS fashionshow, highlighting the key topics of our research. aimmsfestival.nl/
About Us
AIMMS Festival 2023
Join us this July for our inaugural AIMMS Festival — an unforgettable event spanning two inspiring days and one night at Hotel ZuiderDuin in Egmond aan Zee. An exhilarating program that brings together cutting-edge research from our esteemed institute (that means you!) and addresses the innovation challenges of our valued industrial partners. During the festival, we will have opportunities for everyone to ignite new connections and foster collaborations with both colleagues and industry professionals. Imagine engaging in brainstorm sessions focused…
Tumour break load is a biologically relevant feature of genomic instability with prognostic value in colorectal cancer
We are pleased to share our recent publication by Soufyan Lakbir and Sanne Abeln in collaboration with Remond Fijneman, showing that the Tumor Break Load (TBL) is a distinct feature of genomic instability with prognostic value for patients with resected stage II and III microsatellite stable colorectal cancer. Highlights Abstract Background Clinically implemented prognostic biomarkers are lacking for the 80% of colorectal cancers (CRCs) that exhibit chromosomal instability (CIN). CIN is characterised by chromosome segregation errors and double-strand break repair defects that lead to…
Ten quick tips for sequence-based prediction of protein properties using machine learning
We are happy to share our latest publication about protein property prediction using machine learning by Qingzhen Hou, Katharina Waury, Dea Gogishvili, Anton Feenstra. Abstract The ubiquitous availability of genome sequencing data explains the popularity of machine learning-based methods for the prediction of protein properties from their amino acid sequences. Over the years, while revising our own work, reading submitted manuscripts as well as published papers, we have noticed several recurring issues, which make some reported findings hard to understand…
Discovery of novel CSF biomarkers to predict progression in dementia using machine learning
We are excited to share our latest publication by Dea Gogishvili. The paper is a part of a special collection – artificial intelligence for personalised medicine. Here we explore the rate of cognitive decline in dementia patients to identify CSF biomarkers. Thanks to the co-authors for their valuable insights and dedication in bringing this project to life.
Clusters of co-abundant proteins in the brain cortex associated with frontotemporal lobar degeneration
New article out in collaboration with Charlotte Teunissen from the AUMC! We combined existing tools with a novel validation method to identify clusters of co-abundant proteins related to frontotemporal dementia. Read all about it here.
How sticky are our proteins? Quantifying hydrophobicity of the human proteome
We are happy to share our recent publication by Juami Hermine Mariama van Gils, Dea Gogishvili, Jan van Eck, Robbin Bouwmeester, Erik van Dijk, and Sanne Abeln. Check out the ISMB-ECCB talk by Juami van Gils and Dea Gogishvili on our YouTube channel. Abstract: Proteins tend to bury hydrophobic residues inside their core during the folding process to provide stability to the protein structure and to prevent aggregation. Nevertheless, proteins do expose some ‘sticky’ hydrophobic residues to the solvent. These residues can play an important functional…