ABCC : Applications Web Page

Applications Web Page Welcome to the ABCC Accessible Application Web Page.

From this page, you can get information about our scientific applications and databases. To get more information about any topic, or to run an application, click on any of the menu items on the left-hand side. Program with a tag "Run" is runnable. This site continues to grow, so come back often to check out the many accessible applications available here at the Advanced Biomedical Computing Center (ABCC).

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RNA Analysis
EdScan
A program for discovering well-ordered folding segments in nucleotide sequences. The computer program EDscan is designed to calculate z-score Zscre data of local segments in a sequence. The standardized z-score Zscre is defined as Zscre = (Ediff - Ediff(w))/stdw, where Ediff of a local segment is Ediff = Ef - E, E is the lowest free energy of the optimal structure folded by the segment, Ef is the optimal free energy when all base-pairs formed in the original optimal structure are prohibited, Ediff(w) and stdw are the mean and standard deviation, respectively, of the Ediff scores computed by sliding a fixed-length window in steps of a few nucleotides from 5' to 3' along the searched sequence. Consequently, the measures Zscre and/or Ediff signify the stability and uniqueness of the predicted RNA secondary structure from the local segment. The greater the Zscre and/or Ediff of the segment are, the more well-ordered the folded RNA structure is expected to be. The program is based on the dynamic programming algorithm and implemented in Fortran 90 running on Unix.
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EFFold
A program for predicting a set of RNA secondary structures that are near optimal, and simultaneously to compile all possible stems that are thermodynamically favorable in RNA foldings. The primary approach in EFFold is to simulate a normal distribution of the energy rules by perturbing the free energy parameters of Turner's energy rules within the range of experimental errors under the predetermined parameters. Thus, uncertainties of thermodynamic parameters for the formation of RNA duplexes and loops in Turner's energy rules in the dynamic folding are reasonably considered in EFFold. Although the rules are derived from experimental measurements that have normal distributions of precision and accuracy, the rules in dynamic programming algorithm are treated as precise. In practice we often generate 50 or 100 artificial ``simulated energy rules'' (SER) and then compute the corresponding 50 or 100 structures with the lowest free energy by these artificial SER, respectively, using dynamic programming algorithm. These computed ``optimal'' structures are then compared and classified based on the structure similarity among them. A set of predicted structures can be ranked by means of their energy distribution computed from those optimal structures in the sample. The helical stems found to be thermodynamically favorable from the simulation are compiled. Those thermodynamically favorable stems can be used a pool of the structural element for constructing a phyloge- netic conserved structure. The program is based on the dynamic programming algorithm and implemented in Fortran 77 running on Unix.
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SegFold
A programs for discovering unusual folding regions (UFRs) in RNAs. The computer program SegFold is designed to calculate two scores, significant score (SIGSCR) and stability score (STBSCR) of local segments in a sequence by an extended search. In the extended search, the window size is systematically changed within a predetermined range (e.g., 40-350) in the potential interesting region which was previously detected by SigStb using a fixed-length window. The segment of minimal length and minimal scores of SIGSCR and/or STBSCR is selected as the region of potential interest. Consequently, UFRs in a sequence can be delimit precisely in the extended search. The two standardized scores are defined as SIGSCR = (E - Er)/stdr STBSCR = (E - Ew)/stdw where E is the lowest free energy computed from a given folded segment, Er and stdr are the sample mean and sample standard deviation, respectively, of the lowest free energies from folding a large number of randomly shuffled sequences with the same size and base compositions as the given segment. Similarly, Ew and stdw are the sample mean and standard deviation of the lowest free energies obtained by folding all segments of the same size that are generated by taking successive, overlapping, fixed-length segments stepped one or several bases at a time along the sequence. The lowest free energies of formation of the folded segments are calculated by the dynamic programming algorithm with Turner energy rules. The program is based on the dynamic programming algorithm and implemented in Fortran 77 running on Unix.
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SigStb
A program for discovering unusual folding regions (UFRs) in RNAs. The computer program SigStb is designed to calculate two scores, significant score (SIGSCR) and stability score (STBSCR) of local segments in a sequence. The two standardized scores are defined as SIGSCR = (E - Er)/stdr STBSCR = (E - Ew)/stdw where E is the lowest free energy computed from a given folded segment, Er and stdr are the sample mean and sample standard deviation, respectively, of the lowest free energies from folding a large number of randomly shuffled sequences with the same size and base compositions as the given segment. Similarly, Ew and stdw are the sample mean and standard deviation of the lowest free energies obtained by folding all segments of the same size that are generated by taking successive, overlapping, fixed-length segments stepped one or several bases at a time along the sequence. The lowest free energies of formation of the folded segments are calculated by the dynamic programming algorithm with Turner energy rules or Tinoco energy rules. The program is based on the dynamic programming algorithm and implemented in Fortran 77 running on Unix.
