AI-Powered Solution

Our AI-Driven Pipeline for eDNA Analysis

A comprehensive machine learning solution that transforms raw eDNA data into actionable biodiversity insights

Core Innovation

Database-Independent Species Identification

Our AI pipeline uses advanced machine learning to identify species from eDNA sequences without relying solely on reference databases. By generating embeddings and clustering sequences, we can detect both known and novel taxa in marine environments.

  • Unsupervised clustering identifies putative taxa
  • Deep learning embeddings capture sequence patterns
  • Novel species detection alongside known taxa
Key Capabilities
Classification Rate80-95%
Processing SpeedHours
Novel DetectionEnhanced
Database DependencyReduced

AI Pipeline Workflow

Our comprehensive pipeline processes raw eDNA data through multiple AI-enhanced stages

1
Data Preprocessing
Clean and denoise raw eDNA reads using advanced quality control algorithms

Quality Control & Filtering

Raw eDNA sequences undergo rigorous quality assessment, removing low-quality reads, adapter sequences, and potential contaminants to ensure high-quality input data.

  • • Quality score filtering and trimming
  • • Adapter and primer removal
  • • Chimera detection and removal
  • • Length and complexity filtering
2
ML Embeddings
Generate high-dimensional embeddings that capture sequence patterns and relationships

Deep Learning Feature Extraction

Advanced neural networks transform DNA sequences into meaningful numerical representations that capture evolutionary relationships and taxonomic patterns.

  • • Transformer-based sequence encoding
  • • Evolutionary distance preservation
  • • Multi-scale pattern recognition
  • • Dimensionality optimization
3
AI Clustering
Group sequences into putative taxa using unsupervised clustering algorithms

Intelligent Sequence Clustering

Machine learning algorithms identify natural groupings in the embedding space, representing potential taxonomic units without requiring database matches.

  • • Density-based clustering (DBSCAN)
  • • Hierarchical clustering analysis
  • • Optimal cluster number detection
  • • Noise and outlier handling
4
Taxonomic Assignment
Label clusters using available databases while preserving novel taxa information

Hybrid Classification Approach

Combine database matching with cluster analysis to provide taxonomic labels for known species while flagging novel or uncharacterized taxa for further investigation.

  • • BLAST-based database matching
  • • Confidence score calculation
  • • Novel taxa flagging system
  • • Taxonomic hierarchy assignment
Technology Stack

Cutting-Edge AI Technologies

Our pipeline leverages state-of-the-art machine learning frameworks and bioinformatics tools

Deep Learning
Transformer architectures and convolutional neural networks for sequence analysis and pattern recognition in genomic data.
High-Performance Computing
GPU-accelerated processing and distributed computing for handling large-scale eDNA datasets efficiently.
Bioinformatics Tools
Integration with established bioinformatics pipelines and databases for comprehensive sequence analysis and validation.
Research Data

Our Collected Dataset

Comprehensive eDNA datasets from diverse marine environments, curated and processed for AI training and validation

Comprehensive Coverage

Our dataset includes eDNA samples from various marine environments, covering multiple taxonomic groups and geographic regions to ensure robust AI model training.

Quality Assured

All sequences undergo rigorous quality control and validation processes, ensuring high-quality data for reliable AI model performance and accurate biodiversity assessments.

Research Ready

Preprocessed and annotated datasets ready for machine learning applications, biodiversity analysis, and comparative studies in marine ecology research.

Dataset Access
Access our curated eDNA dataset collection for research and collaboration
Sample Count1000+
Taxonomic Groups7 Phyla
Marker Genes18S & COI
Data FormatFASTA/CSV
Access Dataset

Google Drive • Use NSUT College ID • Research Use Only

Dataset Statistics

18S rRNA
Eukaryotic Marker
Universal primer coverage
COI
Metazoan Marker
Species-level resolution
Deep-Sea
Environment Focus
Underrepresented ecosystems
BOLD
Database Integration
Reference validation
Expected Impact

Transforming Marine Research

Our AI solution will revolutionize how researchers study and protect marine biodiversity

Accelerated Discovery

Enable rapid identification of new species in deep-sea ecosystems, accelerating the pace of marine biodiversity discovery and taxonomic research.

Enhanced Monitoring

Provide faster, more comprehensive biodiversity assessments for long-term ecosystem monitoring and conservation planning.

Research Accessibility

Make advanced eDNA analysis accessible to researchers without extensive bioinformatics expertise through user-friendly interfaces.

Projected Improvements
10x
Faster Processing
3x
Higher Classification Rate
5x
More Novel Species Detected

Ready to See Our Solution in Action?

Explore our interactive dashboard to see how AI transforms eDNA data into biodiversity insights

View Interactive DashboardLearn More About Our Research