Central Support Units for Biomedical Research
Bioinformatics and Biostatistics Unit 
The mission of the Bioinformatics and Biostatistics Unit is to provide engineering and computing resources to satisfy both the bioinformatics analysis requirements and the different technological needs that result from research and clinical practice, with an emphasis on the promotion and implementation of state-of-the-art technologies.
The aim of the bioinformatics and biostatistics area is to support researchers with scientific advice for the experimental design, ad-hoc genomic data analysis, and data visualisation. The unit is currently setting up robust workflows for the various and most common types of genomic data analysis, highlighting the quality control on the several steps to achieve the best results. Also, the Unit plans to be continuously updating to improve the current services and to broaden them in the future based on demand.
Contact
Contact email: bioinformatica@imibic.org
Personnel
The Bioinformatics Unit is composed of:
Adrián Santiago Ortiz
Bioinformatician
- adrian.santiago@imibic.org
- +34 957 21 38 62 (Corporative 3862)
Equipment and Facilities
- Sistema HPC (High Performance Computing):
- Bull Sequana X800
- 8 Intel Xeon, 192 núcleos en total, 2.4GHz
- 3TB RAM
- 4 GPUs NVIDIA Tesla V100
- 48 TB de almacenamiento
- Computing resources:
- BullX R428-E3 node. 4x Intel Xeon E5-4610v2 8c, 32 cores. 256 GB RAM
- 3D Printer:
- BCN3D+ Fused Deposition Material Printer (Last update: 2019)
- Development resources:
- Apple Mac Mini for iOS app development (Last update: Mayo 2020)
- Raw data pre-processing and cleaning to subsequent analysis.
- Analysis and integration of omic data. Bioinformatic assistant to studies focus on genomic, transcriptomic (RNA-seq and single cell), proteomic, methylation…
- Differential expression analysis between experimental groups or conditions.
- Metagenomic studies and microbiome analysis using 16s rRNA amplicon sequencing.
- Develop algorithms and in-house scripts to solve user requirements such as filtering and integration of large databases, databases transformation…
- Consultancy to apply projects.
- Analysis of biological significant using methods such as Over-Representation Analysis (ORA), Gene Ontology analysis (GO-terms), pathways (Kegg database) and Gene-Set Enrichment Analysis (GSEA).
- Filogenetic analysis.
- Bacterial genome annotation.
- Review of metodology and research protocols: define hypothesis and objectives, variable selection, define statistical analysis…
- Consultancy about techniques and statistical methodologies.
- Sample size calculation.
- Exploratory data analysis and descriptive statistics.
- Inferential statistical analysis (univariate and multivariate).
- Evaluation of diagnostic tests: sensitivity, specificity, predicted values, ROC curves…
- Analysis of surveillance data.
- Longitudinal data analysis.
- Omic data and high-dimensional data analysis.
- Other statistical tecniques (bayesian analysis, meta-analysis…).
