CNIO Bioinformatics Unit

Welcome to the CNIO Bioinformatics Unit website!

Our group has a double component of bioinformatics support to Spanish National Cancer Research Centre (CNIO) and external investigators and research in bioinformatics. Lab research activity is focused on the development of novel computational techniques for the integration of cancer genomic data with clinical and pathological features. Our final goal is to translate this knowledge from cancer genome-scale studies to effective cancer patient’s treatment.

Introducing bollito: a flexible pipeline for comprehensive single-cell RNA-seq analyses

We are proud to announce bollito, an automated, flexible and parallelizable computational pipeline for the comprehensive analysis of single-cell RNA-seq data. Starting from FASTQ files or pre-processed expression matrices, bollito performs…

Predicting isoforms functional importance with TRIFID

We are pleased to announce TRIFID, a Machine Learning-based method for predicting isoform functional importance. The advent of long-read sequencing means that the number of annotated transcripts in reference databases will increase. Therefore,…

#worldcancerday is today, celebrating each step toward fewer preventable deaths and improved quality of life for patients. EU project @EOSC4Cancer is expediting progress, making various types of #cancerdata accessible across borders to support research.

📍'Tu salud. Tu Planeta'
Dedicamos la campaña del #DiaMundialContraElCancer a llamar la atención acerca del vínculo entre salud humana y la del planeta🌏

✅El 21% de los cánceres podrían prevenirse mejorando el medio ambiente (@WHO)


Open position for a bioinformatician to work in our cancer pharmacogenomic projects. Omics data analysis focused on renal cell carcinoma biomarkers. Great work environment and excellent cancer research at @CNIOStopCancer
More info
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We are always open to motivated and talented postdoctoral candidates, graduate students and summer rotation students in areas of computational biology, and medicine or molecular biology applicants with an interest in computational biology.

For questions regarding available training opportunities, please contact us.