T-Coffee (Tree-based Consistency Objective Function for Alignment Evaluation) is a multiple sequence alignment software using a progressive approach. It generates a library of pairwise alignments to guide the multiple sequence alignment. It can also combine multiple sequences alignments obtained previously and in the latest versions can use structural information from Protein Data Bank (PDB) files (3D-Coffee). It has advanced features to evaluate the quality of the alignments and some capacity for identifying occurrence of motifs (Mocca). It produces alignment in the aln format (Clustal) by de
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T-Coffee (Tree-based Consistency Objective Function for Alignment Evaluation) is a multiple sequence alignment software using a progressive approach. It generates a library of pairwise alignments to guide the multiple sequence alignment. It can also combine multiple sequences alignments obtained previously and in the latest versions can use structural information from Protein Data Bank (PDB) files (3D-Coffee). It has advanced features to evaluate the quality of the alignments and some capacity for identifying occurrence of motifs (Mocca). It produces alignment in the aln format (Clustal) by default, but can also produce PIR, MSF, and FASTA format. The most common input formats are supported (FASTA, Protein Information Resource (PIR)).
==Algorithm== T-Coffee algorithm consist of two main features, the first by, using heterogeneous data sources, can provide simple and flexible means to generate multiple alignments. T-coffee can compute multiple alignments using a library that was generated using a mixture of local and global pair-wise alignments.
Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).