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RNAGA
A program for predicting a secondary structure common to a number of phylogenetically related sequences without the need for pre-aligned RNA sequences. One of the remarkable features of RNAGA is that RNA secondary structures are automatically optimized by not only the free energy of the formation of the structure but also the structural similarity among homologous sequences. The program operates in three stages. In the first stage, a genetic algorithm (GA) is used to generate a population of RNA secondary structures that satisfy certain conditions of thermodynamic stability. In this step, the free energy of a folded structure is taken as a fitness criterion. Secondly, we define a measure of structural conservation for the structure from one sequence with respect to those in other sequences. With this conservation measure as the fitness criterion, GA is then used to improve the structural similarity among homologous RNAs for the structures in the population of a sequence. Finally, those structures that satisfy certain conditions of thermodynamic stability and structural conservation are selected as predicted common structures for a set of homologous RNAs. These predictions are ranked in descending order based on the structural conservation score. The program is based on the genetic algorithm and implemented in Fortran 90 running on Unix.
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RNAfold
RNAfold reads RNA sequences from stdin and calculates their minimum free energy (mfe) structure, partition function (pf) and base pairing probability matrix. It returns the mfe structure in bracket notation, its energy, the free energy of the thermodynamic ensemble and the frequency of the mfe structure in the ensemble to stdout. It also produces PostScript files with plots of the resulting secondary structure graph and a "dot plot" of the base pairing matrix.
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CorreLogo
The CorreLogo server generates for a given RNA or DNA sequence alignment a three-dimensional representation (a "3D sequence logo"). The generated model contains quantities like mutual information, composition and single column information ("conservation") in one three-dimensional representation. This can be useful for visual inspection of the properties of a nucleotide sequence alignment and for RNA secondary structure prediction.
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KNetFold
KNetFold is a new software for predicting the consensus secondary structure for a given alignment of RNA sequences. It uses an innovative classifier system (a hierarchical network of k-nearest neighbor classifiers) to compute for each pair of alignment positions a "base pair" or "no base pair" prediction. In a recent publication it was shown that for a test set of 49 RFAM alignments, the performance of the method is higher compared to the programs PFOLD and RNAalifold. The method is also able to predict pseudoknots.
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COVE
COVE is a program to perform RNA sequence/structure analysis. COVE evaluates covariance models of RNA sequence and structure. RNA covariance models are full probabilistic models which describe the primary sequence and secondary structure consensus of an RNA family. They can be used for the following analysis tasks: - secondary structure-based multiple sequence alignment - consensus secondary structure prediction - secondary structure-based database searching COVE is an implementation of the algorithms described by Sean Eddy and Richard Durbin in "RNA Sequence Analysis Using Covariance Models", Nucl. Acids Res. 22:2079-2088, 1994.
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PKNOTS
Pseudoknots can be used for optimal minimum energy prediction of pseudoknotted RNA structures. The method is described in the paper by E. Rivas and S.R. Eddy which appeared at J. Mol. Biol 285:2053-2068, 1999.
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ViennaRNA
The Vienna RNA packages consists of a few stand alone programs and a library that you can link your own programs with. The package allows you to - predict minimum free energy secondary structures - calculate the partition function for the ensemble of structures - calculate suboptimal structures in given energy range - predict melting curves - search for sequences folding into a given structure - compare secondary structures including pairwise alignment. There is also a set of programs for analysing sequence and distance data using split decomposition, statistical geometry, and cluster methods. The following executables are provided: RNAfold predict secondary structures RNAsubopt calulate suboptimal structures in a given energy range RNAeval evaluate energy for given sequence and structure RNAheat calculate melting curves RNAdistance compare secondary structures RNApdist compare ensembles of secondary structures RNAinverse find sequences folding into given structures AnalyseSeqs analyse sequence data AnalyseDists analyse distance matrices RNAplot
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RNAjunction
RNA is versatile in both its structure and function. Within this database you will be able to find more than 12,000 extracted three-dimensional junction and kissing loop structures as well as detailed annotations for each. If you are interested in RNA as a building block for nano-scale design or if you are analyzing the properties of specific RNA motifs you should find utility in this site. The junctions in this database were extracted using a junction scanning algorithm from a number of structures from the Protein Data Bank. Coming from parent structures, both NMR and crystal, these junctions may be under contextual constraints. It is possible that these constraints play a critical role in the junction's conformation and stability.
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