latest news & announcements

Predictive machine learning methods for species ecology

The study of species' response is a key to understand the ecology of a species (e.g. critical habitat requirement and biological invasion processes) and design better conservation and management plans (e.g. problem identification, priority assessment and risk analysis). Predictive machine learning methods can be used as a tool for modeling species distributions as well as for describing important variables and specific habitat conditions required for a target species.

Toolkit to assess the quality of mass spectrometry proteomics experiments

Despite many technological and computational advances, the results of a mass spectrometry proteomics experiment are still subject to a large variability. For the understanding and evaluation of how technical variability affects the results of an experiment, several computationally derived quality control metrics have been introduced. However, despite the availability of these metrics, a systematic approach to quality control is often still lacking because the metrics are not fully understood and are hard to interpret.

Statistics for clinical effectiveness

The effect of adherence to statin therapy on cardiovascular mortality: quantification of unmeasured bias using falsification end-points

Background: To determine the clinical effectiveness of statins on cardiovascular mortality in practice, observational studies are needed. Control for confounding is essential in any observational study. Falsification end-points may be useful to determine if bias is present after adjustment has taken place.

sORFs.org: a repository of small ORFs identified by ribosome profiling

With the advent of ribosome profiling, a next generation sequencing technique providing a "snapshot" of translated mRNA in a cell, many short open reading frames (sORFs) with ribosomal activity were identified. Follow-up studies revealed the existence of functional peptides, so-called micropeptides, translated from these 'sORFs', indicating a new class of bio-active peptides. Over the last few years, several micropeptides exhibiting important cellular functions were discovered.

Positional proteomics reveals differences in N-terminal proteoform stability

To understand the impact of alternative translation initiation on a proteome, we performed a proteome-wide study on protein turnover using positional proteomics and ribosome profiling to distinguish between N-terminal proteoforms of individual genes. By combining pulsed SILAC with N-terminal COFRADIC, we monitored the stability of 1,941 human N-terminal proteoforms, including 147N-terminal proteoform pairs that originate from alternative translation initiation, alternative splicing or incomplete processing of the initiator methionine.

Highly effective and tissue-restricted anti-melanoma therapy in sight

In collaboration with BIG N2N researchers from UGent, VIB scientists from KU Leuven have revealed a remarkable link between malignant melanoma and a non-coding RNA gene called SAMMSON. The SAMMSON gene is specifically expressed in human malignant melanoma and, strikingly, the growth of aggressive skin cancer is highly dependent on this gene. The conclusions could pave the way for improved diagnostic tools and skin cancer treatment.

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