Calculate sequence alignments, phylogenetic distances, GC content, and molecular evolution parameters. A comprehensive toolkit for researchers and students.
⚠️ Note: This calculator uses standard IUPAC nucleotide codes (A, C, G, T, U, R, Y, S, W, K, M, B, D, H, V, N) and single-letter amino acid codes. Sequences should be pre-aligned for comparison. Results are for educational purposes; validate critical findings with established bioinformatics software.
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Please enter valid input values.
Enter nucleotide sequence (A, C, G, T, U, N allowed)
Enter DNA coding sequence (must be multiple of 3, ATG start codon)
First aligned nucleotide sequence
Second aligned nucleotide sequence (same length)
Enter DNA, RNA, or protein sequence
Sequence Length
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nucleotides
GC Content
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%
GC Count
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G + C bases
AT/GC Ratio
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A+T / G+C
Melting Temp (Tm)
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°C (basic formula)
Base Composition
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A / C / G / T / other
Translated Protein Sequence
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Amino Acid Length
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amino acids
Molecular Weight (protein)
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Da
Codon Usage (first 20 codons)
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Sequence Length
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nucleotides
Identical Sites
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matches
Sequence Identity
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%
p-distance
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proportion different
Jukes-Cantor Dist.
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substitutions/site
Kimura 2-Parameter
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substitutions/site
Sequence Length
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residues
Molecular Weight
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Da
Molar Absorptivity
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M⁻¹ cm⁻¹
📝 Step-by-Step Calculation
Bioinformatics Formulas & Methods
Bioinformatics applies computational techniques to analyze biological data. This calculator implements fundamental sequence analysis methods used in molecular evolution and genomics.
GC Content
GC% = (G + C) / (A + C + G + T) × 100%
Percentage of guanine (G) and cytosine (C) bases. Varies by organism and genomic region, typically 25-75%.
Melting Temperature (Wallace Rule)
Tm = 2°C × (A + T) + 4°C × (G + C)
Simple approximation for oligonucleotides (14-20 bp). The Nearest-Neighbor model is more accurate for longer sequences.
Genetic Distance Models
p-distance = d / n
Proportion of differing sites. Simplest measure, does not correct for multiple substitutions.
dJC = -¾ × ln(1 - ⁴⁄₃ × p)
Jukes-Cantor (1969): Equal rates for all substitutions, logarithmic correction for hidden multiple hits.
dK80 = -½ × ln(1 - 2P - Q) - ¼ × ln(1 - 2Q)
Kimura 2-parameter (1980): Distinguishes transitions (P) from transversions (Q). More realistic than JC for most datasets.
DNA Translation (Standard Genetic Code)
Triplets of nucleotides (codons) translate into amino acids. ATG (Methionine) is the start codon; TAA, TAG, TGA are stop codons. The calculator uses the standard nuclear genetic code with all 64 codons.
Molecular Weight
MW = Σ (residue weights) + H₂O (18.02 Da)
DNA: dAMP=331.2, dCMP=307.2, dGMP=347.2, dTMP=322.2 Da RNA: AMP=347.2, CMP=323.2, GMP=363.2, UMP=340.2 Da Average protein residue: ~110 Da
The Molecular Clock Hypothesis
Zuckerkandl and Pauling (1965): nucleotide and amino acid substitutions accumulate at approximately constant rates, allowing genetic distances to estimate divergence times. Different genes and regions evolve at different rates — functional regions evolve more slowly than non-coding DNA.
Practical Applications
🧬 Phylogenetics
Genetic distances form the foundation of phylogenetic tree construction (e.g., Neighbor-Joining, which uses pairwise distances to infer evolutionary relationships).
🔬 Sequence Annotation
GC content analysis identifies CpG islands (near gene promoters), isochores, and horizontally transferred regions. Coding sequences have distinct GC profiles vs. non-coding DNA.
💊 Drug Design
Translation tools predict protein products from genomic sequences, essential for gene function analysis and identifying drug targets. Codon usage informs heterologous protein expression.
Human mtDNA has ~44% GC overall. This ND2 gene segment shows lower GC content typical of mitochondrial genes.
🔁 GFP Translation
Start Codon: ATG (Methionine)
First 30 AA: M A M V S K G E E L F T G V V P I L V E L D G D V N G H K F S V S G E G E G D A T Y G K L T L K F I C T T G K L P V P W P T L V T T L T Y G
Full Length:238 amino acids (~27 kDa)
GFP from Aequorea victoria forms a beta-barrel with an autocatalytic chromophore (residues 65-67: SYG).
📏 Human-Chimpanzee FOXP2
Alignment (30 bp): Two substitutions out of 30 sites
Bioinformatics combines biology, computer science, and statistics to analyze genomic, transcriptomic, and proteomic data. Key applications include sequence analysis, genome annotation, phylogenetic reconstruction, and protein structure prediction. The Human Genome Project (2003) demonstrated the power of computational biology, and today bioinformatics underpins personalized genomics, drug discovery, and agricultural biotechnology.
