Positional dependent information contents of aligned RNA/DNA or amino acid sequences are useful for the display of consensus sequences and for finding optimal search windows used in sequence analysis. The program calculates the positional information content of mono or poly nucleotides/amino acids from a FASTA file of aligned sequences and writes a Postscript (or encapsulated Postscript, EPS) file that can be viewed and included in text processors
Protein sequence logos using relative entropy.
Protein sequence alignment viewed as sequence logos. The total height of the sequence information part is computed as the relative entropy between the observed fractions of a given symbol and the respective a priori probabilities.
This server finds similar protein sequences in NR and aligns them, providing sequence logos that show relative conservation of different positions. Local structure predictions are done with neural nets for several different local structure alphabets, and hidden Markov models are created. Fold recognition and alignment to proteins in the Protein Data Bank are done, and a full three-dimensional model is constructed.
Seq2Logo is a web-based sequence logo 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 enrichment and depletion.
SeqLogos generates sequences logos from amino acid sequence alignment. Sequences logos are useful tools to visualize sequence patterns and represent a more informative alternative to consensus sequence
Sequence logos are a graphical representation of an amino acid or nucleic acid multiple sequence alignment. Each logo consists of stacks of symbols, one stack for each position in the sequence. The overall height of the stack indicates the sequence conservation at that position, while the height of symbols within the stack indicates the relative frequency of each amino or nucleic acid at that position.