Bioinformatics and Computational Biology

  • Amplicon analysis (16S rRNA)

  • Quality control.
  • Alpha and beta diversity analysis.
  • Taxonomic analysis (OTU abundance).
  • Association analysis between condition/treatment and OTU abundance.
  • OTU differential abundance analysis.

  • De novo sequencing of small genomes (Prokaryotes-Levittas).

  • Data preprocessing and quality analysis.
  • Genome assembly.
  • Gene annotation and functional identification.
  • Variant identification, filtering and annotation.
  • Comparative genomics:
  • Pangenome analysis.
  • Global genomic alignment between samples.
  • Genotype-phenotype association analysis.
  • Impact of presence/absence of genes on phenotype.
  • Impact of variants on phenotype.

  • Genomic resequencing (exomes, whole genome and panels).

  • Data preprocessing and quality analysis.
  • Mapping of reads to reference genome.
  • Variant identification, filtering and annotation.

  • Expression analysis (RNA-Seq / Microarrays).

  • Public data access and analysis (e.g. GEO, ArrayExpress, SRA).
  • Data preprocessing and quality analysis.
  • Differential expression analysis.
  • miRNA target gene prediction.
  • Functional enrichment analysis: metabolic pathway (KEGG, Reactome and WikiPathways) and Gene Ontology.

  • Survival analysis.

  • Univariate and multivariate Cox regression analysis.
  • Kaplan-Meier curves.
  • Gene signature search.



We provide the necessary resources for intensive computation in the computational cluster, as well as update policies and distribution of computational resources.

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