Sequence Analysis Fundamentals
GC content varies from ~25% to over 75% across organisms. Human GC content is ~41%. GC-rich regions associate with CpG islands and gene-rich areas; GC content affects DNA stability (3 H-bonds in G-C vs. 2 in A-T), melting temperature, and codon usage.
Genetic distance quantifies sequence divergence. p-distance is the proportion of differing sites but underestimates true substitutions. Jukes-Cantor and Kimura 2-parameter correct for hidden multiple substitutions — these distances feed into phylogenetic tree construction methods like Neighbor-Joining.
How to Use the Bioinformatics Calculator
Four analysis modes are available. Select the mode matching your task and enter your sequence data.
🧬 GC Content Mode
Paste a nucleotide sequence to get GC%, AT/GC ratio, base composition, and estimated Tm (Wallace rule). Useful for primer design and CpG island analysis.
🔁 DNA → Protein Mode
Translate DNA coding sequences using the standard genetic code. Choose from three reading frames. Results include protein sequence, length, MW, and codon usage.
📏 Genetic Distance Mode
Enter two aligned sequences to compute p-distance, Jukes-Cantor, or Kimura 2-parameter distances. Includes transition/transversion counts and % identity.
⚖️ Molecular Weight Mode
Calculate MW for ssDNA, dsDNA, RNA, or protein sequences. Also estimates molar extinction coefficients for spectrophotometric quantification.
Frequently Asked Questions
What is the difference between p-distance, Jukes-Cantor, and Kimura 2-parameter distances?
• p-distance is the proportion of sites where two sequences differ. It does NOT correct for multiple substitutions, so it underestimates true distance for divergent sequences. • Jukes-Cantor (JC69) assumes all substitutions occur at the same rate and applies a logarithmic correction for hidden substitutions. • Kimura 2-parameter (K80) distinguishes transitions (A↔G, C↔T) from transversions (purine↔pyrimidine), which typically occur at different rates.
For closely related sequences (<5% divergence), all three models give similar results. For divergent sequences, Kimura 2-parameter is preferred.
Why does my translated sequence have a stop codon in the middle?
A premature stop codon can indicate:
• Wrong reading frame: Try Frame 2 or Frame 3 to see if a different shift produces a full-length protein. • Intronic sequence: If you included introns, translation will likely stop early. Use only exon sequences. • Sequencing error: An insertion or deletion shifts the reading frame, introducing premature stop codons. • Pseudogene: Non-functional gene copies accumulate mutations including stop codons.
The standard genetic code has three stop codons: TAA, TAG, and TGA.
How accurate is the melting temperature calculation?
The calculator uses the Wallace rule (Tm = 2°C × (A+T) + 4°C × (G+C)), suitable for short oligonucleotides (14-20 bp). For more accurate Tm:
• Nearest-Neighbor (NN) method is the gold standard, accounting for adjacent base pair thermodynamics. NN Tms can differ by 5-15°C from the Wallace rule. • Salt concentration significantly affects Tm — higher salt stabilizes DNA duplexes. • DNA concentration also affects observed Tm.
For primer design, validate Tm predictions with dedicated tools implementing the NN method with salt corrections.
What is the significance of GC content in genome analysis?
GC content is one of the most informative sequence features:
• Genome signature: Different organisms have characteristic GC contents. Bacteria range from ~25% to ~75%. Human genome averages ~41%. • CpG islands: High-GC regions near gene promoters. ~60-70% of human genes have CpG islands, typically hypomethylated in active genes. • Phylogenetic classification: GC content helps classify organisms and bin metagenomic contigs. • Horizontal gene transfer: Genes with deviant GC content may have been acquired via HGT. • PCR optimization: Primers with 40-60% GC content generally work best.
How do I choose the right genetic distance model for my phylogenetic analysis?
Choosing the right model depends on your data:
• p-distance works for very closely related sequences (<5% divergence), such as within-species comparisons. • Jukes-Cantor suits moderately divergent sequences (5-20%) with roughly equal substitution rates. • Kimura 2-parameter is recommended when the Ti/Tv ratio deviates from 0.5. For mammalian mtDNA, Ti/Tv ratios can exceed 10-15, making K80 much more appropriate. • For protein-coding sequences, consider codon-based models (dN/dS) that account for selection.
Calculate distances with multiple models to check robustness. Phylogenetic software like MEGA, IQ-TREE, or RAxML includes model selection tools.
What are the limitations of this calculator compared to full bioinformatics software?
This calculator provides basic sequence analysis for educational purposes. Limitations vs. professional software:
• No BLAST or database search — only works with sequences you provide. • No multiple sequence alignment — requires pre-aligned sequences. Use MUSCLE, MAFFT, or Clustal Omega. • Simple evolutionary models — advanced models (GTR, HKY, gamma rate heterogeneity) require PAUP*, IQ-TREE, or MrBayes. • No tree reconstruction — genetic distances are inputs for Neighbor-Joining, Maximum Likelihood, or Bayesian methods. • Single-sequence translation — for batch processing, use Prokka or NCBI ORF Finder.
For serious research, complement this with MEGA, Biopython, NCBI tools, or Galaxy.