Results about: cancer

Recent years have seen a paradigm shift in our understanding of gene activity and regulation. It is now clear that processing of primary transcripts as well as translational control open a myriad of opportunities for gene regulation, which are extensively used in virtually every human gene.

<p>Angel R Nebreda</p>

The Signalling and Cell Cycle Laboratory focuses on studying the basic mechanisms of cell regulation, especially regarding how external signals are interpreted by cells to modulate cell proliferation, differentiation and survival. Our research centers on two main subjects:


The recognition of many types of DNA lesions activates the cellular DNA damage response (DDR). The DDR orchestrates the appropriate cellular programs to maintain genome integrity after genotoxic stress.

A high resolution description of the structure and dynamics of proteins is a very useful tool to study the properties and the function of these important biomacromolecules and, most importantly, to understand how changes in sequence or environment can lead to disease.


Candidates with a strong interest in the microtubule cytoskeleton who would like to join our group should e-mail a cover letter with CV including contact information for references to

Our research focuses on three angles of peptide and protein chemistry: the design, synthesis and structure of bioactive molecules. From a structural perspective, we apply modern NMR techniques to study complex molecular recognition processes.

La Marató premia seis proyectos con participación del IRB Barcelona

La fundación financiará 43 proyectos de investigación en cáncer

Desarrollan un algoritmo basado en machine learning para predecir qué pacientes de cáncer pueden beneficiarse de la inmunoterapia

Mediante el uso de machine learning, los investigadores han creado una herramienta que detecta las mutaciones genéticas que activan el sistema inmunitario, lo que contribuye a identificar qué pacientes con cáncer tienen más probabilidades de beneficiarse de la inmunoterapia.

El algoritmo también revela qué personas con determinadas enfermedades hereditarias podrían beneficiarse de un tipo de medicamentos ya existentes.

El potencial de la nueva tecnología se describe hoy en Nature Genetics por parte de investigadores del IRB Barcelona, el Centro de Regulación Genómica y la Universidad de Radboud.