Genomic Analysis

A DNA sequence analysis for sequence characteristics, GC content, and motif structures.

Aspects of DNA sequence analysis:

• GC Content Analysis
• Motif Identification: Identifying motifs for understanding gene regulation and protein-DNA interactions.
• k-mer Frequency Analysis: k-mers are subsequences of length k contained within a biological sequence.
• Sequence Clustering: Groups DNA sequences based on their similarity. We use GC content and sequence length as features for clustering.
• Variation Analysis
• Structural Variation Detection: Identify larger rearrangements.

Core Functionalities

Sequence Analysis

• DNA sequence analysis and manipulation
• GC content analysis
• Motif identification and analysis
• K-mer frequency analysis
• Sequence clustering

Machine Learning Applications

• Sequence Classification

  • Feature extraction from DNA sequences
  • GC/AT content analysis
  • K-mer frequency analysis
  • Random Forest-based classification

• Motif Prediction

  • Sliding window approach
  • Feature extraction from sequence windows
  • Position-based motif prediction
  • Random Forest-based prediction