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PASA / Program to Assemble Spliced Alignments
Allows automation improvement of gene structures in Arabidopsis thaliana. PASA was used in Eukaryotic genome annotation projects such as Rice, Aspergillus species, Plasmodium falciparum, Schistosoma mansoni, Aedes aegypti, mouse, human, among others. This tool is able to recognize and organize splicing variations supported by the transcript alignments. It can clean the transcripts, validate perfect alignments or procced to automatic genome annotation.
SFESA / Shift to Fix secondary structure ElementS in Alignments
A tool to refine pairwise protein sequence alignment, with a combination of sequence and structural scoring by locally shifting secondary structure elements. Taking a pairwise alignment as input, the SFESA web server searches against an in-house database of protein spatial structures to find the closest homolog of either sequence. It then refines the pairwise alignment by combining the sequence profile similarity and residue-residue contact information that were obtained from the homolog with the structure. Finally, it facilitates further analysis of the alignment results at the level of secondary structure, providing details about scoring for all shifts of secondary structure elements.
A web application for optimized model generation through sub optimal HMM-HMM sequence alignment. HHalign-KBest is useful to model the structure of protein domains using automatically optimized alignments and structural models in case of low sequence identity (<35%) between a query and a template protein. It can generate k suboptimal alignments (e.g. top-k scoring) rather than only the optimal one which may contain small to large errors. The method was benchmarked over 420 targets from the SCOP30 database. In the range of HHsearch probability of 20% to 99%, average quality of the models (TM-score) raised by 4.1%-16.3% and 8.0%-21.0% considering the top1 and top10 best models, respectively.
PROPER / PROtein-protein interaction network alignment based on PERcolatin
Offers a global pairwise-network alignment algorithm dedicated to protein-protein interactions (PPIs). PROPER aims to align social graphs from different domains. It is based on a two-stage procedure: (1) it uses the sequence similarities to generate a seed set for a percolation graph matching (PGM) algorithm; and (2) to align remaining couples, it uses only the network structure and the seeds generated from the first step as inputs to the PGM algorithm.
A stand-alone software program and a web-server that provide the functionality for implementing flexible user-specified alignment scoring functions and aligning pairs of amino acid sequences based on the comparison of the profiles of biochemical properties of these sequences. Unlike the conventional sequence alignment methods that use 20x20 fixed amino acid substitution matrices, PR2ALIGN uses a set of weighted biochemical properties of amino acids to measure the distance between pairs of aligned residues and to find an optimal minimal distance global alignment. The user can provide any number of amino acid properties and specify a weight for each property. The higher the weight for a given property, the more this property affects the final alignment.
PRODOC / PROtein Domain Organization and Comparison
Simplifies search for a given sequence of domains in various genomes, identification of domain fusion events, recognition of gene products with identical or similar domain compositions. PRODOC determines proteins with a circularly permuted or jumbled arrangement of the order of domains. It allows comparison of domain organization between two genomes of interest. This tool assists users to suggest possibilities for the functional annotation of domain-unassigned regions.
Employs neighbor-dependent propensities of amino acids as a unique parameter for alignment. NdPASA is a method for pairwise sequence alignment. It optimizes alignment by evaluating the likelihood of a residue pair in the query sequence matching against a corresponding residue pair adopting a particular secondary structure in the template sequence. Statistical analyses of the performance of NdPASA indicate that the introduction of sequence patterns of secondary structure derived from neighbor-dependent sequence analysis clearly improves alignment performance for sequence pairs sharing less than 20% sequence identity.
Evaluates the accuracy of protein sequence alignment methods. CASA is an implementation of the alignment accuracy benchmark. The server produces graphical and tabular comparisons of the accuracy of a user’s input sequence alignments with other commonly used programs, such as BLAST, PSI-BLAST, Clustal W, and SAM-T99. The website provides the sequences to be aligned and several lists of sequence pairs of different sizes from the full set of structure alignments in the benchmark.
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