Bioinformatics Analyses & Multiomics Data Integration
Get answers to your research questions with advanced bioinformatic analyses
DNA sequencing data analysis
DNA sequencing enables identifying mutations, assembling genomes and studying genetic variation in populations of any species.
We analyze DNA sequence data from whole genomes, exomes, sequencing panels, SNP arrays and metagenomic experiments.
RNA sequencing data analysis
Transcriptome-wide expression analyses are the standard approach to study molecular mechanisms in biological systems from single cells to complex microbiomes.
We analyze data from bulk RNA-seq, single-cell RNA-seq, small RNA-seq and a range of other transcriptomic measurements.
Single-cell RNA sequencing data analysis
Single-cell RNA sequencing enables cataloging cells at a scale and resolution unmatched by bulk sequencing.
We analyze single-cell RNA-seq data and integrate datasets across technology platforms, data types (including scATAC-seq), and species.
Spatial transcriptomic data analysis
Spatial transcriptomics provides a molecular view of the organization of complex tissues.
We have experience in both developing new spatial transcriptomics technologies and applying them in various normal tissues and pathologies, such as tumors.
Epigenomic data analysis
Epigenomics characterizes the chromatin state down to minute chemical modifications.
We analyze most types of epigenomic sequencing and array data to gain deeper understanding of gene regulation and to identify biomarkers for diseases.
Proteomic and metabolomic data analysis
Proteomics and metabolomics reveal the functional state of a biological system.
We perform pathway and biomarker analyses on protein and small molecule MS data.
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