dr. Louise de Schaetzen van Brienen

Journal Article
A1
open access

Multifocal cohort analysis unveils cell types associated with regional lymph node seeding in prostate cancer

Louise de Schaetzen van Brienen (UGent) , Taewoo Jung (UGent) , Maarten Larmuseau (UGent) , Kim Van der Eecken, Marie Van Hecke (UGent) , Jef Haerinck (UGent) , Jordy De Coninck (UGent) , Jan Vanwelkenhuyzen (UGent) , Nicolaas Lumen (UGent) , Bram De Laere (UGent) , et al.

(2026) GENOME MEDICINE. 18(1).

Add to list

Journal Article
A1
open access

Whole slide imaging-based prediction of TP53 mutations identifies an aggressive disease phenotype in prostate cancer

Marija Pizurica (UGent) , Maarten Larmuseau (UGent) , Kim Van der Eecken, Louise de Schaetzen van Brienen (UGent) , Francisco Carrillo-Perez, Simon Isphording (UGent) , Nicolaas Lumen (UGent) , Jo Van Dorpe (UGent) , Piet Ost (UGent) , Sofie Verbeke (UGent) , et al.

(2023) CANCER RESEARCH. 83(17). p.2970-2984

Add to list

WSI based prediction of TP53 mutations identifies aggressive disease phenotype in prostate cancer

Marija Pizurica (UGent) , Maarten Larmuseau (UGent) , Kim Van der Eecken, Louise de Schaetzen van Brienen (UGent) , Francisco Carrillo-Perez, Simon Isphording, Nicolaas Lumen (UGent) , Jo Van Dorpe (UGent) , Piet Ost (UGent) , Sofie Verbeke (UGent) , et al.

(2023) CANCER RESEARCH. In Cancer Research 83(8, Supplement S).

Add to list

PhD Thesis

Cohort analysis to identify metastatic prostate cancer drivers

Louise de Schaetzen van Brienen (UGent)

(2023)

Add to list

Journal Article
A2
open access

Extracting functional insights from loss-of-function screens using deep link prediction

Pieter-Paul Strybol, Maarten Larmuseau (UGent) , Louise de Schaetzen van Brienen (UGent) , Tim Van den Bulcke and Kathleen Marchal (UGent)

(2022) CELL REPORTS METHODS. 2(2).

Add to list

Journal Article
A1
open access

Halvade somatic : somatic variant calling with Apache Spark

Dries Decap (UGent) , Louise de Schaetzen van Brienen (UGent) , Maarten Larmuseau (UGent) , Pascal Costanza, Charlotte Herzeel, Roel Wuyts, Kathleen Marchal (UGent) and Jan Fostier (UGent)

(2022) GIGASCIENCE. 11.

Add to list

Journal Article
A1
open access

Network-based analysis to identify drivers of metastatic prostate cancer using GoNetic

Louise de Schaetzen van Brienen (UGent) , Giles Miclotte (UGent) , Maarten Larmuseau (UGent) , Jimmy Van den Eynden (UGent) and Kathleen Marchal (UGent)

(2021) CANCERS. 13(21).

Add to list

Journal Article
A1
open access

Comparative analysis of somatic variant calling on matched FF and FFPE WGS samples

Louise de Schaetzen van Brienen (UGent) , Maarten Larmuseau (UGent) , Kim Van der Eecken, Frederic De Ryck (UGent) , Pauline Robbe Vandewalle, Anna Schuh, Jan Fostier (UGent) , Piet Ost (UGent) and Kathleen Marchal (UGent)

(2020) BMC MEDICAL GENOMICS. 13(1).

Academic Bibliography

dr. Louise de Schaetzen van Brienen

Multifocal cohort analysis unveils cell types associated with regional lymph node seeding in prostate cancer

Whole slide imaging-based prediction of TP53 mutations identifies an aggressive disease phenotype in prostate cancer

WSI based prediction of TP53 mutations identifies aggressive disease phenotype in prostate cancer

Cohort analysis to identify metastatic prostate cancer drivers

Extracting functional insights from loss-of-function screens using deep link prediction

Halvade somatic : somatic variant calling with Apache Spark

Network-based analysis to identify drivers of metastatic prostate cancer using GoNetic

Comparative analysis of somatic variant calling on matched FF and FFPE WGS samples

Contents

Support

Contact