PAcAlCI is novel intelligent algorithm based on least square support vector machine (LS-SVM) to predict how accurately ten different MSA tools could align a particular set of sequences.
MIReNA is a tool to find microRNAs with high accuracy and no learning at genome scale and from deep sequencing data. MIReNA validates pre-miRNAs with high sensitivity and specificity, and detects new miRNAs by homology from known miRNAs or from deep sequencing data.
assp (Assess Secondary Structure Prediction) takes a multiple protein sequence alignmentand estimates the range in accuracy that one can expect for a “perfect” secondary structure prediction made using the alignment.
OXBench includes data and software to evaluate the accuracy of protein multiple sequence alignments. It is a benchmark suite for multiple alignment algorithms that includes a large set of test alignments and software to aid in analysis of a method’s performance or relative performance.
SIB-BLAST (Simple Is Beautiful) is a novel algorithm developed to overcome the model corruption problem that occurs frequently in the later iterations of PSI-BLAST searches.The algorithm compares resultant hits from iteration two and the final iteration of a PSI-BLAST search, calculates the figure of merit for each “overlapped” hit and re-ranks the hits according to their figure of merit. The premise of the algorithm is based on the observation that the profile, namely, the position specific scoring matrix (PSSM), in the first two rounds of a PSI-BLAST search, is the least corrupted since it is comprised mostly of close homologs. These profiles are used to search for more distant homologs, which are used to generate subsequent PSSMs. As more distant homologs are incorporated into the PSSM, non-homologous sequences frequently get included also, thus leading to model corruption. Hence, “benchmarking” hits from later iteration against earlier round when the model is least corrupted should improve the accuracy of a PSI-BLAST search.
