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Services

Find out more details about our Advanced AI Platform

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A Data Science Approach

Learn how we can use our platform to tackle any biomedical problem

Our AI Platform harnesses the power of Data Science (DS) methodologies to streamline complex problem-solving across various domains.

In the world of Data Science, we simplify complex problems from various domains into just three core categories

• Classification: Distinguishing between conditions, such as Cancer vs. Normal, with precision.

• Regression: Predicting outcomes like survival rates with accuracy.

• Clustering: Facilitating patient stratification for improved healthcare decision-making.

Unleash the potential of Data Science with our innovative AI Platform.

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.

3. Variants (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: