Our AI Platform uses a Data Science (DS)
problems from any field are reduced to only three:
• Classification: Diagnosis (Cancer vs. Normal)
• Regression: Survival rate
• Clustering: Patient stratification
We also offer Bioinformatics services:
1. RNA-seq data analysis: This pipeline
includes steps for quality control, adapter trimming, alignment, variant calling, transcriptome reconstruction and post-alignment quantitation.
2. Small RNA-seq data
analysis: Used to discover novel miRNAs and other small noncoding RNAs, and examine the
differential expression of all small RNAs in the sample.
(SNP and Indels) analysis: After alignment of the reads onto a reference genome, it is possible to detect base modifications (SNP or small indels) between the library and the
reference. The variant list is then filtered according to specific thresholds in order to retrieve variants of interest.
4. Copy number variation: are associated with complex phenotypes, by changing the number of copies of genes in the cell, they
affect coding sequences and play an important role in the susceptibility or resistance to human diseases.
5. Single Cell RNA-seq: can reveal complex and rare cell populations, uncover regulatory relationships between genes, and track
the trajectory of distinct cell lineages.
6. CHIP-Seq: (Chromatin immunoprecipitation
followed by sequencing) is used for genome-wide profiling of DNA-binding proteins, histone modifications or nucleosomes
7. Methylation: Current advances in NGS technologies
allow for a genome-wide profiling of methyl marks both as single nucleotide and at a single-cell resolution.
We provide advanced data analysis with both a standard bioinformatics approach and an AI centered approach: