Below you find the complete list of Tier-1-projects since the start of the regular project application programme.

8 Projects found VIB

Optimization of long-read sequencing mapping to discover biomarkers for cancer immunotherapy

Date: 01.12.2017
  • Promotor(s): Diether Lambrechts
  • Institution(s): KU Leuven , VIB
  • Domain(s): Life sciences

In silico study of lymphoma-related MyD88 mutations and their effect on protein actions and mechanism

Date: 01.07.2017
  • Promotor(s): Frank Peelman
  • Institution(s): UGent , VIB
  • Domain(s): Life sciences
The protein MyD88 provides a crucial signaling function for several receptors that are essential for human immunity against invading pathogens. In various cancer types, it has been found that part of this protein has undergone mutation. In this project, we examine several mutations in this protein that lead to various types of white blood cell cancers. Via biochemical experiments, we analyze the effects of these mutations on the protein function. With the aid of microsecond molecular dynamics, we link this experimental data to molecular mechanisms. This helps us understand how these mutations affect the actions and mechanism of MyD88, and how they are connected to disease development processes.

Mechanistic modeling and in silico evolution of gene regulatory networks

Date: 01.11.2016
  • Promotor(s): Steven Maere
  • Institution(s): UGent , VIB
  • Domain(s): Life sciences
Gene and genome duplications are thought to have been important in establishing the complexity of the gene regulatory systems observed in present-day organisms, and they have been linked to the establishment of many adaptations and evolutionary innovations. However, most of the hypotheses on the evolutionary importance of gen(om)e duplications thus far have been obtained by studying genome sequences and highly abstracted molecular system representations. In this project, we use a mechanistic modelling approach, inspired on the engineering-type approaches used in molecular systems biology, to get more insight into the evolutionary impact of gen(om)e duplications on molecular systems. To this end, we use a fine-grained, sequence-based genotype-phenotype mapping model in combination with population-based evolutionary algorithms.

Optimization of long-read sequencing mapping to discover biomarkers for cancer immunotherapy

Date: 01.07.2016
  • Promotor(s): Diether Lambrechts
  • Institution(s): KU Leuven , VIB
  • Domain(s): Life sciences
In recent years, immune checkpoint inhibitors achieved remarkable clinical successes in several cancers. Quantifying the tumor’s total mutational load, assessing the expression of retrotransposable RNA and detection of CD8+ cytotoxic T-cells in tumors have all emerged as promising mechanisms underlying response to immune checkpoint inhibitors. In this application, we aim to leverage the long-read sequencing technology to validate and greatly enhance the detection of these potential biomarkers for the prediction of immune checkpoint inhibition response.

A stochastic birth-death model for evolution of gene family copy numbers along a phylogeny

Date: 01.08.2015
  • Promotor(s): Steven Maere
  • Institution(s): UGent , VIB
  • Domain(s): Biology , Life sciences
Whole genome duplications (WGDs) are believed to play a major role in angiosperm evolution. Previous studies have found that some functional categories of genes, including regulatory and developmental categories, expand almost exclusively through genome duplication, likely because dosage balance effects counteract their expansion through small-scale duplications. However, the duplication dynamics of individual gene families have not been studied in detail. We developed a stochastic birth-death model to study the size evolution of gene families across a species phylogeny, taking into account both small-scale and large-scale duplication events. We use this model on a set of angiosperm species with known WGD history to assess the dosage balance sensitivity of individual gene families, and we interpret the results in the context of the potential impact of WGDs on evolutionary innovation in angiosperms.