Seq2Logo: a method for construction and visualization of amino acid binding motifs and sequence profiles including sequence weighting, pseudo counts and two-sided representation of amino acid…

By Martin Christen Frølund Thomsen, Morten Nielsen. 2012

430 citations recorded by the source corpus.

Seq2Logo is a web-based sequence logo generator. Sequence logos are a graphical representation of the information content stored in a multiple sequence alignment (MSA) and provide a compact and highly intuitive representation of the position-specific amino acid composition of binding motifs, active sites, etc. in biological sequences. Accurate generation of sequence logos is often compromised by sequence redundancy and low number of observations. Moreover, most methods available for sequence logo generation focus on displaying the position-specific enrichment of amino acids, discarding the equally valuable information related to amino acid depletion. Seq2logo aims at resolving these issues allowing the user to include sequence weighting to correct for data redundancy, pseudo counts to correct for low number of observations and different logotype representations each capturing different aspects related to amino acid enrichment and depletion. Besides allowing input in the format of peptides and MSA, Seq2Logo accepts input as Blast sequence profiles, providing easy access for non-expert end-users to characterize and identify functionally conserved/variable amino acids in any given protein of interest. The output from the server is a sequence logo and a PSSM. Seq2Logo is available at http://www.cbs.dtu.dk/biotools/Seq2Logo (14 May 2012, date last accessed).

Subfields: Molecular Biology

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Citations in the corpus

A Recurrent Mutation in Anaplastic Lymphoma Kinase with Distinct Neoepitope Conformations (2018, methodology): “Kullback–Leibler sequence logos were generated as previously described (84).”
The LIR motif – crucial for selective autophagy (2013, methodology): “0/) was used with Kullback-Leibler logo type and Hobohm1 clustering (threshold 0.63 and 0 weight on prior pseudo counts) (Thomsen and Nielsen, 2012).”
NetMHCpan 4.0: Improved peptide-MHC class I interaction predictions integrating eluted ligand and peptide binding affinity data (2017, methodology): “Binding motif plots were made using Seq2Logo with default parameters (30).”
Convolutional LSTM Networks for Subcellular Localization of Proteins (2015, methodology): “We use Seq2logo with the PSSM-logo setting to create the convolution ﬁlter logos (Thomsen & Nielsen, 2012).”
Logomaker: beautiful sequence logos in Python (2019, methodology): “A substantial number of software tools for generating sequence logos have been described (Bailey et al., 2009; Colaert et al., 2009; Crooks et al., 2004; Gorodkin et al., 1997; Maddelein et al., 2015; Menzel et al., 2012; Nettling et al., 2015; Olsen et al., 2013; O’Shea et al., 2013; Ou et al., 201”
Tertiary alphabet for the observable protein structural universe (2016, methodology): “Enrichment ratios were calculated by dividing positional frequencies from Seq2Logo (i.e., the same frequencies as used for generating the sequence logos) by background genomic frequencies of corresponding amino acid.”
Skylign: a tool for creating informative, interactive logos representing sequence alignments and profile hidden Markov models (2014, background): “Several logo web servers have been released since the introduction of logos [20,22-24], each with their own enhancements to logo presentation.”