Explore how AI is transforming genomic research, driving clinical insights, and enabling multiomic discovery
Artificial intelligence (AI) is transforming genomics by offering advanced tools to analyze and interpret complex genetic and multiomic data. Genomic AI complements traditional analysis methods, enhancing accuracy and providing comprehensive genome annotation and interpretation. By integrating accelerated compute, data science, and AI, we can deliver precise sequencing results, significantly reducing analysis time while ensuring rigorous assembly of data across all stages.
Explainable artificial intelligence brings transparency to genomic data analysis by ensuring that AI-generated insights are accurate, traceable, evidence-based, and easy to review. For researchers interpreting complex genetic data, this clarity is essential to trust the findings and scale interpretation with confidence.
Emedgene software, developed for germline tertiary analysis, applies highly accurate explainable AI to highlight high-priority variants and surface supporting evidence in an intuitive, organized format. This enables faster decision-making while reducing manual workload and maintaining scientific rigor across a range of research applications.
Illumina applies AI across the genomic workflow—from variant calling to interpretation and multiomic analysis—to help researchers gain faster, more accurate, and reproducible insights from complex biological data.
Identify relevant DNA and RNA variants in tumor types and conduct in-house comprehensive genomic profiling of tumor samples.
PrimateAI-3D and Splice AI, leading algorithms from the Illumina Artificial Intelligence Laboratory, are disrupting how we approach drug discovery and precision medicine.
Obtain accurate and informative genetic disease insights.
Predicting gene expression alterations due to promoter mutations is essential for understanding genetic regulation. PromoterAI is a deep learning model that predicts the impact of promoter variants on gene expression by analyzing genomic sequences.
AI plays a role at every stage of the genome sequencing workflow, helping to increase efficiency, enhance accuracy, and support confident decision-making. From quality control to interpretation, intelligent tools streamline processes and uncover deeper insights.
AI-enhanced error correction: Identifies and corrects systematic sequencing errors to improve data quality at the earliest stage.
Predictive QC: Uses machine learning to forecast potential issues before they impact downstream analysis.
Base calling optimization: Deep learning models translate raw signals into bases (A, T, G, C) with improved speed and accuracy.
Variant calling accuracy: Detects SNVs, indels, and structural variants with enhanced sensitivity and precision.
Read assembly acceleration: AI streamlines the alignment and reconstruction of DNA fragments, reducing computational time.
Gene prediction and annotation: Identifies coding regions and predicts gene functions with higher confidence.
Gene and pathway analysis: Discovers expression patterns and biological pathways associated with disease or phenotypes.
Population-level insights: Analyzes genetic variation across cohorts to support association studies and evolutionary research.
Variant prioritization with explainable AI: Highlights candidate variants and links them to supporting evidence using explainable AI.
Automated literature curation: NLP tools scan databases and publications to surface relevant gene-disease associations.
The collaboration will advance technology platforms for the analysis and interpretation of multiomic data, accelerating progress in clinical research, genomics AI development, and drug discovery.
The collaboration will combine leading Illumina AI technologies with Tempus's comprehensive multimodal data platform to train genomic algorithms and ultimately accelerate clinical adoption of molecular testing for patients.
This strategic research collaboration will accelerate drug target discovery by combining their strengths in artificial intelligence (AI) based genome interpretation and genomic analysis techniques along with industry expertise.
Leveraging Genomic AI to deliver a more accurate and comprehensive genome
Artificial intelligence (AI) is reshaping genomics as we know it. The capability of AI to parse and analyze massive amounts of sequencing data is a natural fit to facilitate a deeper and more accurate understanding of the genome.
“How do you train genomic AI?”
In this video presentation, Kyle Farh (Illumina AI Lab) outlines the AI work being done on the protein coding side and non-coding sides, along with the use of deep learning to predict pathogenic mutations in humans.
Illumina Connected Annotations
Providing annotations of genomic variants you can trust, leveraging 17 databases with the option to access PrimateAI-3D, SpliceAI, PromoterAI, COSMIC, and OMIM.
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