Top 50 Ai For Genomics in LATAM

AI for genomics startups apply machine learning, deep learning and data‑science methods to biological sequence data, variant interpretation and phenotype prediction. The sector includes providers of predictive analytics, drug‑target discovery platforms and clinical‑decision support tools that combine genomic datasets with artificial intelligence.

Typical applications of AI for genomics include variant annotation, disease‑risk scoring, drug‑target identification, synthetic biology design and population‑scale cohort analysis. Users range from research scientists and clinical geneticists to pharmaceutical R&D teams that need predictive models built on sequencing, expression and epigenetic data.

AI genomics platforms commonly run on cloud or hybrid environments using Python, R and Java together with frameworks such as TensorFlow, PyTorch and scikit‑learn. Data pipelines integrate FASTQ, BAM/CRAM, VCF and expression matrices, often stored in object storage or data lakes and accessed via APIs or SaaS portals.

A searchable directory of AI for genomics startups aggregates firms, vendors and platforms that deliver machine‑learning solutions for sequencing, analysis and clinical interpretation. Users can filter by sub‑sector, technology focus, deployment model (SaaS, on‑premise or hybrid) and geographic region such as LATAM.