All tools

Number antibody and T cell receptor variable domain sequences using IMGT, Chothia, Kabat, Martin, AHo, or Wolfguy. Reports chain type, the best HMM species match, and optional germline assignments.

Number antibody, T cell receptor, and shark VNAR/VHH sequences with language models, or renumber PDB, mmCIF, and mmJSON structures using ANARCII.

Perform multiple sequence alignment on protein or nucleotide sequences using the Clustal Omega algorithm.

Infer approximately-maximum-likelihood phylogenetic trees from alignments of nucleotide or protein sequences.

Fast protein structure search, comparison, and clustering. Search your structure against 200M+ AlphaFold predictions, compare 2 structures, or cluster up to 2500.

Sensitive sequence homology search using profile hidden Markov models. More accurate than BLAST for detecting remote homologs, ideal for finding evolutionarily distant protein family members.

Analyze immunoglobulin (antibody) and T cell receptor variable domain sequences. Identifies V/D/J gene segments, delineates CDR regions, and analyzes rearrangement junctions.

Build phylogenetic trees using maximum likelihood with automatic model selection (ModelFinder) and ultrafast bootstrap support.

Perform multiple sequence alignment using MAFFT (Multiple Alignment using Fast Fourier Transform). Supports multiple algorithms from fast progressive to highly accurate iterative methods.

Ultra-fast sequence search and clustering. 10,000x faster than BLAST for database searches, with powerful sequence clustering capabilities for proteins and nucleotides.

Rapidly align and compare DNA sequences using MUMmer4 nucmer. Perform pairwise genome comparisons to identify SNPs, indels, and structural variants between reference and query genomes.

Align protein, DNA, or RNA sequences with MUSCLE v5.3 using the native PPP or Super5 algorithm, with optional stratified and diversified ensembles.

RNAalifold computes consensus RNA secondary structure from a multiple sequence alignment. Uses covariation information to improve prediction accuracy for evolutionarily conserved structures.

Quantify transcript abundance from RNA-seq reads with Salmon selective alignment. Upload a transcript FASTA reference plus single-end or paired-end FASTA/FASTQ reads to produce TPM and estimated read-count tables.

Calculate batched Levenshtein distances and Needleman–Wunsch or Smith–Waterman sequence scores with StringZilla v5 CPU acceleration.

USAlign (Universal Structure Alignment) aligns protein, RNA, and DNA structures to compute TM-scores and generate superposed structures. Compare 3D structures to assess structural similarity.